IoT Analytics, a leading provider of market insights and strategic business intelligence for the Internet of Things (IoT), AI, Cloud, Edge, and Industry 4.0, today has published its latest research on the global cellular IoT module and chipset market.

The report reveals that shipments of cellular IoT modules and chipsets dropped 16% year-over-year in 2023; however, our research projects the market to climb back to near 2022 levels in 2024. The research article further delves into the evolution of cellular IoT modules and chipsets with the latest technological innovations in smart and AI-enabled cellular IoT modules as key drivers for the project growth.

Key insights:

• The latest update to the Global Cellular IoT Module and Chipset Market Tracker and Forecast shows that shipments of cellular IoT modules and chipsets dropped 16% year-over-year in 2023; however, the tracker projects the market to climb back almost fully to 2022 levels in 2024.
• The rise of smart and AI-enabled cellular IoT modules, which enable data processing and decision-making near or at the edge, is helping to drive this projected growth.
• AI is not the same across the board—the capabilities of AI-enabled cellular IoT modules vary between low, medium, and high based on the speed of AI inference, typically driven by the chipsets used.

Key quotes:

Satyajit Sinha, Principal Analyst at IoT Analytics, remarks “IoT devices are evolving beyond connecting devices and expanding to analyzing the data they produce to make swift, informed choices. As a result, there is a growing need for more computational power and intelligence, especially at the edge closer to the data generated. This trend is also apparent in the cellular IoT field, where integrating AI with cellular IoT modules and chipsets leads to more autonomous decision-making. It also minimizes data transmission over cellular networks, reducing bandwidth and costs. On-device AI models powered by NPUs enhance this capability by enabling smart decision-making at the edge.”

Cellular IoT module market update

Global shipments of cellular IoT modules and chipsets dropped 16% year-over-year in 2023, according to the updated Global Cellular IoT Module and Chipset Market Tracker & Forecast (Q1/2024 Update). Two factors contributed to this decline:

1. Inventory optimization: Initial supply shortages caused by the COVID-19 pandemic and trade tensions around the same time led to manufacturers overordering modules and chipsets in 2021 and 2022, resulting in a surplus of these on the market. To address the surplus in 2023, manufacturers prioritized using existing modules and chipsets, thus delaying new orders.
2. Economic uncertainty: Inflation, rising interest rates, recession fears, and renewed US–China trade tensions have created a cautious investment climate, impacting new orders.

Fortunately, corporate executives appear to be easing their economic concerns, which could lessen the impact of the second factor as supply rebalances with demand. As this balance is achieved, cellular IoT module and chipset shipments are expected to rebound in the near term and are forecasted to grow at a 22% CAGR until 2027, with the slump of 2023 almost fully eradicated by the end of 2024.

Also likely to help rejuvenate this market is the rise of smart and AI-enabled cellular IoT modules—technologies that leverage embedded computational resources to execute advanced data analysis or even AI inference directly on IoT devices. Together, shipments of these advanced modules are forecasted to grow at a CAGR of 76% until 2027.

Smart and AI-enabled cellular IoT modules represent the latest frontiers of cellular IoT connectivity—the latest interactions of cellular IoT technology operating alongside their more basic, yet still quite capable, predecessor modules worldwide. Below, we will look at the evolution of IoT modules and chipsets and delve further into AI-enabled cellular IoT modules, including a look at their various processing capabilities and some applications for these intelligent modules.

Evolution of IoT cellular modules

The evolution of IoT cellular connectivity can be seen as 3 overlapping generations: legacy, smart, and AI-enabled.

“AI-driven productivity is inevitably evolving as an essential to extend the capabilities of IoT devices, significantly [improving] operational efficiency by enriching the IoT device with edge computing.” – Eden Chen, General Manager of MC BU at Fibocom

In the beginning: Legacy cellular IoT modules

Legacy cellular IoT models have been around for nearly two decades, simply providing connectivity for IoT devices to send and receive data from other locations. They include a cellular chipset/baseband to connect to a specified cellular technology, e.g., 2G, 3G, 5G, or NB-IoT.

In 2023, legacy cellular IoT modules comprised 96% of global cellular IoT module shipments. While shipments of these modules are forecasted to grow at a CAGR of 18% until 2027, their share of global cellular IoT module shipments will begin to give way to smart and AI-enabled cellular IoT modules, as discussed below.

Example of a legacy cellular IoT module

An example of a legacy cellular IoT module is the EM9190 5G New Radio (NR) Sub-6 GHz Module from Sierra Wireless, a Canadian wireless communications equipment manufacturer. This module enables devices to connect to 5G networks with 4G and 3G fallback when 5G is unavailable. Sierra Wireless announced the EM91 series of these legacy modules in August 2020, which is fairly recent; however, this reflects that legacy cellular IoT modules are still in demand when edge processing is unnecessary.

*Note: US-based semiconductor and IoT systems provider Semtech acquired Sierra Wireless in January 2023.

A move toward the edge: Smart cellular IoT modules

Smart cellular IoT modules have been on the market for nearly a decade. In addition to providing the connectivity capability found with their legacy counterparts, these smart modules include powerful CPUs and GPUs for on-device data processing. They can also support operating systems like Linux or Android to enable advanced functions and multimedia capabilities.

In 2023, these smart modules comprised 2% of global cellular IoT module shipments; however, the tracker forecasts this number to rise to 10% by 2027, with a CAGR of 79%.

Example of a smart cellular IoT module

An example of a smart cellular IoT module is the CQS290 Smart Cellular IoT Android Module from US-based cellular IoT module manufacturer Cavli Wireless. Cavli announced the unveiling of this module at the India Mobile Congress in October 2023. This LTE Cat 4 module, with Android 12, runs on an ARM Cortex A53 quad-core processor and has a built-in Adreno 702 graphics processing unit (GPU).

Intelligence at the edge: AI-enabled cellular IoT modules

AI-enabled cellular IoT modules are relatively newer than their legacy and smart counterparts, having been on the market for over 5 years. Along with the connectivity capabilities of the other types of cellular IoT modules, AI-enabled versions include NPUs, TPUs, PPUs, or other dedicated parallel-processing chipsets (e.g., GPUs) for AI inference.

While still in its early stages, AI and cellular IoT convergence holds immense potential to revolutionize industries. Integrating AI directly into IoT modules means AI inference can occur at the edge, allowing for rapid and intelligent decision-making at the edge. This reduces data transmission over cellular networks, saves bandwidth and costs, and facilitates immediate, autonomous decision-making for time-sensitive applications. Further, embedding AI chipsets within connectivity modules can save space and streamline the form factor of IoT devices. In all, these modules are evolving from mere data communication enablers to intelligent edge nodes capable of handling certain workloads independently.

In 2023, AI-enabled cellular IoT modules comprised 2% of global cellular IoT module shipments. The tracker forecasts that by 2027, this will grow to 9%, with a CAGR of 73%.

Example of an AI-enabled cellular IoT module

In November 2023, China-based wireless communications modules vendor Fibocom announced the release of its SC228 LTE smart module, which is powered by Qualcomm’s SM6225 (aka Snapdragon 680) SoC. With its 8 processing cores (4 x A73 at 2.4GHz and 4 x A53 at 1.9GHz), the SC228 is designed to handle AI algorithms, such as image processing algorithms. It is geared toward industrial IoT, smart retail, in-vehicle infotainment, and similar applications. The system comes with Android 14 but is upgradable as new software develops. For connectivity, it supports 4G LTE, 3G, WiFi, and Bluetooth.

Capabilities and applications of AI-enabled cellular IoT modules

AI is not the same across all applications. Within AI-enabled cellular IoT modules, there are varying processing capabilities based either on the needs of specific applications or the limitations of the hardware. IoT Analytics generalizes these modules’ capabilities into three categories: low, medium, and high.

1. Low AI capability

Cellular IoT modules with low AI capability conduct AI inference at less than 5 trillion (or tera) operations per second (TOPS), the standard measure of AI performance based on the number of computing operations an AI chip can handle in one second. Common applications of these modules include:

• Acoustic event detection
• Gesture/Activity recognition
• Voice ID/ Keyword spotting

These low AI capability modules comprised 59% of global AI-enabled cellular IoT module shipments in 2023. While the tracker projects the number of shipments of these modules to grow at a CAGR of 30% until 2027, cellular IoT modules with medium and high AI capabilities are expected to grow faster.

Example of a cellular IoT module with low AI capability

Fibocom’s SC138-EAU module features a Qualcomm QCM6125 SoC with an AI engine capable of 1 TOPS.

2. Medium AI capability

Cellular IoT modules with medium AI capability conduct AI inference at 5–10 TOPS. Common applications for these modules include:

• Human detection
• Vehicle detection
• People counting
• Face detection

In 2023, these medium AI capability modules comprised 36% of all global AI-enabled cellular IoT module shipments. The tracker projects that the shipment of these modules will grow at a CAGR of 102% until 2027.

Example of a cellular IoT module with medium AI capability

Quectel’s SG-530C-CN module hosts a UNISOC P778 SoC, which contains an NPU and is capable of 8 TOPS.

3. High AI capability

Finally, cellular IoT modules with high AI capability conduct edge AI inference at over 10 TOPS. Common advanced applications for these modules include:

• AI-driven predictive maintenance
• Enhanced decision-making with advanced analytics
• AI-enhanced driver safety solutions
• Real-time monitoring for drowsiness and distractions
• Comprehensive safety analysis
• Intelligent voice assistance

According to the tracker, these high AI capability modules comprised 5% of all global AI-enabled module shipments in 2023. The tracker forecasts the shipments of these modules to grow at a CAGR of 128% until 2027.

Example of a cellular IoT module with medium AI capability

MeiG’s SRM930 module bears a Qualcomm QCM6490 SoC, which includes Qualcomm’s 6th Gen AI Engine capable of reaching an AI performance of 12 TOPS.

Analyst takeaway

IoT is evolving beyond mere connectivity—it now encompasses connecting devices, understanding the data they generate, and making fast, informed decisions based on this data. As such, computing power and intelligence are becoming increasingly essential, particularly closer to where data is generated—at the edge. Thus, it is beneficial to have a dedicated chipset, such as a GPU or NPU, that can be used for AI inference directly on IoT devices, whether embedded in the printed circuit board (PCB) or as a component within the main processor.

Cellular IoT modules are undergoing a similar evolution. Although still in the early stages, integrating AI with cellular IoT promises to transform various industries. However, the core technology is driven by chipset companies like Qualcomm, Sony Altair, and UNISOC. Other chipset companies like MediaTek and ST may enter this market soon. So far, as seen above, vendors are predominately using Qualcomm chipsets equipped with AI engines that utilize the chipsets’ CPU, GPU, or NPU components.

With the rise of AI-enabled cellular IoT modules, two trends are emerging that are worth watching:

• AI-enabled 5G modules in automotive: The adoption of AI-enabled cellular modules focused on automotive applications, especially with 5G connectivity, is expected to accelerate. By 2027, AI-enabled 5G modules for automotive applications are projected to constitute 21% of all AI-enabled cellular module shipments.
• AI in cellular LPWA modules. So far, most of the modules are focused on standard 5G and 4G technology (with 2G and 3G as fallbacks). However, cellular LPWA modules are already entering the scene. For example, the Sony Altair ALT1350 is a low-power, LTE-M/NB-IoT SoC equipped with AI capabilities for low-power acceleration. This chipset is designed for edge processing and tiny ML model inference, opening doors for AI-enabled modules in the cellular LPWA segment.

Disclosures

Companies mentioned in this article—along with their products—are used as examples to showcase market developments. No company paid or received preferential treatment in this article, and it is at the discretion of the analyst to select which examples are used. IoT Analytics makes efforts to vary the companies and products mentioned to help shine attention to the numerous IoT and related technology market players.

It is worth noting that IoT Analytics may have commercial relationships with some companies mentioned in its articles, as some companies license IoT Analytics market research. However, for confidentiality, IoT Analytics cannot disclose individual relationships.

The post The rise of smart and AI-capable cellular IoT modules appeared first on IoT Business News.

What tech skills companies recruited for in Q1 2024? AI, Gen AI, and 5G

IoT Analytics today released the results of their latest report titled: “State of Tech Employment”.

The report analyzes over one million U.S. job postings to determine which tech expertise and skills are in demand and assess the hiring intensity of 450+ companies across various sectors. The findings from Q1 2024 show that 1. AI-related job postings are on the rise, 2. 5G- and WiFi-related job postings are up, while most other connectivity technologies decline, and 3. Cloud-related job postings have notably fallen.

Key insights

• Tech job openings decreased 2% in Q1 2024 in the US and are now down 47% since their peak in April 2022, according to the inaugural State of Tech Employment Spring 2024 report.
• AI-related job postings increased in Q1 2024, driven by strong demand for generative AI expertise. The number of 5G-related job postings also increased, while demand for cloud-related expertise declined QoQ.
• Hiring density in the industrial automation industry currently tops other industries, with the telecommunications industry at the tail end.

Key quotes

Knud Lasse Lueth, CEO at IoT Analytics, remarks: “Our new State of Tech Employment Spring 2024 report highlights a pivotal shift towards AI and expertise in the tech industry. Despite a 47% downturn in overall US tech job openings since April 2022, we’re witnessing a surge in demand for generative AI skills. February also marked the first month of increase in total job openings after seven quarters of decline. AI hiring is widespread, but AI providers such as OpenAI, Nvidia, and Anthropic are clearly leading the pack—each firm is currently at the forefront of the hiring intensity ranking.”

Philipp Wegner, Principal Analyst at IoT Analytics, adds:

“The jump of AI-related job postings in Q1 2024 indicates that companies have realized that the talk of AI needs people that actually work on AI projects.”

The big picture: US tech role openings are down overall, but AI roles are up

The number of tech job postings decreased by 2% in Q1 2024 compared to Q4 2023, according to IoT Analytics’ inaugural 85-page State of Tech Employment Spring 2024 report. With that, Q1 marks the 7th consecutive quarter of overall declines in tech job openings in the US. Total job openings are now down 47% since their post-COVID peak in April 2022. For comparison, the US Bureau of Labor Statistics reports a 27% drop in overall monthly job openings over the same period, showing that the tech industry has certainly taken a hit in the recent economic slowdown.

However, on the bright side, February 2024 saw the first month-to-month growth in tech job openings since the start of the slump, at 3% compared to January 2024. Helping to steer this upward trendline was a significant climb in AI and AI-related fields, which will be discussed further below.

The State of Tech Employment report analyzes over one million U.S. job postings to determine which tech expertise and skills are in demand and assess the hiring intensity of 450+ companies across various sectors. Below are three key findings from the report that reflect the state of tech employment going into Q2 2024.

Key finding 1: AI-related job postings are on the rise

As a whole, job postings seeking expertise in AI and AI-related fields are up 4% QoQ, with AI itself climbing 8% QoQ. Most impressively, job postings seeking Generative AI (GenAI) expertise were up 38% QoQ in Q1 2024, and this steep climb helped propel the 3% bump in tech job openings in February 2023.

For recent historical context, AI-related job postings have followed a similar path as other tech job postings, peaking around April 2022 and declining significantly since then. However, in January 2023—shortly after the public release of OpenAI’s ChatGPT—the rate of decline in AI-related job openings began to steady while other fields continued declining. By July 2023, the number of AI-related job postings began to rise, increasing 18% through February 2023.

This upward trend in AI-related job postings correlates with corporate executives’ rising interest in AI. Compared to Q4 2022, the number of quarterly earnings calls mentioning AI in Q1 2024 has risen 19 percentage points, from 13% of calls to 32% of calls.

Executives are concerned about a labor shortage and skill gap in this area, thus creating the need to upskill existing or future workforces. Companies appear worried about losing existing AI talent, exemplified by Google’s co-founder Sergey Brin personally calling an employee to convince them not to move to OpenAI. Other executives (e.g., from Cognizant and Accenture) highlight the need to develop the skills in-house.

Key executive quotes on upskilling for AI

• “In 2023, 90% of our global workforce spent time in learning with 270,000 of our employees acquiring at least one new skill proficiency. And 88,000 completing AI and generative AI courses.” – Ravi Kumar, CEO, Cognizant, February 06, 2024
• “Invest more in the people than in the technology. […] There is no AI-ready workforce you can hire a year from now, or two years from now, or three years from now. You need to bring your workforce with you and develop them.” – Paul Daugherty, CTO, Accenture, 12 December 2023

A closer look at AI-related job postings shows that Python skills are very important for AI roles—52% of all AI-related job postings mention it, much more than other programming languages such as C++ (12%) or R (8%). Expertise related to TensorFlow (14%) and Pytorch (11%), both machine learning libraries, also play an important role. There is also a significant demand for cloud-related skills in AI job postings, with Azure (15%) topping AWS (10%) in terms of the skills mentioned.

The increasing demand for AI-related skills and expertise naturally influences the salary for skilled workers with desired skills. The platform Comprehensive.io indicates that the median salary of skilled employees in AI jobs is now $172,000 per year, 17% higher than that of a software engineer with a similar level of experience.

Key finding 2: 5G- and WiFi-related job postings are up, while most other connectivity technologies decline

Job postings seeking 5G expertise rose 13% QoQ in Q1 2024, the highest climb of connectivity-related job postings. This aligns with what IoT Analytics observed at the Mobile World Congress 2024 in Barcelona, Spain, where advancements in 5G technology to enhance quality and performance and enable private 5G connectivity were on full display.

WiFi-related job postings also rose in Q1 2024, though these only grew 2% QoQ. Meanwhile, in Q1 2024, job postings seeking 4G, cellular, Bluetooth, and LoRa expertise declined 3%, 6%, 9%, and 15% QoQ, respectively.

Key finding 3: Cloud-related job postings have notably fallen

According to the State of Tech Employment report, cloud-related job openings were down 3% QoQ in Q1 2024. Though this tech field has the highest number of job postings in absolute terms, the declining number of job postings is part of a continued downward trend since the peak of cloud-related job postings in April 2022. As discussed in the recent State of IoT Spring 2024, cloud revenue growth has reduced significantly in 2023 as cost optimization took center stage in many companies. That also impacted the cloud-related job postings. The job postings largely include companies that build products or services in the cloud and seek expertise in utilizing certain hyperscalers. Job postings that mentioned AWS dropped by 2% QoQ, Azure (-2% QoQ), and Google Cloud (-4% QoQ).

Other notable findings from the State of Tech Employment report

The State of Tech Employment covers more than just the changes in expertise and skills related to tech-related job postings. It also delves into the hiring intensity—the number of openings publicly displayed per 100 current employees—and layoff data of specific companies or industries.

Hiring intensity

Out of 7 tracked industries in the report (including the catchall “Other”), the industrial automation industry had the highest median hiring density in Q1 2024 at 3.1 open positions per 100 current employees. By comparison, the median hiring density across all industries tracked was 2.4.

Four industrial automation companies stood out in terms of hiring density:

• Johnson Controls International plc had a hiring intensity of 6.2
• Siemens had a hiring intensity of 4.8
• Schneider Electric had a hiring intensity of 4.4
• ABB Ltd. had a hiring intensity of 4.3

Companies in the telecommunications industry had the lowest median hiring intensity, with only 1 open position per 100 employees in Q1 2024. Some examples include:

• AT&T had a hiring intensity of 1.05.
• Verizon had a hiring intensity of 0.83.
• Orange had a hiring intensity of 0.26.

Layoffs

Some tech companies continue to lay off staff, although at a much smaller scale than a year ago. In Q4 2023, approximately 24,000 tech-related layoffs were registered, compared to 167,000 in Q1 2023—a stark decline. The areas with the highest cuts were:

1. HR – Our tracker shows that US-based cloud computing and virtualization technology company VMware cut 44% of its HR personnel in 2023.
2. Marketing – Our tracker shows that US-based software company Informatica, for example, cut 16% of its marketing team in 2023.
3. Support – US-based technology giant Microsoft, for example, cut its support staff by 18% in 2023, according to our data.

The post What tech skills companies recruited for in Q1 2024? appeared first on IoT Business News.

IoT Analytics released a research article that highlights 10 out of 41 telecom industry trends included in the Mobile World Congress (MWC) conference report.

This report presents a comprehensive summary of the key highlights and trends assembled by the IoT Analytics analyst team and discusses more than 130 companies.

Key insights:

• The current state of telecommunications was on full display at MWC Barcelona 2024.
• IoT Analytics’ three-analyst team produced a 123-page event report, covering 130+ companies, and presents its top 10 trends on the state of IoT & telecommunications here.

Key quotes:

Knud Lasse Lueth, CEO at IoT Analytics, remarks “Mobile World Congress Barcelona 2024 brought to light the ongoing evolution within the IoT and telecom sectors. AI showcases took center stage this year. 5G advances, the anticipation around 6G and a pronounced focus on sustainability was also visible. Our team put together an in-depth 123-page event report, covering major developments from more than 130 companies that presented or exhibited at the fair.”

Satyajit Sinha, Principal Analyst at IoT Analytics, adds that:

“Leveraging eSIM and eUICCs as a hardware-based root of trust represents an innovative step in enhancing IoT security. Securing hardware forms the foundational layer for chip-to-cloud security. As we approach the era of quantum computing, focusing on quantum-resistant solutions and cryptographic agility will serve as a proactive defense against new cyber threats.”

Mobile World Congress 2023

The Mobile World Congress (MWC) Barcelona 2024, which took place from February 26 to February 29, is the telecommunication (telecom) industry’s main event showcasing the latest technologies and solutions, such as 5G, edge computing, and AI.

The MWC saw a significant increase in attendance in 2024, with a rise of 14% compared to the previous year. The event drew in 101,000 attendees. It hosted 2,700 exhibitors—a testament to the industry’s resilience and the undiminished allure of cutting-edge mobile technologies.

However, attendance was still 7% lower than at MWC Barcelona 2019, before the COVID-19 pandemic. On the other hand, the number of exhibitors increased by 12% from the pre-COVID era, reaching a new five-year record high.

“MWC Barcelona embodies the energy and vibrancy of the mobile ecosystem. We are honored to host this special event, which, once again, has delivered an exceptional four days of debate, thought leadership, inspiration, and deal-making.” – John Hoffman, CEO, GSMA Ltd.

IoT Analytics had a team of 3 analysts on the ground during the event’s four days. The team visited approximately 60+ booths and conducted more than 50 in-person interviews to comprehensively understand the most recent developments. Nearly every meeting started with, “What’s new in MWC, apart from AI?”

That said, AI was a common theme among the numerous new products and projects showcased at MWC 2024, from network operations management down to the chipsets themselves. However, AI was not a part of every notable advancement.

Our research clients can refer to the full 123-page MWC Barcelona 2024 Event Report to read more about the myriad of new technologies, trends, announcements, and insightful quotes from key telecom industry players. This article only highlights some of the major trends.

10 IoT and telco trends observed at MWC 2024

The full report shares 41 telecom industry trends the IoT Analytics team observed, including AI integration, telecom and satellite convergence, security, and sustainability. Here, we will highlight 10 trends that showcase the future of telco IoT connectivity, with a summary of each.

1. AI integration is enabling smarter, more efficient networks

The telecom industry spotlighted the integration of AI into telecom networks, particularly Radio Access Networks (RAN), emphasizing the shift towards more intelligent and automated network operations. Propelling this trend is the need for cost reductions, enhanced user experiences, and the mitigation of skill shortages.

AI’s role in telecom networks now includes smart monitoring, efficient analysis, and improved anomaly detection—offering solutions to the growing complexity of networks and cybersecurity threats. Companies are focusing on user-friendly AI tools that are accessible to developers with varying levels of expertise in AI/ML, thereby addressing the pressing need for innovation in network management and security.

Sweden-based multinational telecommunications company (telco) Ericsson introduced the Telecom AI concept, emphasizing zero-touch operations, trustworthy AI, and AI’s integration into networks. This initiative underscores the industry’s move towards automation, with AI enabling networks to adapt to user demands dynamically. This fosters a more responsive and adaptive telecom infrastructure.

Meanwhile, Japan-based mobile network operator Rakuten Mobile partnered with OpenAI, the US-based developer of ChatGPT, to develop AI tools for the telecom industry. This partnership aims to deploy AI solutions to open RAN’s architecture to enhance customer service and network optimization.

2. Cellular network technologies are enhancing performance and services

At MWC 2024, the integration of standalone 5G (SA 5G) with network slicing, the commercialization of 5G-Advanced (5G-A), and AI’s foundational role in the impending 6G networks highlight an evolution in telecoms. Collectively, these developments enhance network performance, efficiency, and the capacity to support a myriad of new applications and services.

Network slicing, a significant innovation driven by SA 5G deployments, allows customized network segments catering to diverse needs, optimizing resources, and bolstering security. It facilitates novel business models by offering personalized network experiences underpinned by technologies like Open RAN Intelligent Controllers (RICs) and machine learning.

Regarding SA 5G with network slicing, Finland-based telecom and IT company Nokia demonstrated multi-access edge slicing in partnership with e& UAE, a UAE state-owned telco, over a live mobile network. Multi-access network slicing allows e& UAE to offer new premium slicing services across 4G/5G, fixed wireless access, and fixed access that can support several use cases and applications simultaneously. Further, US-based semiconductor company Qualcomm showcased AI-driven 5G RAN network slicing capabilities within its Edgewise Suite.

Meanwhile, regarding 5G-A, China-based telecom equipment and services provider Huawei announced at MWC 2024 the world’s first 5.5G intelligent core network, which offers a tenfold speed increase over the initial 5G speeds.

Finally, regarding AI integration into future 6G networks, South Korea-based telecommunications operator SK Telecom shared a proof-of-concept video demonstration of a collaborative AI integration effort between it, Japan-based telco NTT, NTT’s telecom-provider subsidiary DOCOMO, and Nokia. The demonstration was for this team’s implementation of AI in the 6G air interface, which aims to enhance performance while minimizing energy consumption.

3. GenAI is revolutionizing customer interactions and network management

The IoT Analytics team noted 20 generative AI (GenAI) showcases at MWC Barcelona 2024, highlighting a significant shift toward leveraging GenAI to enhance customer interactions and improve network operations. Telcos showcased various GenAI-powered solutions across different stages of development, with most aiming to provide real-time, efficient customer service and network troubleshooting.

Of the 20 identified GenAI showcases, 10 were customer interaction and support use cases, making it the largest use case. Only 5 of the 20 showcases have been rolled out across the respective organizations or to customers—most others are either being piloted or their status is otherwise not known.

UK-based multinational telecom company Vodafone showcased its updated TOBi chatbot supported by Microsoft Azure’s OpenAI Service. TOBi has managed various customer interactions, including billing journeys, offers, and appointment booking, for Vodafone for years, but with GenAI integration, it can handle natural language well and personalize customer experiences. Meanwhile, Qualcomm presented its Edgewise Suite, a GenAI-powered RAN network management consultant system designed to simplify network and slice management tasks for RAN engineers. Its solution features impact assessment modeling, network topology, network performance tracking, gateway provisioning, and knowledgebases (including external data sources).

4. Semiconductor and AI advancements redefine the future of vRAN

The evolution of virtual RANs (vRANs) is at the forefront of mobile network development and is greatly influenced by semiconductor innovations and AI integration. Semiconductor companies are pivotal in this transformation, offering specialized processors and chipsets that boost vRAN performance, which can provide a cost-efficient, adaptable, and advanced architecture.

Meanwhile, AI’s inclusion within vRAN accelerator cards revolutionizes network efficiency, flexibility, and intelligence. AI algorithms run on specialized hardware such as CPUs, GPUs, and vRAN accelerator cards to optimize 5G networks.

Collaboration between leading telecoms is facilitating these advancements. At MWC 2024, Nokia and US-based semiconductor company NVIDIA unveiled a partnership integrating Nokia’s RAN software and layer 1 acceleration with NVIDIA’s CPUs for layer 2 processing and its GPUs for AI and vRAN acceleration. This collaboration marks a significant milestone towards AI-driven RAN solutions (AI-RAN)

US-based semiconductor company Intel announced the upcoming launch of its Xeon Granite Rapids-D processors, designed specifically for vRAN workloads. These processors will be equipped with high-performance, next-generation P cores and enhanced with Intel vRAN Boost acceleration.

5. AI integration into connectivity and chipset technologies

The previous trends highlight AI integration into telecom infrastructure, with advanced modules and chipsets to help accelerate AI. However, the technology industry is experiencing a transformative phase with AI integration into modules and chipsets themselves.

Telecom vendors are now embedding AI directly within connectivity modules and 5G chipsets, aiming to revolutionize how devices process data, manage network traffic, and optimize performance.

At MWC 2024, several companies showcased their latest module and chipset innovations with AI integration. For instance, Cina-based cellular module provider MeiG presented a comprehensive product line of AI modules—the SNM930 and SNM970—which boast AI computing power up to 48Tops and support high-end applications such as service robots.

Similarly, China-based cellular module providers SIMCom and Fibocom showcased their AI integrations. SIMCom introduced the SIM9650L Wi-Fi 6E module, featuring an 8-core processor and AI capabilities exceeding 14 Tops. This module is suitable for devices like intelligent point-of-sale systems and VR/AR devices. Meanwhile, Fibocom highlighted their SC208 module, powered by Qualcomm’s Snapdragon 460 platform and capable of efficiently handling complex tasks like 1080P video transmission and multi-camera inputs.

6. 5G RedCap chipsets, modules, and devices are advancing

Speaking of chipsets in general, several manufacturers unveiled new 3GPP Release 17-compliant 5G RedCap chipsets at MWC 2024. These chipsets emphasize enhanced power efficiency, lower development costs, and support for various applications.

Module manufacturers appear to be seizing the 5G RedCap opportunity by developing pre-tested modules that facilitate quicker and more reliable device development. These modules, often equipped with advanced power-saving features and high data throughput capabilities, are fostering the deployment of new devices and gateways across various industries.

For example, China-based IoT module manufacturer Lierda showcased its TE310 5G RedCap Industrial Gateway, equipped with a 5G RedCap NR90-HCN module, Gigabit Ethernet port, and Wi-Fi6 technology. Meanwhile, US-based private network solutions provider MosoLabs presented its Moso Connect 5G mobile adapter, which allows legacy machines with serial or ethernet connectivity to communicate over a private 5G network. Additionally, Ericsson demonstrated video surveillance capabilities using 5G AIoT cameras integrated with 5G RedCap modules.

Devices like these underscore 5G RedCap’s versatility and potential to enhance connectivity and reliability for various applications.

7. Cellular and satellite ecosystem convergence enhances IoT connectivity

The integration of satellite connectivity into cellular networks is revolutionizing global IoT deployment. Underscoring this trend is the proliferation of 3GPP non-terrestrial network (NTN) capabilities in chipsets and modules and the telcos’ embrace of satellite connectivity for ubiquitous IoT coverage.

At MWC 2024, the IoT Analytics team noted several collaborations and certifications highlighting this convergence. Examples on the telco front are Deutsche Telekom, a German telecom provider, launching IoT tariffs with geostationary satellite providers, and US-based non-geostationary satellite infrastructure provider Omnispace collaborating with MTN, a South African multinational telecom provider, to enhance 5G connectivity through low-Earth orbit satellites.

On the satellite front, in July 2023, US-based NTN service provider Skylo Technologies partnered with Keysight Technologies, Inc., a US-based electronics testing and measurement equipment manufacturer, to expand cellular testing to NTNs via a certification program for NB-IoT devices over satellite. At MWC 2024, Skylo announced that Keysight extended the number of available test cases to 145 in the Keysight RF/RRM Carrier Acceptance Toolset, which enables certification of 3GPP 5G Rel-17 NTN chipsets, modules, and devices for Skylo’s network.

Such advancements aim to enhance performance, reliability, and coverage, especially in remote areas where traditional connectivity is limited.

8. eSIM adoption for IoT and automotive on the rise

The global landscape of eSIM technology is witnessing transformative shifts, notably with China’s recent embrace of eSIM technology, advancements in pre-standard development for GSMA SGP.31/32 compliance, and the increasing implementation of eSIM/iSIM in IoT devices and vehicles.

After years of hesitation, China is now moving towards eSIM adoption. At MWC 2024, the IoT Analytics team observed strategic partnerships between major telecommunication entities, such as Chinese state-owned telecom operator China Unicom and eSIM technology providers Thales and Giesecke+Devrient.

“A sophisticated eSIM solution for China Unicom will help it reach a greater degree of security and reliability in its business development and user services in the 5G future.” – Eva Rudin, Vice President of Mobile Connectivity Solutions, Thales

On the regulatory and standards front, the introduction of GSMA’s new eSIM IoT specifications, SGP.31 and SGP.32, has prompted eSIM management companies to develop pre-standard solutions compatible with these requirements. IoT device manufacturing companies like Thales, Kigen, Webbing, and Redtea Mobile showcased advanced solutions that address the transition and coexistence of M2M and IoT eSIM standards, thereby facilitating the IoT ecosystem’s growth.

Moreover, the adoption of eSIM/iSIM technology in IoT devices and vehicles is gaining momentum, offering enhanced connectivity, flexibility, and scalability across various sectors, including pharmaceuticals and automotive. Initiatives like the Saga Card by Iceland-based pharmaceutical supply chain automation enabler Controlant and Deutsche Telekom, or German automotive company BMW‘s partnership with NTT Data for personal eSIM activation, underscore the vital role of eSIM/iSIM in enabling global connectivity and seamless network management for IoT solutions and connected vehicles.

9. On-device AI to quantum-resistant technologies enhance cybersecurity

In September 2023, IoT Analytics noted that 66% of cellular IoT modules shipped without dedicated hardware security. Fortunately, it seems the cybersecurity landscape is undergoing a transformative shift, driven by advancements in AI, enhanced IoT security through embedded universal integrated circuit card (eUICC) technology, and the development of quantum-resistant cryptography.

Integrating AI into cybersecurity solutions enables dynamic threat detection, prevention, and response. Traditional methods fall short in identifying novel cyber threats, but AI’s adaptability and learning capabilities ensure robust defense mechanisms. At MWC 2024, Israel-based endpoint security solutions provider Bufferzone highlighted this evolution by upgrading its endpoint security solutions to include AI-based security powered by Intel Core Ultra processors.

Further, eUICC helps fortify IoT device security by establishing a hardware-based root of trust. This approach allows for the local generation of cryptographic keys, leverages IoT-SAFE protocols, and enhances the security framework of IoT applications.

Notably, at MWC 2024, Ireland-based global IoT connectivity provider ZARIOT and UK-based IoT security solutions provider Crypto Quantique unveiled their collaboration to bolster IoT device security. Their solution integrates ZARIOT’s hardware root of trust SIM cards and Crypto Quantique‘s QuarkLink IoT device security platform to enhance secure provisioning, onboarding, and device lifecycle management.

10. Telcos and manufacturers strive for sustainability

Some of the above trends highlight energy efficiency as a driver or outcome of the respective advancements. IoT Analytics recently noted that discussions around sustainability and energy efficiency trended upward in Q1 2024 corporate earnings calls, and that trend appeared on showcase at MWC 2024.

Specifically, companies appear to be focusing on passive sustainability through 5G RAN energy optimization. Currently, RAN consumes approximately 70% of a 5G network’s total energy. As networks expand and data demand grows, the energy consumption of radio units and other RAN components escalates, negatively impacting not only operational costs but also environmental sustainability.

Based on observations at MWC 2024, vendors are focusing on passive sustainability efforts such as energy management in RAN. Key strategies include the following:

• Fronthaul control, cell admin state management, and energy-saving modes, all focusing on optimizing the power usage of radio units
• Enhanced power management states for servers and telemetry use, improving energy efficiency by monitoring and adjusting power usage in real time
• Deployment of RAN intelligent controllers, which use policy-based management and AI/ML techniques to enable intelligent energy management, including dynamically adapting network operations to current needs without compromising service quality

For example, Nokia showcased a new “extreme deep sleep” mode designed to reduce energy consumption. This feature uses Nokia’s AirScale radio architecture and its Reefshark system-on-chip chipsets and works by shutting down radio equipment during no-traffic periods, aiming for what Nokia calls “zero traffic, zero Watt.”

Additionally, VMware, a US-based cloud computing and virtualization technology company, presented its Network Efficiency framework, which was developed with Intel and Equinix, a US-based digital infrastructure company. The framework consists of two parts: a tool for analyzing energy usage and a tool to help discover cost savings. The former includes “green window”-based workload placement that simulates the impact of running some workloads during peak hours with lower energy costs.

“One of the main drivers for integration cost efficient energy saving features is ongoing global recession. Another driver is state policy with focus on ESG strict regulations and commitments of the companies to reach net zero in the next 10–15 years.” – Solution Architect at VMware

What these telco IoT trends mean for the future of connectivity

From AI integration across the network-to-device spectrum to enhanced security and sustainability, the telecom trends observed at MWC Barcelona 2024—presented above and in the MWC Barcelona 2024 Event Report—are going to have a significant impact on IoT connectivity and the telecom industry as a whole. As more and more mobile and IoT devices come online, being able to provision them and ensure data security will be important for the continued growth of the IoT market. However, most of the projects supporting these trends were either announced or demonstrated at MWC 2024 or are currently being piloted—it may take 2 or 3 years before we see mass commercialization or impact of these projects. That said, these trends suggest a future of interconnected, intelligent, and sustainable telecom ecosystems catering to evolving consumer demands and technological advancements.

The post Top 10 IoT & telco trends – as seen at MWC 2024 appeared first on IoT Business News.

IoT Analytics today released the results of the quarterly company earnings call analysis.

This analysis is based on a comprehensive dataset of Q1 2024 earnings calls from 6,000+ leading US-listed firms. The findings from Q1 2024 show that three key themes are currently trending in CEO discussions: 1. AI, 2. sustainability, and 3. election. These influential topics have captivated boardrooms worldwide and are shaping the future investment priorities for companies across various industries.

Key insights:

• According to the latest “What CEOs talked about” report, three themes gained noticeable traction in Q1 2024: 1) AI, 2) sustainability, and 3) elections.
• AI discussions continue to move away from ChatGPT and other chatbots and toward individual technologies, especially GPUs and LLMs.
• Economic topics like recession significantly declined, though inflation saw a bump in mentions in Q1 2024.

Key quotes:

Knud Lasse Lueth, CEO at IoT Analytics, remarks: “In Q1 2024, CEO discussions clearly reflect a growing focus on AI, with one in three executives highlighting its significance during their earnings calls. The discussions around GPUs and LLMs have seen a notable increase, indicating a deeper engagement with the technological aspects of AI. There is also a renewed emphasis on sustainability, although we have yet to surpass the engagement levels of Q1 2022. The report “What CEOs talked about in Q1 2024″ offers a comprehensive analysis of current executive dialogues. My primary insight? Both AI and sustainability are poised to be pivotal in shaping 2024.”

Philipp Wegner, Principal Analyst at IoT Analytics, adds that:

“In Q1 2024, the hype around ChatGPT has decreased further, and executives are increasingly discussing how to generate value by integrating LLMs into their operations and products.”

The big picture

In Q1 2024, economic concerns remained the most discussed topic area in corporate earnings calls. Inflation remained the most mentioned tracked keyword, rising 7% quarter-over-quarter (QoQ) to 48% of calls; however, recession and uncertainty had fewer mentions, down 22% and 11% QoQ, respectively.

AI and its related terms (e.g., generative AI, data centers, and LLMs) continue their rise.

Key rising themes in Q1 2024

1. AI

In Q1 2024, discussions regarding AI rose 17% quarter-over-quarter (QoQ) to 32% of earnings calls. This constitutes a new peak after a noted short decline in mentions of AI in corporate earnings calls in Q4 2023. Additionally, AI-related terms witnessed rises in their discussions:

• Generative AI (GenAI): +10.4% QoQ to 8.8% of calls
• Data center: +20.6% QoQ to 9.4% of calls
• LLM: +43% QoQ to 2.1% of calls
• AI infrastructure: +34.5% QoQ to 0.7% of calls

Discussions around US-based semiconductor vendor—and leading provider of data center GPUs—NVIDIA experienced a rise of 19% QoQ to 2% of earnings calls. This follows a slight QoQ decline in Q4 2023.

Following a trend noted in Q4 2023, GenAI has further cemented its separation from the groundbreaking ChatGPT as discussions seem to focus more on actual applications of AI rather than impressive chatbots.

Executives from nearly all verticals discussed how to integrate AI into their products and operations or how to prepare themselves for the age of AI. The CEO of British multinational oil and gas company Shell, for example, highlighted how AI assists their engineers in detecting anomalies remotely. The CEO of India-based IT services and consulting company Tech Mahindra announced that the company plans to upskill all IT staff in AI-related skills in the next financial year.

Key quotes on AI

“We have millions of sensors collecting over 5 trillion rows of data that our AI models, combined with our conventional models, used to monitor equipment 24 hours a day, 7 days a week, alerting engineers to anomalies from a distance.” – Wael Sawan – CEO, Shell plc, February 01, 2024

“We plan to train 100% of our IT talent in AI in FY 2025.” – Mohit Joshi – CEO, Tech Mahindra, January 24, 2024

Some executives discussed their LLM strategy quite in-depth. For example, US-based software and data company ZoomInfo’s president, David Travers, shared that the company is integrating LLMs agnostically. ZoomInfo developed its own LLM to support its operations but partnered with Anthropic to support its Copilot offering. It also leverages OpenAI’s ChatGPT in other aspects of its operations and offerings. Meanwhile, US-based business intelligence software and services provider MicroStrategy’s CEO, Phong Le, stated the company utilizes retrieval-augmented generation (RAG) to combine its data with OpenAI LLMs to support its flexible AI bot offering across industry verticals.

2. Sustainability

Sustainability had a resurgence in Q1 2024, climbing 18.5% QoQ to 21.8% of earnings calls. This follows a drop to its lowest point in two years in Q4 2023. Further, keywords related to sustainability also had significant gains:

• Energy efficiency: +50.4%QoQ to 3.2% of calls
• Renewable energy: +33.3% QoQ to 6% of calls
• Emission: +32.2% QoQ to 14.8% of calls

Since its peak in Q1 2022 at 26.6% of earnings calls, sustainability has generally hovered around 22% (±4 percentage points) of earnings calls, indicating it remains a topic of interest to executives. In context to this, February 2024 was the hottest February on record and the 9th consecutive month of record-breaking monthly averages. While the share of companies discussing has not grown much in recent years, vendors that market sustainability-related products and services frequently point out the business value, such as Germany-based automation and digitalization company Siemens’ CEO highlighting sustainability as a driver for business in almost every market.

Key quotes on sustainability

“Sustainability is a secular business driver in almost every market segment, such as electrification and renewables integration, energy efficiency, or safety in buildings, among others.” – Roland Busch – CEO, Siemens AG, February 13, 2024

“We also installed solar panels providing an extra 2.4 megawatt peak power compared to last year, and […] renewable energy community—the first ever energy community in Italy to be backed by an industrial company for the benefit of its local area.” – Benedetto Vigna – CEO, Ferrari N.V., February 1, 2024

3. Elections

2024 marks a year of elections in many countries and regions across the globe. Citizens of India, Indonesia, the EU parliament, the U.K., and the US are all scheduled to cast votes in upcoming elections this year—with Russia just having concluded its elections—and executives appear aware of this fact. The share of earnings calls mentioning election rose 28.4% QoQ to 17.2% of earnings calls. Notably, only 16.6% of companies based in North America discussed the upcoming elections, while companies in EMEA (19.2%) and APAC (22%) were much more likely to discuss the topic.

Elections in India (April–June 2024) and the European Union (June 2024) are coming up sooner than the presidential and congressional elections in the US, which are scheduled for November 2024. The analysis of earnings calls during the last presidential election gives a taste of what we can expect: 32% of all CEOs of North American earnings calls discussed the elections in Q4 2020. One keyword that had not been discussed for a while is rising strongly again: Trump. The keyword Trump rose 450% QoQ (though to only 0.8% of earnings calls).

Declining themes in Q1 2024

1. ChatGPT

While GenAI and LLMs appear to be developing into their own distinct topic areas within earnings calls, ChatGPT has further declined (-19% QoQ) in its mentions and was the only tracked AI-related term that did so.

This does not mean ChatGPT’s usage has declined. As of March 1, 2024, it had over 180 million users, and many companies have incorporated it into their operations. However, the release of ChatGPT and the availability of LLMs in easy-to-use web applications sparked new hype around AI in general. Now, as mentioned earlier, executives are moving past just ChatGPT and discussing broader AI with a focus on enterprise-grade projects and real-world use cases.

Key quote:

“Last year was the year of AI talk. Now, the conversation will shift to more tangible things, shift features, successful deployments, [and] practical value.” – Matt Calkins – CEO, Appian, February 15, 2024

2. Recession and most other economic concerns

Mentions of recession declined 22.3% QoQ to 7% of earnings calls in Q1 2024, as executives appear to be easing on this concern. Uncertainty also dropped a fair amount (-10.7% QoQ), though it still appeared in a quarter of earnings calls.

Key quote on recession:

“Even though we’ve got moderating economic growth, we are assuming an avoidance of a deep recession […].” – Mike West – President of Moody’s Investor Service, Moody’s Corporation, February 13, 2024

Not all economic concerns have dropped, though. After a slight drop in Q4 2023, inflation bounced 7% QoQ to 47.6% of Q1 2024 earnings calls and remained the most discussed tracked topic. This comes as inflation in the US was higher than economic forecasters had expected in January and February 2024. A jump in gas prices largely fueled this bump, though grocery prices generally remained flat during this period.

Key quote on inflation:

“The inflation has muted to a certain degree, but not gone away.” – Vimal Kapur – CEO, Honeywell, February 20, 2024

Mentions of interest rates also fell 7% QoQ to 35% of earnings calls, the second most-mentioned keyword we tracked. This is unsurprising, as the US Federal Reserve has held interest rates since July 2023. On March 20, 2024, the Fed indicated it still expects to cut interest rates three times in 2024, with the Federal Reserve Chair Jerome Powell adding that the surprising uptick in inflation in January and February 2024 had not changed the Fed’s picture of the economy: a cooling in inflation, though more gradual than previously expected.

3. War

War had the sharpest drop in executive mentions in Q1 2024, decreasing 28.7% to 5.8% of earnings calls. In Q4 2023, the Israel–Hamas war started, and the Russia–Ukraine war carried on, adding to geopolitical uncertainty during boardroom discussions.

However, the decline in the mention of war indicates that most industries have not experienced operational disruptions from these conflicts, even as Yemen’s Houthi rebels have conducted drone attacks on commercial vessels in the Red Sea (with the first fatal attacks on March 6, 2024).

What it means for CEOs

5 key questions that CEOs should ask themselves based on the insights in this article:

1. Sustainability: Given the increasing focus on sustainability, energy efficiency, and emissions in earnings calls, how are we tracking against our own emissions and energy savings goals, and what new sustainability initiatives should we implement or enhance?
2. Elections: How might the upcoming elections in the US, India, Indonesia, and the UK—and related global political shifts—impact our business, and what strategies should we develop to mitigate potential risks?
3. Recession and economy: How should we adjust our financial planning and strategies in response to ongoing muted business confidence, muted global GDP growth for 2024 and 2025, and declining concerns about recession and the current economic landscape by peers?
4. AI: As companies ramp up AI efforts (specifically generative AI), does our company have the necessary infrastructure, talent, and data to test and implement AI solutions effectively? Do we know where AI technologies add the most value to your company and might help us differentiate from our competition?
5. Labor market: Given rising inflation and ongoing skill gaps, how can we ensure our salary structure is competitive enough to attract top talent while also being sustainable for our business?

What it means for those serving CEOs

5 key questions that those serving CEOs should ask themselves based on the insights in this article:

1. Strategic alignment: How can I ensure that our company’s strategy aligns with the current trends in AI, sustainability, and political climates, especially considering their growing importance in corporate discussions?
2. Competitive analysis: What are our competitors doing regarding AI and sustainability initiatives, and how can we differentiate ourselves or learn from their approaches?
3. Risk management: What potential risks (e.g., market changes, regulatory developments, geopolitical issues) should I monitor that could impact our business strategy and operations?
4. Training and development: What training or development programs should we consider to enhance our team’s understanding and capabilities in AI and sustainability?

Long-term vision: How does the current focus on AI, sustainability, and the political landscape influence our long-term business vision and strategy?

The post What CEOs talked about in Q1 2024 appeared first on IoT Business News.

IoT Analytics has published a new analysis that provides an overview and insights into the LPWAN market in 2024.

This analysis is derived from the “Global LPWAN Market Tracker and Forecast 2015-2027 (Q1/2024 Update)” – a tracker that includes market data on worldwide LPWAN connections and module shipments from 2015 to Q4 2023, including market projections for 2024 to 2027.

Key Insights:

• LPWAN connectivity is on the rise. There were nearly 1.3 billion LPWAN IoT connections globally by the end of 2023, according to IoT Analytics’ Global LPWAN Tracker and Forecast 2015–2027 (updated Q1 2024). This is expected to grow at 26% CAGR until 2027.
• NB-IoT comprises 58% of these connections. However, that does not tell the whole story about NB-IoT’s global adoption, as China’s nationwide adoption policy has greatly skewed this number.
• In 2023, licensed LPWAN connections surpassed unlicensed LPWAN connections, even when excluding China’s saturation of NB-IoT, a licensed LPWAN connectivity technology.

Key Quotes:

Knud Lasse Lueth, CEO at IoT Analytics, remarks: “In less than a decade, LPWAN technology has transformed from a nascent market into 1.3 billion connections. This remarkable growth, propelled by both licensed and unlicensed LPWAN technologies, underscores the critical role of low-power wide-area connections in powering IoT applications across diverse industries. At IoT Analytics, our dedication lies in delivering precise, actionable insights that empower stakeholders to adeptly navigate the rapidly evolving IoT connectivity landscape.”

Satyajit Sinha, Principal Analyst at IoT Analytics, adds that:

“LPWAN technology is evolving rapidly. Integration with satellite IoT connectivity is a natural progression in the field and will likely pave the way for new applications and connect previously unconnected things. Both NB-IoT and LoRa technologies have important roles to play in this hybrid connectivity model, enhancing the efficiency and reach of IoT applications.”

LPWAN Market overview

There are nearly 1.3 billion LPWAN IoT connections globally, according to IoT Analytics’ Global LPWAN Tracker and Forecast 2015–2027 (updated Q1 2024), which tracks LPWAN market data at a granular level across regions, industries, and types. This represents approximately 8% of the over 16 billion connected IoT devices worldwide in 2023.

The LPWAN tracker forecasts that the number of LPWAN connections will grow at a 26% CAGR until 2027, reaching 3 billion at that time, or 10% of all IoT connections worldwide. Behind this growth is the need for use cases like remote monitoring that require infrequent data transmission and battery operation, which LPWAN is especially suited.

The tracker shares granular LPWAN market data across regions, industries, and technology types, including revenue, shipments, and connections. Here, we will look at three insights from the tracker that merit context, as discussed below:

1. China’s “Big Connectivity” strategy skews global LPWAN connection data
2. LoRa remains the leading LPWAN technology outside of China
3. Licensed LPWAN connectivity technology surpassed unlicensed in 2023, even when excluding China’s weighted adoption rate

Market insight 1: China’s “Big Connectivity” strategy skews global LPWAN connection data

Globally, NB-IoT has the largest share of LPWAN connections at approximately 54%. However, this does not paint a clear picture of the world’s adoption of this LPWAN technology.

In 2016, China—the world’s most populated country—made the nationwide rollout of NB-IoT part of its “Big Connectivity” strategy for 2016 to 2020 to support a wide range of use cases. One such use case is smart metering, in which China is a regional leader in adopting smart gas and water meters. According to the LPWAN tracker, by 2023, ~81% of all LPWAN connections in China were NB-IoT, and the country accounted for ~84% of all global NB-IoT connections.

The following charts help demonstrate the impact of China’s dedicated adoption of NB-IoT on global LPWAN connections. On the top chart, we see NB-IoT’s share of LPWAN connections skyrocket between 2016 and 2023—the timeframe for China’s “Big Connectivity” strategy. However, on the bottom chart, China’s LPWAN data are excluded from the global totals, and NB-IoT’s climb—while significant—is nowhere near as pronounced. By the start of 2024, LoRa had a sizeable lead over the other technologies.

This does not mean NB-IoT is not gaining steam elsewhere, however. As the bottom chart shows, when excluding China, NB-IoT comprised 20% of LPWAN connections in 2023—a quick climb since its 3GPP standardization in June 2016. By 2027, the LPWAN tracker forecasts NB-IoT to reach 23% of China-excluded global LPWAN connections, while LoRa is expected to maintain its lead at 36%.

Interesting new use cases are helping drive NB-IoT’s increasing share of LPWAN connections. In July 2023, Spain-based low-Earth orbit (LEO) constellation satellite operator Sateliot and Spanish multinational telecommunications company Telefónica successfully tested an end-to-end roaming 5G cellular network in space using NB-IoT. In January 2024, IoT Analytics noted this test as the most innovative IoT connectivity technology development in 2023.

Market insight 2: LoRa remains the leading LPWAN technology outside of China

When excluding all LPWAN data from China, LoRa has the leading share of global LPWAN connections at 41%—more than double NB-IoT’s share.

Though LoRa’s share of LPWAN connections is decreasing, the technology’s market is still forecasted to grow at a CAGR of 17% by 2027. Helping drive this growth are smart water and gas metering applications, sustainability applications, such as agricultural resource management and optimization, and asset monitoring and tracking solutions, such as US-based semiconductor manufacturer Semtech’s LoRa Edge technology.

Market insight 3: Licensed LPWAN connectivity technology surpassed unlicensed in 2023, even when excluding China’s weighted adoption rate

According to the LPWAN tracker and forecast, licensed LPWAN technology reached a milestone in 2023: its share of LPWAN connections surpassed that of unlicensed LPWAN connections without the assistance of China’s weighted adoption of NB-IoT, a licensed LPWAN technology.

When considering China’s adoption of NB-IoT, licensed connections had already surpassed unlicensed ones by 2020. However, as shown above, NB-IoT’s share of LPWAN connections is not representative of global adoption due to China’s dedicated nationwide rollout of the NB-IoT. Now, without China’s significant boosting considered, it appears that licensed connections are on the rise worldwide and are forecasted to comprise 58% of LPWAN connections in 2027.

Helping drive the rise of licensed LPWAN are cases like smart city management. China offers a good use case with its smart meters, but there are other case studies around the world. For example, Germany-based IoT sensor and data analysis company Sentinum sought to address inefficiencies with public waste management, such as waste collection trucks driving routes where some waste bins are not full. It wanted to use LPWAN connectivity due to its low-power demands, further adding to sustainability.

Sentinum partnered with Vodafone, a UK-based global telecommunications provider, to leverage Vodafone’s licensed LPWAN (specifically, NB-IoT) to reliably relay bin fill data to Sentinum’s backend servers and alert municipal waste disposal staff what bins need collection. Vodafone notes that some applications can experience a time savings of 40% and a CO2 reduction of around 25%.

Analyst assessment: Key LPWAN trends to watch

These insights are from the updated Global LPWAN Tracker and Forecast 2015–2027, which readers can leverage for granular data across regions and industries. Later in 2024, IoT Analytics is planning to publish a full LPWAN market report, which will dive into the LPWAN market data, trends, and company insights. For now, here are two trends worth watching: 1) cooperation and convergence and 2) addressing LPWAN’s limitations.

Trend 1: Convergence and collaboration

The LPWAN industry has evolved significantly over the last decade, and the technology has become more popular. With the market maturing and taking hold within greater IoT connectivity, there appears to be a shift from the early days of high competition to an increased focus on convergence and cooperation.

For example, on July 25, 2023, US-based semiconductor manufacturer Semtech Corporation announced a collaboration with UnaBiz, a Singapore-based IoT solutions provider specialized in LPWAN connectivity, to integrate Unabiz’s Sigfox 0G technology into Semtech’s LoRa Edge and LoRa Connect platforms. This partnership aims to create a cost-effective, versatile platform by offering Sigfox technology support in Semtech’s LR1110, LR1120, and LR1121 products through Sigfox-specific APIs.

Moreover, this initiative highlights the industry’s push towards sustainable, adaptable IoT solutions, allowing customers to choose optimal connectivity based on their unique use cases and sustainability objectives. It is these solutions that will drive the market through 2027, and possibly beyond.

Trend 2: Addressing LPWAN limitations

There are still some limitations of LPWAN that need to be addressed. For example, LPWAN was designed around point-to-point connectivity, not large-scale connectivity with heavy data loads. Higer packet transmission can make LPWANs susceptible to interference from a number of sources (e.g., atmospheric/electrical noise, other radio networks, or even jamming).

To address this, transmission protocols need to ensure that complete data structures are delivered to their endpoints. One notable approach gaining attention in the LPWAN field is from mioty Alliance, a group of businesses, institutes, and engaged individuals aiming to enhance IoT connectivity solutions.

The alliance’s solution is to leverage the Telegram Splitting Multiple Access (TSMA) method to split data packets into smaller subpackets at the sensor level and transmit the packets over different frequencies and time marks. An algorithm on the receiving end will monitor for mioty subpackets and reassemble them into complete messages, ensuring complete messages are received even if one or a few frequencies are experiencing interference.

The post LPWAN market 2024: Licensed technologies boost their share among global 1.3 billion connections as LoRa leads outside China appeared first on IoT Business News.

IoT Analytics has published a new analysis that highlights 10 emerging IoT trends driving market growth.

This analysis is derived from the comprehensive “State of IoT – Spring 2024” – a report on the current state of the Internet of Things, including market updates and projections, the latest trends, market sentiments, investments, M&As, industry expert opinions, and more.

Key Insights:

• According to the latest State of IoT – Spring 2024 report, IoT remains a top-three corporate technology priority.
• While AI has surpassed IoT in corporate prioritization, combining IoT and AI is on the rise and seen as a tailwind for the $236-billion IoT market rather than a disrupter.
• IoT Analytics identified 40+ current IoT market trends in this research, 10 of which are shared below.

Key Quotes:

Knud Lasse Lueth, CEO at IoT Analytics, remarks:

“In 2023, the IoT market demonstrated significant resilience among economic fluctuations and geopolitical tensions. We now estimate a robust growth of 17% per annum through 2030. This growth is fueled by an increase in connected assets and corresponding investments in AI and cybersecurity within the IoT sector.”

IoT remains a top corporate priority on the back of the current AI wave

IoT remains a top priority. IoT remains a top-three corporate technology priority while AI has taken over as the top technology priority, according to the latest 148-page State of IoT – Spring 2024 report. In recent surveys from PWC, KPMG, and BCG, respondents ranked IoT second or third after AI in terms of investment prioritization for emerging technologies, with AI coming in first across the board.

AI is a tailwind for IoT. The latest research finds that the growth of AI is a strong tailwind for the $236-billion IoT market, as companies are gaining interest in both AI and IoT within their organizations. One indication is from IoT Analytics’ analysis of company earnings calls: since Q3 2022, the mention of these two technologies in the same earnings call rose by 61%.

40 current trends identified by the IoT Analytics team. IoT Analytics’ market analysis relies on the valuable findings of its research analyst team and input from industry experts and advisors. These professionals contributed greatly to the spring 2024 State of IoT report, which showcases nearly 40 IoT market trends, along with IoT market data, recent IoT news and developments, and the performance and activities of IoT companies. The analysis shows that AI is not the only trend that will help drive the IoT market—10 of the trends discussed in our report can be found below.

IoT market expected to continue its growth path. IoT Analytics assesses that the 10 trends discussed in this article (among many more) will contribute to an IoT market CAGR of 17% until 2030, which is a cautious downward revision from the forecasted 19% CAGR in early 2023 but nonetheless a testament to the strength of the technology and its impact in a variety of markets.

CEO quote: “In 2023, the IoT market demonstrated significant resilience among economic fluctuations and geopolitical tensions. We now estimate a robust growth of 17% per annum through 2030. This growth is fueled by an increase in connected assets and corresponding investments in AI and cybersecurity within the IoT sector.” – Knud Lasse Lueth, Chief Executive Officer

Spring 2024 macro environment outlook: Lingering economic uncertainty, but IoT remains a key investment

Inflation coming down. The high inflation rates that we saw in 2023 seem to be subsiding. The Euro area inflation estimate for January 2024 was 2.8%, down from 2.9% in December 2023. In the US, consumer inflation has greatly eased from its peak of 9.1% in June 2022; it currently stands at 3.2% in February 2023. In Asia, some countries witnessed their lowest inflation levels since 2022.

Muted global economic growth projections. However, despite inflation progress, global economic growth projections are still below the historical annual average. The IMF forecasts a 3.1% global economic growth in 2024 and a 3.3% growth in 2025. Additionally, by December 2023, China—the second-largest economy and the country with the most connected devices—experienced its longest deflation streak since 2009, with prices declining for the third consecutive month. On the flip side, India’s economy has been outperforming the rest of the world.

IoT markets affected, but positive sentiment shows. The IoT market has seen positive economic news lately. Going into 2024, the Global Supply Chain Pressure Index is back to its long-term average, indicating a normalization of supply chains after stormy times during the pandemic. Additionally, business sentiment around IoT appeared overall positive, and many IoT companies reported significant year-on-year growth in both revenue and gross margin within the IoT sector in Q4 2023 (e.g., Supercom, Lantronix, and Globalstar). Unfortunately, some IoT companies have reported revenue declines and market weakness.

Analyst quote: “India has emerged as the ‘new China’ in terms of growth outlook.” – Philipp Wegner, Principal Analyst—Data

With this market backdrop, the following is a list of 10 notable IoT and tech-related trends and opinions identified by the IoT Analytics team as part of the research for the report with accompanying commentary:

Trend 1: Semiconductor companies invest in embedded chipset security

Semiconductor companies are increasingly investing in embedded chipset security to address the growing security threats IoT devices face. Securing hardware at the chipset level with secure elements and physical unclonable functions (PUFs) can help protect data flowing from edge devices to the cloud.

Example: The ecosystem of US-based semiconductor company Intel is growing with security partners like US-based digital authentication company Intrinsic ID. In February 2024, Intel Foundry added Intrinsic ID to its Accelerator IP Alliance program, aiming to ensure the availability of hardware-based root-of-trust solutions for the Foundry’s members. Accepting that security and reliability are valuable for applications, the Foundry opened access to Intrinsic ID’s QuiddiKey X00 product family of root-of-trust (RoT) solutions, which use standard SRAM as a PUF to generate a hardware RoT without needing additional security-dedicated silicon.

Analyst quote: “Semiconductor companies are at the forefront of tackling [the growing security threats IoT devices face], focusing on investing in embedded chipset security, as hardware forms the foundational layer.” – Satyajit Sinha, Principal Analyst – Connectivity and hardware

Trend 2: Industrial automation hardware is becoming more intelligent with the integration of AI chipsets

With the advancement in AI technology, companies are now looking to leverage AI at the edge, increasing the demand for real-time data analytics also at the edge. AI chipsets are also becoming smaller in size while growing in power. This trend has led to the emergence of IPCs and gateways embedded with AI chipsets, resulting in edge AI equipment that can perform parallel computations and train algorithms with very low computational response latency.

One benefit of using AI chipsets at the edge is the acceleration of data processing directly on the industrial equipment. This, in turn, reduces network traffic and enhances security, as the amount of data going to the cloud for processing is reduced.

Example: At SPS in November 2023, Germany-based automation and digitalization manufacturer Siemens presented its SIMATIC IPC520A Box PC embedded with 6-core NVIDIA Carmel for edge capabilities and NVIDIA Jetson Xavier NX GPU for A, making it suitable for AI-oriented operations. The IPC520A is designed to work seamlessly with AI-based applications across various industries, including factory automation and logistics.

Analyst quote: “Advancements in AI chipsets specifically designed for the edge are noteworthy. Embedding AI chipset in edge hardware such as IPCs and gateway is bringing decision-making closer to the edge and opening doors to new IoT applications such as machine vision.” – Kalpesh Baviskar, Market Analyst—Connectivity and hardware

Trend 3: The race for generative AI solutions in manufacturing has begun

Many industrial generative AI (GenAI)-based solution showcases are popping up. Vendors in the industrial and manufacturing space are racing toward developing GenAI-based solutions around coding, troubleshooting/support, operational analytics, and generative design, among others.

Examples: The following are just two of the six showcase examples found in the State of IoT – Spring 2024 report:

• At SPS 2023, Germany-based automation technology company Beckhoff showcased its TwinCAT Chat for the TwinCAT XAE engineering environment. The TwinCAT Chat Client enables AI-supported engineering to automate tasks such as the creation or addition of function block code, code optimization, documentation, and restructuring.
• In November 2023, Canada-based industrial AI software company Canvass AI announced the next evolution of its industrial AI software with Hyper Data Analysis. Through the use of GenAI, the Canvass
  AI software now incorporates learnings from text and visual-based data—adding it to production data streams—to advance traditional time-series-based AI insights for applications such as visual inspection, predictive maintenance, and quality within the process industries.

Analyst quote: “15 industrial automation and related vendors at SPS 2023 told us that GenAI is currently one of their top technology priorities. Moreover, we observed that these GenAI-based solutions are mostly in the stage of showcasing their capabilities rather than being widely available to the public. We believe this is to evolve in the coming months when vendors will go ‘live’ with these products for purchase.” – Fernando Brügge, Senior Analyst—Industrial IoT and AI

Trend 4: Generative AI has a positive (not negative!) impact on the manufacturing workforce

The race to integrate GenAI solutions in manufacturing—and how it differs from other technologies so far—revolves around the speed of adoption and the level of investment in the technology. Within three months of its public launch, ChatGPT reached an estimated 123 million users, an incredible feat for a new type of product. Additionally, soon after ChatGPT’s launch, Microsoft made a $10 billion investment in OpenAI, helping increase ChatGPT’s profile. This investment also showed the seriousness big tech companies like Microsoft are placing in this technology, leading companies across industries to question how they could leverage GenAI in their processes.

Adoption of new technology in manufacturing is often associated with negative impacts on the workforce. However, GenAI adoption in manufacturing is expected to boost employment and upskilling, shifting focus from automation to strategic growth. With GenAI contributing potentially $2.6–$4.4 trillion to the global economy annually, according to McKinsey, manufacturers are likely to deepen their investment in AI technologies.

However, AI’s impact on the workforce appears counterintuitive to common automation narratives. According to the Manufacturing Leadership Council, 32% of manufacturers anticipate an increase in headcount due to AI, suggesting that AI will create new roles and require upskilling rather than just automating existing ones. With 96% of manufacturers projecting increased investment in AI, there is a clear trend toward embracing AI for cost savings, growth, and revenue generation.

Emerging roles will likely include AI strategy managers and data specialists, reflecting a shift toward higher cognitive work.

Advisor quote: “The urgency for upskilling is underscored by the current lack of a dedicated AI training budget in 65% of manufacturing firms, signaling a potential increase in investment in human capital.” – Jeff Winter, Industry 4.0 expert and advisor

Trend 5: Companies are in danger of neglecting tech adoption basics in the rush to generative AI

GenAI is everywhere. Vendors are looking for ways to implement it in their products or to create new ones, and end users are eager to adopt. This rush, however, is not always helpful when it comes to adopting new technologies. The hype can often shift the mindset of adopters and vendors alike from “What technology should I use to alleviate X pain point?” to “How should I use this technology to alleviate some (sometimes non-existent) pain point?”

In almost all the surveys that IoT Analytics conducts—be it about IoT use case adoption, Industry 4.0, IoT software, or similar—“having a set goal” is always on the list of success factors that respondents mention. This is often forgotten whenever a new technology promises to “change the way we work” (the metaverse, for example).

Analyst quote: “[AI] should be treated like any other technology. First, think of the why, who, and how before deciding on implementing it. Second, if you are a (software) vendor, you should also keep in mind that being fast to innovate is not always the most important factor to keep your customers happy.” – Dimitris Paraskevopoulos, Senior Analyst—Quantitative data

Trend 6: Marketplaces are gaining in importance for technology procurement

Companies and sellers alike are embracing the subscription-based economy and seeking to simplify the procurement process. In January 2024, IoT Analytics published an article delving into the rise of B2B marketplaces, noting that B2B marketplaces are the fastest-growing procurement channel for software.

Analyst quote: “Cloud hyperscaler marketplaces currently lead in cloud-based software spending since many businesses have already committed cloud spending that can be utilized to procure software from these platforms.” – Justina-Alexandra Sava, Market Analyst—Software

Trend 7: Data fabric is emerging as an advanced evolution of data lakes

Though a relatively new term, data fabric describes a comprehensive data integration and management framework. It encompasses architecture, management tools, and shared data sets and is designed to assist organizations in handling their data.

Data fabrics differ from data lakes in that they go beyond storing raw data and from data warehouses in that they handle only processed or refined data. A core benefit of data fabrics is they offer a cohesive, consistent user interface and real-time access to data for all members of an organization, regardless of their global location.

Examples:
In 2023, several large data management vendors either upgraded their already existing data fabric solutions or launched new solutions:

• In February, US-based data integration platform provider Talend—one of the early users of the term data fabric—announced upgrades to their Talend Data Fabric solution, which was initially launched in 2015.
• In May 2023, US-based technology and software company Microsoft introduced Microsoft Fabric and launched it in November.

Analyst quote: “Given the increase in data complexity because of the exponential growth in big data, propelled by hybrid cloud, AI, IoT, and edge computing, there seems to be a good opportunity for vendors [offering data fabric].” – Mohammad Hasan, Market Analyst—Software and cloud

Trend 8: Hyperscalers pivot their edge strategies to innovate and secure their IIoT market position

Cloud providers are strategically adapting to the evolving IIoT market. In recent developments within the IIoT landscape, important shifts have occurred among major cloud service providers, with more focus on edge and containerization strategies.

Examples:

• Microsoft pivots its Azure IoT strategy toward Kubernetes. Microsoft has notably redirected its strategy toward Kubernetes, a move signaling a pivot within its Azure IoT Operations offering. This transition, accompanied by organizational restructuring and the discontinuation of the Azure Certified Device Catalog, highlights how Microsoft’s IoT strategy seems to evolve as technology and market dynamics shift.
• Google ends IoT Core but keeps Manufacturing Connect via Kubernetes. Similarly, Google’s decision to terminate its IoT Core offering in August 2023 has prompted attention. Despite this closure, Google’s IIoT solution, Manufacturing Connect, remains viable through its Kubernetes-compatible architecture, a strategic alignment reflecting the company’s technical prowess in this domain.
• AWS boosts IIoT investment with Sitewise and Monitron enhancements. AWS seems to double down on the IoT edge, which is particularly evident in the revitalization of Sitewise and other offerings like Monitron.

Advisor quote: “As the IIoT market evolves, cloud giants like Microsoft, Google, and AWS are moving further to the edge by embracing Kubernetes and enhancing edge computing capabilities. Their strategies revolve less around serving individual use cases themselves but rather participating in the edge (software) platform layer, which serves as the basis of digitalization for their partners and customers.” – Matthew Wopata, Edge solutions expert

Trend 9: Industrial vendors are strongly investing in DataOps solutions

Several vendors are investing in industrial DataOps solutions to tackle data integration and analysis challenges.
Industrial DataOps is an approach to data integration focusing on enhancing data quality through contextualization and modeling. This approach is experiencing growing attention within the industrial connectivity space.

Examples:

Some of the key vendors that offer industrial DataOps for data contextualization and modeling include:

• New vendors: Cognite – CDF, HighByte – Intelligence Hub, Prosys – OPC UA Forge, Litmus – Litmus Edge, Element – Unify, and Crosser – Flow Studio
• Industrial incumbents: ABB – Ability Genix, Aveva – PI System, Aspentech – Inmation, GE Digital – Asset Modeler, and Halliburton – DecisionSpace 365

Analyst quote: “In the world of AI, OT data stands as the cornerstone. It’s the quality and context of this data that truly empowers insights. We are seeing vendors aggressively advance DataOps tools for modeling and contextualization, with both new entrants and established OEMs perfecting their solutions. This concerted effort underscores the pivotal role of enhancing the quality of data from varied assets/software in unlocking digital transformation’s full potential.” – Anand Taparia, Principal Analyst—Industrial IoT

Trend 10: Robots charged per hour are starting to replace manual labor due to labor shortage

Manufacturing companies can benefit from equipment as a service (EaaS) by replacing labor-related operational expenses with another type of operational expense: robotics as a service (RaaS). RaaS is a relatively new business model, where a robot is provided by a machine builder on an outcome-based basis (paying per parts produced with the equipment) or runtime basis (paying per hours of equipment used) instead of as a direct purchase.

Example: US-based truck trailer chassis manufacturer Cheetah Chassis chose to hire welding robots per hour and explained that it could not find enough welders to fulfill demand. Its CEO, Garry Hartman, explained that it had trialed robotics before, but it was unsuccessful because it did not have the capacity to program and service robots. With RaaS, Cheetah Chassis can now enjoy the benefits of robotics without having to do so because it is provided by the RaaS vendor.

Analyst quote: “Companies are more likely to consume equipment by the hour if they are trying to fill in the gaps in the workforce (which is already paid by the hour) rather than purchasing new equipment.” – Matthieu Kulezak, Senior Analyst—Industrial IoT

Conclusion

The IoT sector is undergoing transformative changes. The new 148-page State of IoT – Spring 2024 report highlights the continuous evolution and resilience of the IoT market, driven by technological advancements and strategic shifts.

The shift of hyperscalers towards edge and containerization strategies, the integration of AI into industrial automation, the advent of generative AI in manufacturing, and the rise of data fabric solutions represent just a few of the dynamic developments redefining the enterprise IoT ecosystem. These trends, alongside other market data in the report, not only reflect the current state of the market but also provide a glimpse at future growth and innovation.

In navigating this landscape, it is crucial for businesses to stay informed and adaptable. With a projected CAGR of 17% until 2030, the potential for growth and transformation in the IoT sector is immense.

The post State of IoT Spring 2024: 10 emerging IoT trends driving market growth appeared first on IoT Business News.

IoT Analytics has published a new analysis focusing on smart meters.

It is derived from the comprehensive “Global Smart Meter Market Tracker”. The tracker includes installed base, shipments and shipment revenues for electricity, gas and water smart meters. The current analysis underscores the global adoption rate of smart electricity meters in 2024, providing an in-depth regional exploration and market forecast.

Key insights:

• By the end of 2023, 1.06 billion smart meters (electricity, water and gas) have been installed worldwide, according to IoT Analytics’ Global Smart Meter Market Tracker 2020–2030.
• Smart meters enable utility service providers across the world to digitalize their distribution infrastructure and services efficiently with near real-time data.
• North America has the most mature smart electricity meter market, with nearly 77% electricity meter market penetration, while Latin America has largely lagged in its adoption of the technology. Some European Union countries and the East Asian region, too, have high rates of smart electricity meter market penetration.
• South Asia, Latin America, and Africa represent a high-growth potential for smart meters, as some regional governments have become convinced of the need to update their aging grid infrastructure and are more actively engaging with smart grid industry stakeholders to develop regulatory policies to drive the adoption of smart meters.

Key quotes:

Knud Lasse Lueth, CEO at IoT Analytics, remarks: “IoT-based smart electricity meters have become a reality in the world but adoption varies greatly by country and region with countries like Sweden, France, or Canada having completed or nearly completed their roll-outs while others like Germany are yet to start their initiative in a meaningful way. India is likely to see the largest roll-out in the coming years.”

Adarsh Krishnan, Principal Analyst at IoT Analytics, adds that: “Digital transformation is sweeping the utility industry as global service providers’ smart meter deployment, a foundational smart grid technology, exceeds installed base of 1 billion units. While advanced economies embrace feature-rich smart meters, emerging markets focus on more cost-effective solutions for their grid upgrades. Furthermore, future advancements in AI and edge computing will bring greater operational efficiencies and innovative consumer services, creating sustainable and resilient smart grids.”

By the end of 2023, Utility Service Providers (USPs) around the world will have installed over 1.06 billion smart (electricity, gas, and water) meters, according to IoT Analytics’ updated Global Smart Meter Market Tracker 2020–2030. As IoT devices, smart meters are enabling energy and water USPs to build resilience into their operations with near real-time data from their distribution networks. With sustainability and the digitalization of utilities gaining traction worldwide, the installed base of these devices is expected to exceed 1.75 billion by 2030 (CAGR 6%), making the smart meter market a market to watch closely.

Smart electricity meter adoption is far ahead of the adoption of smart gas and smart water meters at this point, though the picture could change by 2030, with smart gas and water meter adoption expected to grow at 10% and 16% CAGR, respectively.

While the tracker provides in-depth coverage of smart electricity, gas, and water meters across 52 countries and 5 regions—including installed base, shipments, revenue, market penetration, and connectivity technology—IoT Analytics plans to offer highlights for each smart meter submarket separately as its own article, starting here with smart electricity meters.

Global smart electricity meter market snapshot

As of late 2023, the smart electricity meter market achieved 43% penetration of the overall global electricity meter market, according to the market tracker.

Electricity grid modernization initiatives started in the late 2000s in Italy and the US and accelerated to national rollouts throughout the EU and APAC regions after 2010. Regulatory policies—supported by financial incentives from regional or national governments—have contributed to this growth, as these policies have encouraged utilities to replace mechanical electricity meters with smart meters to modernize their grid infrastructure.

However, as discussed below, not all parts of the world are modernizing their electricity infrastructure. According to the tracker, North America, Europe, and East Asia have had higher rates of smart electricity meter market penetration, but adoption rates still vary from country to country. Meanwhile, Latin America, Africa, and South Asia have been slow to initiate smart electricity meter projects across the board. Some countries have initiated large-scale smart electricity meter projects in recent years, though project implementation complexity, lack of regulatory policies, and cost hurdles have delayed rollouts in several countries.

Overall, the market for smart electricity meters looks promising, as the Smart Meter Market Tracker forecasts these IoT devices to achieve 54% adoption of the overall global electricity meter market by 2030.

Smart electricity meter market and adoption by region

While the smart meter market tracker shares market data down to the country level, the following are highlights about the smart electricity meter market at the regional level.

North America leads in smart electricity meter adoption

North America has the most mature smart electricity meter market, with nearly 77% electricity meter market penetration by the end of 2023.

In the US, smart electricity meters have 76% penetration in the overall electricity meter market as of 2023, driven by large-scale deployments from investor-owned utilities. Smart meter rollouts in the US are expected to slow down or plateau during the forecast period due to smart meter’s high penetration rate and long product life cycles. As municipalities with smaller budgets and cooperative-owned utilities replace their traditional electricity meters with smart meters, smart meter annual shipments in the US should see marginal growth through the rest of the decade.

Furthermore, the region will get a further boost in smart meter shipments, as Canadian utilities Fortis and Hydro One have announced plans in 2023 to replace their existing AMI with 2nd-generation smart meters.

The APAC region has the second most mature smart electricity meter market, driven by nationwide deployments in China and Japan.

Meanwhile, the APAC region has the largest addressable market for smart electricity meters, with over 1.1 billion electricity metering endpoints. In 2023, the APAC region accounted for almost 60% of the global smart meter installed base and more than 50% of annual smart meter shipments. In 2023, the region achieved a smart meter penetration rate of 49%, largely driven by successful nationwide rollouts in China and Japan. With planned nationwide deployments in Australia, South Korea, India, Indonesia, and Singapore, the region’s smart meter penetration is expected to reach 67% by the end of this decade.

Of note in this region, in 2021, India’s government set an ambitious goal of installing 250 million smart electricity meters by the end of 2025. To execute the implementation strategy, the government of India launched the Revamped Distribution Sector Scheme (RDSS) not only to help financially support regional USP smart meter deployment and maintenance but also to expand the domestic manufacturing capacity to produce smart meters within India. By the end of 2023, India had achieved less than 3% of this goal, making it unlikely for this goal to be met before 2030. That said, by 2030, India is on track to become the single largest market for smart electricity meters in terms of annual shipment and revenue.

Europe comes third in smart meter adoption, though adoption differs greatly by country

Europe had 47% smart electricity meter market penetration across the continent at the end of 2023. France, Spain, Italy, Netherlands, and the Scandinavian countries initiated nationwide rollouts in the last decade, while Greece, Hungary, Poland, and Romania only started their initiatives more recently.

Germany, with over 50 million electricity metering points, has largely lagged in its adoption rate, with under 10% of smart electricity meters deployed to date. However, in early 2023, the government of Germany revamped its 2016 Metering Point Operation Act to speed up smart meter deployments, targeting a complete rollout by 2032. The new law stipulates binding deadlines for USPs with a roadmap that includes 20% rollout by the end of 2025, 50% by the end of 2028, and 95% by the end of 2030 for residential and small business consumers, with targets extending to 2032 for large consumers. However, there is strong market skepticism around achieving these deadlines due to the need for clarity from the government around financial support for USPs, AMI technical specifications, data privacy, and security governance framework.

Saudi Arabia and the UAE lead in the Middle East and Africa region

In the Middle East and Africa region, Saudi Arabia and UAE are leading the way in the implementation of smart meters for electricity. In 2022, Saudi Arabia’s state-owned USP Saudi Electricity Company (SEC) announced the successful deployment of approximately 11 million smart meters over three years. Meanwhile, the UAE, which already has 1.6 million smart electricity meters installed, is expected to complete its nationwide rollout by the end of 2029.

Latin America lags in smart electricity meter adoption

Finally, Latin America has seen the slowest smart electricity meter deployment, largely due to regulatory indecisiveness delaying project rollouts. Uruguay was the first country in the region to mandate a nationwide smart meter rollout, aiming for completion in 2026.

Analyst’s outlook on the electricity smart meter market

Though regional variations persist—with energy USPs in North America, Europe, and East Asia boasting much more mature markets than their counterparts—the regions of Southern Asia, Latin America, and Africa represent a high-growth potential for smart meters. Some key considerations for various stakeholders are as follows:

• Market saturation and marginal growth in advanced economies: The implementation of more advanced and feature-rich 2nd-generation smart meters is already underway or in the advanced planning stages in countries such as Sweden, Italy, Finland, and Canada. This is likely to marginally drive up the average selling price of smart electricity meters.
• Cost sensitivity in emerging markets: In regions such as South Asia, Latin America, and Africa, where penetration rates are lower, some national governments are convinced of the need to upgrade their aging grid infrastructure and are actively engaging with smart grid industry stakeholders to develop regulatory policies and standards to drive the adoption of smart meters. However, these are also cost-sensitive markets where low-cost smart meters are more likely to be successful.
• Smart meter supply chain diversification: Several countries (e.g., Saudi Arabia, Mexico, Brazil, India, and Indonesia) that are initiating large-scale rollouts are stipulating that smart meter OEMs localize the manufacturing of 40% or more of the smart meter demand.
• Regulatory policy uncertainties: Policy indecisiveness creates complex and uncertain environments for smart meter stakeholders, hindering innovation and investments that subsequently delay smart meter deployments, as seen in countries such as Brazil, India, Mexico, and South Africa.
• Future innovations and market trends: Innovations in ICs, edge computing, and AI (TinyML), as seen in 2nd-generation smart meters, may help reduce strain on communication networks, improve real-time responses to grid fluctuations, build resilience, and enhance data security and privacy.

Based on the Global Smart Meter Market Tracker 2020–2030, the traditional USP industry, once considered a laggard in adopting new technology innovations, is leading the digital transformation market with more than a billion smart meters and accelerating its digital footprint.

IoT Analytics will closely monitor this evolving USP industry and technology landscape to provide in-depth analysis and actionable insights into this market. Its next report on energy utilities (expected in Q2 2024) will provide a deep dive assessment of USPs in 10 countries to identify key trends in smart grid programs, such as distribution automation, green energy integration, and EV charging infrastructure.

The post Smart electricity meter market 2024: Global adoption landscape appeared first on IoT Business News.

IoT Analytics published an analysis based on the “IoT Commercialization & Business Model Adoption Report 2024” report highlighting 8 insights from OEMs with business models that are considered more successful.

Key insights:

• Many equipment manufacturers (OEMs) have significantly advanced their IoT strategies, introducing innovative software and services, and revamping their business models. This evolution has enabled some to expand their IoT deployments to millions of devices successfully.
• Connected products are now the norm – It is expected that by 2026 more than 50% of products sold by OEMs will be IoT connected.
• IoT Analytics’ 206-page IoT Commercialization & Business Model Adoption Report 2024 delves into OEMs’ approaches to IoT business models. It highlights key factors that distinguish the more successful OEMs from less successful ones, such as acting on customer equipment usage behavior.

Key quotes:

• Knud Lasse Lueth, CEO at IoT Analytics, remarks: “Our 2024 IoT Commercialization & Business Model Adoption Report, reveals pivotal insights into what differentiates successful IoT implementations among OEMs. A standout finding is the projection that over 50% of products sold by OEMs will be IoT-connected by 2026. The report also highlights the significance of leveraging customer equipment usage data as a cornerstone for innovation, enabling OEMs to offer tailored solutions that significantly enhance customer experiences and operational efficiencies. This report is a clarion call to OEMs everywhere: the path to IoT success is through deep customer insights and innovative business models. It takes years to get there but early innovators show that the journey is worth it.”

• Dimitris Paraskevopoulos, Senior Analyst at IoT Analytics, adds that “From the question of ‘Should I build connected IoT products?’ in 2014 to ‘How should I build my (next) smart connected products?’ in 2024, the shift in OEMs’ approach to IoT is evident. With over 16 billion active connected IoT devices globally, the transformation is not just about sales or specific partnerships. It’s about understanding customer behavior, analyzing it, and better serving their current and future needs.”

How to create a successful IoT business model

Less than 10 years ago, in November 2014, Michael Porter (one of the world’s most influential management thinkers and professor at Harvard Business School) and Jim Heppelman (former CEO at PTC) published a widely recognized article in Harvard Business Review titled “How Smart, Connected Products Are Transforming Competition.” In it, they argued that IoT-connected products would alter traditional industry structures, business models, and the nature of competition in many industries.

While the change has not been as quick as expected, 10 years later, we do have over 16 billion active connected IoT devices globally as of 2023, including consumer devices (e.g., smart homes and watches) and enterprise equipment (e.g., connected factory machinery, electrical equipment, and commercial vehicles). Most large OEMs have a connected product roadmap and, with it, a software and servitization strategy.

In 2014, when the article came out, many OEMs that IoT Analytics spoke with asked, “Should I also build connected IoT products?” This has since dramatically shifted; now, in 2024, the questions OEMs are asking are, “How should I build my (next) smart connected products?” and related to that, “What should the business model look like?”

Prominent examples of OEMs that have innovated their business model and subsequently scaled to hundreds of thousands or even millions of connected devices at this point include:

• BMW, with over 20 million connected vehicles on the road worldwide.
• John Deere, with over 500,000 connected agriculture- and construction-industry machines in the field.
• Schindler, with over 500,000 connected elevators around the world.

Even smaller OEMs are reaching impressive numbers with their connected devices. Take the example of Italy-based professional kitchen machinery manufacturer UNOX, a company with approximately 1,200 employees. Unox started its connected product proof-of-concept stage in 2015 and has since connected more than 30,000 ovens and introduced new revenue streams with it.

There are thousands of other examples of smart product/IoT business models that are scaling to these numbers of connected devices, and the resulting business implications should not be taken lightly—they are often core to the company strategy. Take, for example, US machinery giant Caterpillar, which has set a target of $28 billion in service sales by 2026. The data coming from smart connected IoT trucks, excavators, and wheel loaders play a crucial role in achieving that target.

“Our confidence is increasing that we will achieve our $28 billion services target by 2026. Through tools like the new Cat® Central and SIS2GO apps and insights from data on our more than 1.4 million connected assets, we are creating a superior customer experience as we help customers minimize downtime, improve utilization and extend product life.” – Jim Umpleby, Chairman and CEO at Caterpillar (2022)

In our research for the 206-page IoT Commercialization & Business Model Adoption Report 2024 (published February 2024), we looked at 100 OEMs like Caterpillar to understand: What are the takeaways and best practices these companies have developed as they are scaling their connected products to the thousands or millions?

The data are based on surveys with participants from these OEMs who have knowledge of and can speak to their respective OEM’s IoT business model.

Components of a successful IoT implementation

There are many tradeoffs when bringing a smart connected product to market, for example:

• Which features should we focus on developing?
• Do we monetizethe hardware, the software, a service, or the data? Or perhaps a combination of those?
• Do we charge once, monthly, or perhaps even per usage (pay-per-use)?
• Do we offer some features for free?
• Do we source the tech stack via an external vendor, develop it in-house, or find an open-source solution?

The report provides answers and viewpoints on each of these tradeoffs and highlights which IoT business models are considered to be more successful. This article does not go into the same depth as the report, but it highlights 8 insights that were uncovered during the analysis.

We split our analysis of IoT business models into 4 parts:

1. Making the case for connected equipment (e.g., determining the revenue contribution, outlining key benefits, and highlighting key beneficiaries of connected equipment)
2. Developing the IoT product (e.g., budgeting, sourcing parts, time to market, and developing the features)
3. Developing the business model (e.g., market positioning, key use cases/features, value chain, and revenue model)
4. Commercializing the IoT product (e.g., determining ways to monetize, developing measures to drive adoption)

1. Making the case for connected equipment

Insight 1: 40% of products sold by OEMs are connected.

The survey participants reported that, on average, connected products accounted for 40% of the product mix that was sold in 2023. The participants expect this average to rise to 54% by 2026, though OEMs in APAC are already seeing over 50% of products sold being connected.

Machinery OEMs and electrical equipment makers were the forerunners in this regard as of Q4 2023. However, respondents from OEMs in other major industries are expected to see their connected products take more of the share of the total products sold over the next three years and match those two industries. For example, according to the survey participants, ~34% of products sold by automotive OEMs in 2023 were connected. But by 2026, the participants from that industry expect that the share of connected products for their OEMs will reach 54%, the biggest expected increase among other major industries.

Insight 2: Gaining deep insights into customer usage is the single most valuable feature of connected products.

The research found signs that the core value of connected devices is to drive OEMs and customers closer together. 67% of the survey participants reported that generating deep insights into customer usage of their products and services is either extremely or very useful for their organization—the highest ranked in terms of benefits from connected products. Second to this was better management of customer needs, which 61% of OEMs reported as extremely or very useful.

However, it is not simply about sales or focusing on specific partnerships. Instead, companies find this information more valuable because they can understand customer behavior, analyze it, see how their product is broadly used, and better serve their current and future customers.

“What is happening on a single press might not be valid on a global scale. Machine data helps us to understand what is going on for certain press formats or applications. Since we have all the data from the market now, we do see regional shifts and shifts in applications. That helps us focus our company on what is most important for our customers.” – Thomas Göcke, head of digitalization, König & Bauer

2. Developing the IoT product

Insight 3: OEMs need 41 months to bring their connected products to market.

The research found that the survey participants’ OEMs average 41 months from project kick-off to their first sale (time to market), with 43% of them reporting time to market taking more than 45 months to reach their first sale. Participants in the automotive industry reported the slowest overall time-to-market, with an average of 53 months from project start to the first paying customer. Meanwhile, participants from electrical equipment OEMs reported the fastest, with an average of 33 months.

Insight 4: Microsoft, Cisco, and AWS are the three most mentioned vendors across the tech stack

According to the survey participants, OEMs appear to frequently outsource aspects of their tech stack. 150 unique vendors were mentioned by the 100 OEMs surveyed for this research. The top outsourced parts of the tech stack include connectivity services (e.g., cellular services), connectivity hardware (e.g., modems and gateways), and cloud-based applications.

The most mentioned vendors that the survey participants reported are Microsoft (mentioned in all 12 tech stack categories that we queried), AWS (mentioned in 11 out of the 12 categories), and Cisco (mentioned in 10 out of the 12 categories).

3. Developing the business model

Insight 5: Successful OEMs help their customers optimize workflows.

61% of survey participants from successful companies—those with an amortization time of 24 months or less for their connected product—shared that workflow optimization was crucial or of high value for their customers, while only 21% of less successful companies stated the same—a 40 percentage point gap. This gap, the largest when looking at how successful and less successful OEMs assess the value of the software or service to their customers, reflects that successful OEMs help their customers optimize their workflow.

A notable example of this from the report is German industrial machine manufacturing company Trumpf. Its Oseon software is a workflow optimization tool for sheet metal processors, with features including digital order management, traceability of materials and stock, and optimization of the overall order flow. Trumpf designed Oseon to help improve each step of the sheet metal production process across the workflow of the average sheet metal processor.

Insight 6: Upselling software based on customer usage is the most successful business model innovation.

When it comes to business innovations, OEMs have several options to explore and try, as shown in the preceding table. However, the best-performing innovation, according to the survey participants, is upselling software/services based on actual product usage, where OEMs observe customer product usage and offer relative add-ons. Of the 67 respondents who said their OEM tried this innovation, 60 (or 90%) of them shared that it was successful.

The most tried innovation is offering specific performance guarantees to the customers (e.g., specific uptime guarantees). This also had the second highest success rate at 59%; however, it also comes with more risk, as OEMs must be ready to stand by the promise and be prepared to address issues quickly.

4. Commercializing the IoT product

Insight 7: IT and data security concerns have not left the customers’ minds.

According to the survey participants, on average, the three biggest concerns/roadblocks that customers report when adopting new IoT-based digital services and software are:

• #1: IT/data security concerns
• #2: issues with integrating the product into legacy systems
• #3: lack of budget

Most notable in this statistic is that IT and data security concerns remained the top roadblock since 2020, when IoT Analytics last released a report on IoT business models for OEMs. These concerns are understandable since high-profile security breaches in connected products can remain fresh in the minds of many. For example, in 2021, hackers gained access to over 150,000 cameras produced by US-based building security solutions vendor Verkada, compromising customer data and giving video access to hospitals, jails, schools, and even Tesla cars.

Insight 8: Privacy and regulations are hindering the abilities of OEMs.

Along with customer concerns related to security, regulations aimed at protecting customer data and cyber security standards appear to be hampering European OEMs’ ability to make the most of their connected products. According to the survey respondents, on average, 71% of European OEMs felt that privacy and security laws were limiting their ability to make the most of their connected product solutions. Europe was the only region to increase in this regard from similar research in 2020; North America and Asia decreased by 22% and 18%, respectively, though 56% of North American OEMs expressed feeling similar limitations.

As this sentiment of hindrance by North American OEMs decreased, it is notable that 59% of North American OEMs stated that they own the data generated by their customers, surpassing both European and Asian OEMs by 17 percentage points. That said, 72% of North American OEMs reported that the customer has a say in whether the generated data is shared with the OEM.

Analyst takeaways and outlook

Since Michael Porter and Jim Heppelman’s paper in 2014, most OEMs have developed a business model strategy, finding what works best for them and their products. However, now that OEMs are looking to scale, adapting their existing business models to this growth presents new challenges.

The research in the IoT Commercialization & Business Model Adoption Report 2024 shows many successful commercialization models are scaling, but it shows a fair share of non-successful ones as well. A key question from this is, “Why are some connected IoT product OEMs more successful than others?”

Overall, it appears to come down to OEMs putting the focus squarely on the customer—but behind the scenes, this is more complex than it sounds. While many OEMs claim that they are getting better at putting themselves in their customers’ shoes, there is clearly still room for improvement. The IoT Analytics’ team, for example, struggled to find a good set of OEM webpages that have a clear and well-articulated IoT value proposition that is geared toward real-world customer problems.

Another struggle for OEMs is making the revenue from connected products meaningful. With some equipment costing hundreds of thousands of dollars and the related software available for only a fraction of that cost, many OEMs still struggle to make the business of connected products meaningful enough to the company’s top and bottom line.

One approach to addressing this is the equipment-as-a-service model. Of the various innovative business models in the IoT Commercialization & Business Model Adoption Report 2024, this model is the most innovative and, in turn, the most complex. It is designed around charging for either some or all of the equipment based on usage.

Of the various innovative business models in the IoT Commercialization & Business Model Adoption Report 2024, EaaS is the most innovative and, in turn, the most complex. It is designed around charging for either some or all of the equipment based on usage.

What it means for OEMs

7 key questions that OEM executives should ask themselves based on the insights in this article:

1. Using IoT for customer-centricity: How well do we understand our customers’ usage of our products, and are we leveraging this data to enhance their experience and address their specific needs?

2. Offering workflow optimization: In what ways can our IoT products help customers optimize their workflow, and are we communicating this value effectively in our sales and marketing efforts?

3. Business model innovation: How can we innovate our business model, perhaps through upselling based on customer usage or offering performance guarantees, to enhance profitability and customer satisfaction?

4. Pricing and monetization strategy: What is the most effective pricing strategy for our IoT products? Should we consider a pay-per-use model, subscription-based services, or a combination of different pricing models?

5. Security and privacy concerns: How are we addressing IT and data security concerns in our IoT products, and are we compliant with the latest privacy and cybersecurity regulations, especially in different geographical markets? Can we prove this to our customers and communicate it effectively?

6. Equipment-as-a-Service (EaaS) model: Could the EaaS model be applicable to our products, and how can we structure it to provide clear value propositions and strong customer service?

7. Scaling challenges: As we scale, what are the key challenges we need to prepare for, particularly in terms of adapting our business model and maintaining a customer-focused approach?

The post How to create a successful IoT business model – Insights from successful OEMs appeared first on IoT Business News.

As we kick off 2024, the IoT Analytics team has again evaluated last year’s main IoT developments in the global “Internet of Things” arena.

This article highlights some general observations and our top 10 IoT stories from 2023, a year characterized by multi-decade high interest rates, a challenging macroeconomic environment, and, of course, the advent and excitement of generative AI (gen AI).

General IoT 2023 market

2023 was a year of surprises—both positive and negative. The U.S. and several other Western countries proved highly resilient in the face of higher interest rates and elevated inflation, and they avoided a much-anticipated recession. The 2023 global GDP growth of 3.0% ended up more solid than many had expected at the beginning of the year but still trailed the historic average by 0.8 percentage points.

The Nasdaq Composite, one of the key indices for technology companies, rose 43% in 2023 after dropping 33% in 2022. Not only did investors celebrate the potential peak in interest rates, but they also saw new opportunities with the hype around gen AI. Chipmaker Nvidia (ticker symbol NVDA) gained 246% in 2023, Amazon (AMZN) gained 77%, Microsoft (MSFT) gained 58%, and Alphabet (GOOG) gained 57%—all outshining the Nasdaq.

Against this backdrop, IoT 2023 markets held up steadily, with the number of connected IoT devices growing to approximately 16.7 billion (exact update coming in a few weeks) with roughly $235 billion in IoT enterprise spending (IoT Analytics will publish the 2023 IoT spending later in Q1).

The public relevance of the term “IoT,” which peaked in Q1 2022, continued to see strong interest, holding steady at around 10–20% below the Q1 2022 peak despite the renewed focus on AI (see Google trend graph in the lead image of this article). We did notice, however, that the use of the term “IoT” in corporate earnings calls declined 16% from Q4 2022 to Q4 2023.

With many organizations now managing millions of IoT devices (case in point: in Q4 2023, consumer giant Nestlé announced 2.8 million connected devices through the AWS IoT platform), do not assume that IoT is fading in importance. Quite the opposite: IoT is scaling for many organizations. Our take: IoT is not the “cool” term it used to be. In 2023, companies loved talking about the AI opportunity instead, but at the same time, IoT is quietly scaling.

Top 10 notable IoT 2023 developments

Throughout 2023, we monitored significant developments regarding IoT technology as part of our continued coverage of the field. In our opinion, these are the top 10 notable developments of IoT in 2023 (in chronological order of the leading stories we highlight).

1. Most notable IoT-related regulation: The EU’s NIS2 cybersecurity directive

In January 2023, the EU’s second Network and Information Security Directive (NIS2) became active. This cybersecurity directive comes as a follow-up to the first NIS directive (introduced in 2016) to address shortcomings from the first version, namely inconsistent implementation across member states in terms of what organizations were considered essential.

The new version enforces requirements for cyber risk management and incident reporting across 15 sectors. The intent of NIS2 is to clearly define the organizations meant to comply and to force them to deeply consider their cybersecurity posture, ideally protecting citizens and essential services from cyber threats.

Each EU member state has until October 2024 to adopt laws in compliance with NIS2 by 17 October 2024, giving companies time to look ahead and start compliance without much pressure now. However, as that deadline approaches, companies will begin to feel the compliance pressure, as failure to comply with its measures can cost companies up to €10 million or 2% of their annual global revenue (whichever is higher), as well as possible sanctions and audits.

The specific covered sector in the NIS2 that impacts IoT is digital infrastructure, which covers telecoms, DNS/TLD services, data centers, trust services, and cloud services. The EU projects the annual revenue of this sector to be €85.4 billion and notes that dependence on digital infrastructure opens companies to various cybersecurity risks.

In addition to NIS2, the EU is also expected to start enforcing its Cyber Resilience Act in early 2024. This legislation targets hardware and software products sold within the EU market. Once enforced, manufacturers will have 36 months to start applying the act’s guidelines.

Other notable IoT-related regulations in 2023 included:

2. Most surprising market destabilization: Tech layoffs

In January 2023, Microsoft announced it planned to lay off 10,000 employees between January and March 2023. Most notably for us, the third wave in March saw the largest cut for IoT-, AI-, and supply chain-focused personnel across various levels, functions, teams, and regions.

Microsoft did not have the most tech-industry layoffs—that unfortunate honor appears to belong to Amazon—but it was the most direct hit at IoT and related fields, especially from a company whose IoT services appear to be expanding, at least in the cloud (more on this below).

Google also experienced more layoffs than Microsoft. Though most of its layoffs appeared to be across the board, at times focused on their human resources and recruitment sections, Google shuttered its IoT Core service in August 2023 (also more on this below), meaning roles associated with that service either got moved elsewhere or scrapped altogether.

The fact that three companies seemingly at the forefront of the biggest tech trend in 2023, AI, laid off parts of their team shook the markets and created a lot of uncertainty. The IoT Analytics team noted that some of the laid-off people included high-performers who enjoyed industry-wide recognition, adding to the overall uncertainty of what was happening.

While the thousands of big tech layoffs represented only a small percentage of the respective company employee baseline, it was the startup scene that was most affected by the layoffs. For example, in December 2023, Israel-based grid-computing software startup Incredibuild, known for its accelerated software development technology, including for embedded IoT systems, laid off 40 employees, or 20% of its workforce (75% of which were based in the company’s HQ).

3. Most innovative IoT 2023 connectivity technology development: 5G in space

In July 2023, Spain-based low-Earth orbit (LEO) constellation satellite operator Sateliot and Spanish multinational telecommunications company Telefónica announced the success of their end-to-end test of a roaming 5G cellular network in space. The test process involved an IoT cellular device with a regular SIM card provisioned on Telefónica Tech’s Kite platform—all of this following 3GPP Release 17 non-terrestrial network (NTN) standards and leveraging narrowband IoT (broadly referred to as NB-IoT) communication technology. The device was able to switch between Telefónica’s terrestrial network and Sateliot’s non-terrestrial, low-earth-orbit (LEO) satellite network, demonstrating the integration of both network types using GSMA roaming.

The test, which the European Space Agency supervised, also involved Sateliot’s “Store & Forward” mode, a two-step authentication method developed by Sateliot to store information on a satellite when it is not in a position to connect with a ground station, forwarding the information when it enters coverage range.

IoT solution providers working with sectors that can often experience intermittent connectivity, such as transportation, logistics, or rural agriculture, will see applications to keep their customers connected when between terrestrial 5G network node ranges. Interestingly, in February 2023, Sateliot partnered with space and IoT hardware company GOSPACE LABS to provide 5G NTN NB-IoT connectivity to GOSPACE LABS’ MERATCH water management solution in the US, including water wells in rural areas, and in April 2023, Sateliot applied to the US Federal Communications Commission to bring its space-based 5G NB-IoT technology to the US market.

4. Most accelerated driver of IoT 2023 initiatives: Sustainability and ESG

Amit Kohli, Sr. Solution Director and Sustainability Leader, Orange Business:

“Gone are the [days] of greenwashing. Things are getting more serious in terms of reporting… [It’s a less] casual outlook [than] in the past.”

Europe, and international companies doing business in the EU, witnessed a wave of sustainability directives enter into effect. This is not just one news story but a series of stories that have been on the radar of many for several years.

In January 2023, the Corporate Sustainability Reporting Directive (CSRD) entered into force, enacted as a legal framework that requires all EU companies, except micro-enterprises, to submit annual sustainability reports starting in 2024. Then, on July 31, 2023, the European Commission adopted the first set of European Sustainability Reporting Standards (ESRS), which act as the roadmap for CSRD compliance and require large companies and listed companies to publish regular reports on the social and environmental risks they face. The ESRS became law on 1 January 2024 and now applies directly in all 27 EU member states. Large corporations now must report various IoT-type data, including pollution levels, GHG emissions, and resource use (e.g., water and energy consumption).

Additionally, in November 2023, the EU’s Renewable Energy Directive (Revised Directive EU/2023/2413) became enforceable across all member states. The member states have 18 months to transpose the directive’s provisions into their own national laws, with some provisions having a deadline of July 2024.

With strict adherence guidelines like these, it was no surprise to find increasing emphasis and prioritization on sustainability and energy management at the Smart Production Solutions (SPS) Fair 2023 in Nuremberg, Germany, in November. Coinciding with this, we have noted sustainability and environmental concerns as key topics during CEO earnings calls throughout 2023.

Other notable sustainability ESG regulations in 2023 helping drive IoT initiatives included:

5. Largest IoT-related acquisition: Renesas acquires Sequans

In August 2023, Japan-based semiconductor manufacturer Renesas Electronics agreed to buy Sequans Communications, a France-based cellular IoT chipmaker, for $249 million. The deal, expected to close in early 2024, is poised to expand Renesas’ foray into the IoT sector. The electronics company plans to integrate Sequan’s cellular IoT products into its microcontrollers and other products, enhancing its WAN market reach.

A few months prior, in June 2023, Renesas completed its all-cash acquisition of Panthronics AG, an Austrian-based fabless semiconductor company specializing in wireless products. The deal was originally made in March 2023 for approximately $95 million, and in its announcement of the completed acquisition, Renesas released 13 designs leveraging Panthronics’ NFC technology, showcasing the “embedded processing, power, connectivity, and analog portfolios” of both companies and what customers may be able to look forward to in the near future.

These are just the latest IoT-focused acquisitions by Renesas, but they are by no means the largest by the company financially. The following is a breakdown of its other IoT-oriented acquisitions in recent years:

• 2017: Renesas began its IoT expansion journey by acquiring Intersil, a provider of power management and analog solutions, for approximately $3.2 billion, targeting larger IoT, automotive, and industrial market opportunities.
• 2019: Renesas acquired US-based mixed-signal semiconductor manufacturer Integrated Device Technology, Inc. (IDT) for approximately $6.7 billion.
• 2021: Renesas acquired UK-based Dialog Semiconductor in a nearly $6-billion deal. Dialog had been one of Apple’s major chip suppliers, and this deal sought to expand Renesas’ reach into the IoT, power management, and connectivity solutions market.
• 2022: Renesas acquired Stradian, an India-based manufacturer of 4D imaging radars, for approximately $44 million, aiming to boost its automotive and industrial sensing solution offerings.

Other notable IoT-related acquisition announcements of 2023 included:

6. Most notable software developments: IoT cloud wars

The leading cloud providers, Google, AWS, and Microsoft, all recorded a strong slowdown in cloud revenue growth in 2023 as many organizations started to optimize their cloud spending. AWS, for example, grew by 40% in late 2021 but slowed to 12% growth in late 2023.

On the back of slowing growth, in August 2023, Google made its shock announcement from 2022 a reality and shut down its IoT Core service. The company seemingly now redirects its customers to partners such as Litmus Automation, KORE Wireless, or SoftServe to get the job done (Google’s IoT Core site lists these and other partners on its website to “meet the needs of IoT customers”)

How would Microsoft and AWS react in 2023?

AWS and Microsoft Azure did not follow suit but instead expanded their IoT cloud services in 2023:

Microsoft most notably announced Azure IoT Operations in November 2023, an expansion of its Azure IoT portfolio enabled by Azure Arc. It aims to enable “a cloud to edge data plane with local data processing and analytics to transfer clean, useful data to hyperscale cloud services such as Microsoft Fabric for unified data governance and analytics.”

AWS also announced several IoT extensions to its cloud platform services portfolio in 2023, including AWS IoT FleetWise vision system data and AWS IoT SiteWise Edge on Siemens Industrial Edge B2B marketplace (both in November 2023) as well as a new open-source, no-code IoT dashboard application, aimed at allowing users to visualize and interact with data from its AWS IoT SiteWise service.

7. Largest IoT-related funding round: Pragmatic

UK-based circuits manufacturer Pragmatic Semiconductor raised $389.3 million in 2023. Its latest funding round, Series D, closed on 6 December 2023 and raised the largest venture funding round for a European chipmaker at $206 million.

Pragmatic Semiconductor manufactures flexible, ultra-thin integrated circuits—thinner than a human hair—by leveraging thin-film semiconductors and polymers rather than silicon. The company aims to use the technology to bring intelligence to low-cost items as part of IoT applications, including smart packaging, recycling and reuse, traceability, and product authentication.

Very notable in this latest funding round was that the UK Infrastructure Bank led in investments (alongside M&G Catalyst). While the US and EU worked to establish an early warning system for semiconductor supply chain disruptions and increase investment and trade between the two on this technological front, the UK pursued its own national semiconductor strategy. The strategy aims to support UK leadership in the research, design, and advancement of chip manufacturing, and the UK Infrastructure Bank made the direct equity investment to support this effort.

Other notable IoT-related funding rounds of 2023 included:

8. Best performing IoT 2023 stock: Samsara

After making our IoT 2022 in review list of underperforming IoT company stocks, US-based IoT solutions company Samsara, Inc. (ticker symbol “IOT”), best known for its fleet management and telematics solutions, witnessed 180% growth in its stock in 2023, rising from $11.92 on 3 January to $33.38 on 29 December. Bolstering its climb were three better-than-expected quarterly earnings reports in March, June, and November.

Founded in 2015 by Sanjit Biswas and John Bicket, Samsara specializes in telematics, or “the convergence of telecommunications and information processing,” as it defines it. However, it has expanded its portfolio in the past few years to offer a more holistic connected operations platform and target other industries, such as utilities, manufacturing, and retail.

In 2021, we listed Samsara’s IOT stock as the biggest IoT-related IPO of that year.

9. Most notable IoT 2023 project: 250 million smart meters in India

250 million (or 1.5%) of the current 16.6 billion global IoT devices could soon come from one initiative alone: the ambitious national smart meter roll-out in India. However, though approved in 2021, the project has generally sputtered along, largely due to low domestic production means for the meters while trying to cover a whole subcontinent.

This year, to help spur the project and control the costs, the Indian government opened the projects to a total expenditure (TOTEX) approach, whereby the government can issue $40 billion in grants on completion of the projects and pay per meter. The project’s goal and financial approach have also opened the project to international support. For example, in June 2023, the US International Development Finance Corporation (DFC) announced a formalized $49.5 million investment to India-based smart meter manufacturer Genus Power Infrastructures, aimed at helping the company expand its production of smart meters.

Nonetheless, capacity remained low by the end of 2023, and only 8 million smart meter installations have taken place. As a result, it appears unlikely that India will meet this goal by the end of 2025, but with the spurred investment, the goal could be met not too long after. According to the government, 99 million of the 250 million smart meter contracts had already been rewarded at the end of 2023.

10. Generative AI and IoT breakthrough: None yet

How can recent advances in gen AI, which is mostly text- or image-based, be combined with IoT data, which is mostly based on time-series sensor data? This was one of the top questions we received in 2023.

The answer is … it is complicated.

However, throughout 2023, we have seen several developments on this front, but none have reached scale just yet. Nonetheless, the following are a few initial steps in gen AI and IoT convergence that caught our attention, some of which are discussed in our Generative AI Market Report 2023–2023 (released December 2023).

a) Using national language (gen AI) to query operational data (IoT)

In June 2023, Norway-based industrial software company Cognite launched Cognite AI, a generative AI solution designed for industrial operational data. Built within Gognite Data Fusion, it is meant to enable more tailored, business-specific data retrieval and contextualization in a private, secure manner. Siemens presented a similar example in November 2023, together with Schaeffler, at the SPS fair—which we covered in our SPS 2023 report.

b) Providing guided repair or operations (gen AI) based on operational data (IoT)

In September 2023, Google’s Cloud team shared a video demonstrating their gen AI solution alerting train maintenance operators to potential train issues and proactively providing possible causes and solutions based on manuals and past issue/repair reports.

In November 2023, Microsoft announced Copilot in Microsoft Dynamics 365 Guides, a solution that combines gen AI and mixed reality to assist frontline workers in their tasks. Paired with HoloLens 2 and IoT sensors, Microsoft claims that operators can pinpoint and identify specific assets and access relevant information about them—such as operational conditions or troubleshooting guides—in real time.

c) Using generated images (gen AI) to train vision systems (IoT)

In December 2023, Germany-based engineering and technology company Bosch announced it is piloting gen AI models in manufacturing, whereby they use synthetic, gen AI-created images to develop and scale AI solutions for optical inspection and optimizing existing AI models.

d) Using natural language (gen AI) to teach and control robots with vision systems (IoT)

In February 2023, Microsoft’s Autonomous Systems and Robotics Group released a paper entitled “ChatGPT for Robotics: Design Principles and Model Abilities” (Microsoft is a major backer of ChatGPT’s parent company, OpenAI). In this paper, the research team leveraged ChatGPT’s intuitive language capabilities to control multiple robotic platforms, including arms, drones, and home assist robots. Soon after, in April 2023, Microsoft published another paper, “ChatGPT empowered long-step robot control in various environments: A case application” (last updated in August 2023), in which they demonstrate a specific example of how ChatGPT could be used to convert natural language instructions into robotic actions.

In July 2023, Germany-based AI software and robotics company Sereact announced the release of PickGPT, a gen AI transformer that combines LLMs with computer vision. By combining these capabilities, users can use simple language to instruct a robot to sense conditions or identify objects, offering many potential use cases for remote sensing and control.

Others

We also noted a startup that, in May 2023, announced a revolutionary gen AI solution that would use gen AI to produce synthetical IoT sensor data that could then be used to train AI algorithms. The company has since deleted all references to the announcement.

The post IoT 2023 in review: The 10 most relevant IoT developments of the year appeared first on IoT Business News.

IoT Analytics published an analysis based on the “Generative AI Market Report 2023–2030” report and highlights the landscape with its top players in the data center GPU, foundational model and platform, and generative AI services markets.

Key insights:

• The generative AI market went from nearly nothing to a hot market within a year, as shown by IoT Analytics’ latest research report.
• IoT Analytics analyzed 3 interconnected markets for generative AI: 1) data center GPUs, 2) foundational models and platforms, and 3) generative AI services. Each has distinct aspects and market players.
• NVIDIA leads the data center GPU segment with a 92% market share, while OpenAI and Microsoft have a combined share of 69% in the foundational models and platforms market. The services market is more fragmented, with Accenture currently seen as the leader with a 6% market share.

Key quotes:

Knud Lasse Lueth, CEO at IoT Analytics, remarks: “The speed of generative AI innovation with new offerings coming on the market on a weekly basis is fascinating monitor. Nvidia with 92% market share for data center GPUs as well as Microsoft and OpenAI with a combined 69% market share in the models and platforms segment are firmly in the lead in their respective market segments. With hyperscalers developing their own data center chips, with the availability of powerful open-source models and with giants like AWS and Google looking to differentiate with their new offerings, it will be interesting to watch how much the early lead is worth for the current market leaders. I personally do expect both Microsoft and Nvidia to maintain their strong positions in the coming years but the gap to the competition will likely close a bit.”

Philipp Wegner, Principal Analyst at IoT Analytics, adds that:

“The Generative AI market is rapidly evolving, with established leaders and a growing number of startups. In 2024, it’s a make-or-break year for Gen AI vendors, as they navigate a crowded field of competitors.”

The leading generative AI companies

The rise of generative AI

Following its release of ChatGPT in 2022, OpenAI experienced an impressive one-year, zero-to-$1 billion revenue bump—surpassed only by US-based chipmaker NVIDIA, which managed to increase its data center GPU sales from $3.6 billion in Q4 2022 to an expected $16 billion in Q4 2023. When it comes to generative AI companies, these two stand out.

The generative AI foundational models and platforms market is expected to reach nearly 5% of global software spending by 2030

According to IoT Analytics’ Generative AI Market Report 2023–2030 (published December 2023), the generative AI software and services market reached $6.2 billion in 2023. Although it is still very early to forecast where things are going from here, the IoT Analytics research team expects the generative AI foundational models and platforms market to make up nearly 5% of global software spending by 2030 due to its disruptive nature and tremendous value potential.

However, this does not include the market for individual generative AI solutions. The team believes generative AI will become standard within most software in the near future. This also does not include the hardware market, such as for data center GPUs, since this market is looked at separately from software but is discussed below.

In this article, we dive into the data center GPU, generative AI foundational model and platform, and generative AI services markets, discussing what aspects of the generative AI field make up each market and highlighting the leading generative AI companies within them.

Market segment 1: Data center GPU market

a.) Market overview

The data center GPUs market refers to specialized GPUs designed to handle the extensive computation demands of modern data centers, which are the backbone of generative AI. Originally designed for rendering graphics, GPUs excel at parallel processing, which is fundamental for deep learning computations used in generative AI.

The report shows the data center GPUs market reached $49 billion in 2023—a booming increase from 2022 (+182%), mostly driven by one company alone: NVIDIA. Although the market for data center GPUs has seen steep price increases and is undergoing severe supply constraints, there is currently no reason to believe demand will decline in the next two years.

b.) Leading data center GPU companies

The data center GPU market at this point has one very clear leader. However, the market report shows that there are other promising startups and other established companies trying to make inroads.

The data center GPU market at this point has one very clear leader. However, the market report shows that there are other promising startups and other established companies trying to make inroads.

1. NVIDIA

NVIDIA leads the data center GPU market by a long shot, owning 92% of the market share. In 2023, the company’s quarterly revenue jumped 272%, from $4.3 billion in Q1 to a forecasted $16 billion in Q4.

The NVIDIA A100 Tensor Core GPU is the de facto standard for data center GPUs. However, as discussed in the report, hardware is not the only differentiator for NVIDIA. Some consider their developer ecosystem, CUDA, as NVIDIA’s biggest moat, and it is often cited as the key reason why NVIDIA is not set to lose its dominant position anytime soon.

2. AMD

The Data Center segment of US-based semiconductor AMD player, NVIDIA’s first real GPU challenger, grew by 21% from Q2 2023 to Q3 2023 and shared 3% of the market. However, AMD has big ambitions in 2024 to eat into NVIDIA’s market share. In early December 2023, it announced the release of its Instinct MI300 Series accelerators, which are cheaper than NVIDIA’s comparable accelerators and, as AMD claims, faster. AMD’s CEO, Dr. Lisa Su, forecasted at least $1 billion in revenue in 2024 through this chip alone, and Microsoft, Meta, and OpenAI stated they would use the Instinct MI300X in their data centers. AMD also recently launched ROCm 6.0 to provide developers with an ecosystem that is equally attractive to CUDA.

3. Intel and others

US-based chipmaker Intel, the traditional competitor to NVIDIA and AMD, has lagged behind on the data center GPU front. In May 2022, Intel’s Habana Labs released its second generation of AI processors, Gaudi 2, for training and inferencing. Though not as fast as NVIDIA’s popular H100 GPU, it is considered a viable alternative when considering price to performance.

Meanwhile, in July 2023, startup chipmaker Cerebras announced it had built its first of nine AI supercomputers in an effort to provide alternatives to systems using NVIDIA technology. Cerebras built the system, Condor Galaxy 1, in partnership with the UAE, which has invested in AI research in recent years.

Market segment 2: Generative AI foundational models and platforms market

a) Market overview

The foundational models and platforms market comprises two related areas. Foundational models are large-scale, pre-trained models that can be adapted to various tasks without the need for training from scratch, such as language processing, image recognition, and decision-making algorithms.

Generative AI platforms, in turn, refer to software that enables the management of generative AI-related activities outside of foundational models. Notably, IoT Analytics identified six platform types: 1) development, 2) data management/databases, 3) AI IaaS/GPU as-a-service, 4) middleware & integration, 5) MLOps, and 6) user interface and experience (UI/UX).

The foundational models and platforms market exploded with the public release of ChatGPT in late 2022, reaching $3.0 billion in 2023. This is substantial growth over 2022, which saw next to nil in terms of revenue. IoT Analytics’ analysis projects strong market growth in the coming years as enterprises invest billions in—and report real value from—generative AI implementations and continuous improvements.

b.) Leading generative AI foundational model and platform companies

Unsurprisingly, the foundational model and platform market are currently led by OpenAI, with several well-known technology companies trying to catch up.

1. OpenAI

With the November 2022 launch and subsequent success of ChatGPT, OpenAI leads in the share of the foundational model and platform vendors market with 39%. Since the release of ChatGPT, OpenAI’s generative pre-trained transformer (GPT) models went from GPT-3.5 to GPT-4 to GPT-4 Turbo, showcasing the continued development of the model. OpenAI’s models continue to impress in independent model assessments and rankings—often coming out in the top three of all tested models. Although many experts expect the foundational model space to become a commodity over time, at this point, OpenAI’s flagship models remain the top foundational model on the most common benchmarks.

According to IoT Analytics’ What CEOs Talked About series, in 2023, ChatGPT skyrocketed in boardroom discussions in Q1, but as other foundational models and generative AI applications became available, mentions of ChatGPT steadily declined as “generative AI” separated and continued to rise. (The What CEOs Talked About in Q4 2023 report and blog is expected to be released mid-December 2023.)

2. Microsoft

On OpenAI’s heels at 30% market share is Microsoft, its largest shareholder. Microsoft’s platform, Azure AI, offers Azure OpenAI, which uses OpenAI’s LLMs but goes beyond the public ChatGPT offering by promising greater data security and custom AI apps. This is suited for enterprises who want to secure their proprietary data when leveraging the benefits of generative AI since ChatGPT’s terms of use state that they can store and use content (both input and output) to improve their services. In November 2023, Microsoft reported over 20,000 active paying customers for its Azure AI platform, adding that 85% of Fortune 100 companies used it in the past year.

Despite Microsoft’s strong partnership with OpenAI, Microsoft also heavily promotes the usage of other models, such as Llama 2, via its platform, thereby enabling customers to freely choose and test different models and providers. Another key priority for Microsoft is integrating AI capabilities into its existing product portfolio, such as Azure, Microsoft/Office 365, and Bing.

3. AWS

AWS has an 8% share of this market. Its Bedrock service, publicly released in September 2023, provides access to models from several AI companies, such as Anthropic, AI21 labs, and Cohere (each with a 2% share of this market), and combines them with developer toolsets to help customers build and scale generative AI applications.

AWS has quickly claimed the third spot in this market because the company is the market leader in public cloud services and quickly got its existing customer base excited about its differentiated approach to Generative AI. In contrast to Google and Microsoft, AWS Bedrock focuses on providing a platform service that gives users access to a number of both general and domain-specific foundational models from a variety of vendors—providing choice, flexibility, and independence.

4. Google

In 2022, most experts credited Google as being the one tech company at the forefront of AI. Many experts interviewed by the IoT Analytics team continuously praised Google for its AI and its data products and innovations. In 2023, the picture is different, and Google is fighting to defend its position as an AI leader.

Vertex AI is Google Cloud’splatform focused on machine learning (ML) ops. It is integrated with other Google Cloud services, such as BigQuery and Dataproc, and offers a Jupyter-based environment for ML tasks. In early December 2023, Google released a preview version of its new multi-modal flagship model, Gemini. The related technical report states that the largest of the Gemini family outperformed other existing models in 30 out of 32 common ML benchmarks. Initially, the announcement of Gemini was widely received as positive, but a popular demo video released by Google later turned out to be staged.

Market segment 3: Generative AI services market

a) Market overview

The generative AI services market represents a specialized segment dedicated to consulting, integration, and implementation support for organizations aiming to integrate generative AI capabilities. With generative AI having risen as one of the top discussion points in boardrooms, services companies are sensing a large opportunity in helping companies formulate their generative AI strategies (e.g., what use cases to implement), advising them on technical architecture choices (e.g., which models to use) and helping them implement and build individual solutions.

IoT Analytics assesses that the generative AI services sector’s opportunity is now. Due to the novelty of generative AI, organizations often lack skills and experience, and the only option is to look for professional services firms that have or are in the process of building up the required expertise.

b) Leading generative AI services companies

The generative AI services market is more dispersed than the other two markets highlighted here.

1. Accenture

Accenture is estimated to have the largest generative AI services market share at 6%. The company announced in June 2023 that it is investing $3 billion in data and AI practice over three years to double its AI talent and develop new capabilities. Additionally, Accenture disclosed in its Q4 2023 earnings press release that its revenue for generative AI projects grew to $300 million for 2023.

In November 2023, Accenture announced plans to launch a network of generative AI studios in North America where companies can explore ways to integrate generative AI applications. These studies are expected to be at Accenture Innovation Hubs in Chicago, Houston, New York, San Francisco, Toronto, and Washington, DC.

2. IBM

US-based technology corporation IBM makes up 2% of this market. To position itself for the opportunities that generative AI brings, the company announced it had established a “Center of Excellence (CoE) for generative AI,” which as of May 2023, already had over 1,000 consultants specialized in generative AI. The CoE operates alongside IBM’s AI and Automation practice, which includes over 21,000 data and AI consultants.

3. Capgemini

France-based IT services company Capgemini also has a 2% share in this market, offering consulting services intended to help clients adopt key technologies such as the cloud and AI. In July 2023, Capgemini announced the launch of a portfolio of generative AI services, including in the following areas:

• Strategy
• Customer experience
• Software engineering
• Custom solutions for enterprise

One of Capgemini’s current customers is London Heathrow Airport which aims to improve traveler experiences through its “Generative AI for Customer Experience” offer. Heathrow’s Director of Marketing and Digital, Pete Burns, stated that the project is intended to “assist, empower and delight passengers” with tailored customer service solutions.

4. The many others

Past this point, the remaining 86% of the market becomes a cornucopia of specialized generative AI services providers and larger general consulting and system integration companies, each taking a bite of the rapidly growing segment.

As an example, in April 2023, UK-based professional services company PwC announced plans to invest $1 billion over three years to not only grow its AI offerings but also transform how it works by using generative AI. Additionally, in July 2023, global consultancy firm McKinsey & Company announced it partnered with AI startup Cohere to provide customized AI solutions to its enterprise clients.

Generative AI company landscape outlook

The enterprise generative AI market is roughly a year old, and already, the generative AI companies landscape appears vast.

IoT Analytics released its first generative AI report, the Generative AI Trend Report, in March 2023. Since then, more foundational models and platforms have emerged, e.g., OpenAI’s GPT4 Turbo, Google’s Gemini, or Microsoft’s Phi-2. At the same time, the demand for data center GPUs exploded, which is also mirrored in NVIDIA’s stock performance (+231% year-to-date as of 14 December 2023). Finally, consulting giants have made investments to position themselves in the generative AI services market, such as Accenture’s $3B investment in AI and its pledge to double “AI talent.”

As part of this research, we talked to 30+ experts in the field and gathered information on 270+ generative AI projects and analyzed which industries and departments are fastest to adopt and which vendors are most selected today.
The coming months will reveal how many of those projects will deliver value besides just being a marketing coup or how many of those currently in the proof-of-concept stage will move forward. Most companies are only now forging their generative AI strategies and considering whether to build foundational models from scratch based on industry-specific data, use an out-of-the-box propriety model, or fine-tune open-source models. All of this comes as generative AI companies release new products at unprecedented speed.

There is still a lot of movement in the generative AI company landscape, and there will be more in the foreseeable future. IoT Analytics will stay on top of this space, with a follow-up report expected in 2024.

The post The leading generative AI companies appeared first on IoT Business News.

IoT Analytics published an analysis based on the “Predictive Maintenance & Asset Performance Market Report 2023–2028” report and highlights 5 key insights related to the $5.5 billion predictive maintenance market.

Key insights:

• The global predictive maintenance market grew to $5.5 billion in 2022–a growth of 11% from 2021—with an estimated CAGR of 17% by 2028, according to the Predictive Maintenance and Asset Performance Market Report 2023–2028.
• With median unplanned downtime costs larger than $100,000 per hour, the importance of accurately predicting failures of large assets has never been higher.
• This article shares 5 key highlights of the predictive maintenance market: 1) The market is valued at $5.5 billion, 2) there are 3 different types of predictive maintenance, 3) predictive maintenance software tools share 6 features, 4) predictive maintenance is commonly being worked into the maintenance workflow, and 5) successful standalone solutions vendors specialize in an industry or asset.

Key quotes:

Knud Lasse Lueth, CEO at IoT Analytics, remarks: “Predictive Maintenance continues to be one of the leading use cases for Industry 4.0 and digital transformation, especially in process industries where asset failures can quickly go into the hundreds of thousands of dollars. It is great to see that the market is moving ahead with AI integration into existing APM and CMMS systems and that prediction accuracies are improving. Nonetheless, we still have a long way to go as false alerts remain commonplace.”

Fernando Brügge, Senior Analyst at IoT Analytics, adds that “Predictive maintenance is reaching new heights of maturity and sophistication thanks to the rapid advancements in artificial intelligence, hardware, and data engineering. We are at the point where these technologies enable us to collect, process, and analyze massive amounts of data from multiple sources, and use them to build more accurate and reliable models of machine health and behavior, as well as to determine potential courses of action to fix machine issues. In this way, predictive maintenance is not only a smart way to optimize equipment performance and lifecycle, but also a strategic way to enhance operational efficiency and competitiveness in a rapidly evolving industrial space.”

Predictive maintenance market: 5 highlights for 2024 and beyond

One accurately predicted failure of a large asset is worth more than $100,000 in many industries.

Our latest research highlights, among many other things, that the median unplanned downtime cost across 11 industries is approximately $125,000 per hour. With critical unplanned outages in facilities in industries such as oil and gas, chemicals, or metals occurring several times a year, an investment into predictive maintenance can amortize with the first correct prediction.

Unfortunately, there is a flip side: the accuracy of many predictive maintenance solutions is lower than 50%. This creates headaches for maintenance organizations that often run to an asset to find it is perfectly fine, eroding trust in the entire solution.

That said, vendors have been making strides to increase prediction accuracy, with more data sources and better analysis methods becoming available, including AI-driven analysis. There are positive signs that this determination for better prediction accuracy is helping end users: our research indicates that 95% of predictive maintenance adopters reported a positive ROI, with 27% of these reporting amortization in less than a year.

General search interest in predictive maintenance and related concepts has been on the rise for the last 12 years. Online searches for the term have grown nearly threefold since we initiated coverage on the topic in 2017 and have outgrown condition-based maintenance and asset performance management (APM) related searches.

Indeed, predictive maintenance appears to be well on track to be the must-have killer application we made it out to be in 2021.

In this fourth installment of our predictive maintenance market coverage, we look at 5 important highlights to note about the market going into 2024:

1. The predictive maintenance market is valued at $5.5 billion (2022)
2. There are 3 different types of predictive maintenance, with anomaly detection on the rise
3. Predictive maintenance software tools share 6 common features
4. Integration into the maintenance workflow is becoming important
5. Successful standalone solutions vendors specialize in an industry or asset

Highlight 1: The predictive maintenance market is valued at $5.5 billion

The predictive maintenance market reached $5.5 billion in 2022. Uncertain economic conditions and other manufacturing priorities in the last 2 years resulted in 11% market growth between 2021 and 2022. With companies reinvesting in efficiency, safety, and operational performance, we expect the market for predictive maintenance to grow to 17% per year until 2028.

Our research indicates that industries with heavy assets and high downtime costs are driving the adoption of predictive maintenance solutions (e.g., oil & gas, chemicals, mining & metals).

Highlight 2: There are 3 different types of predictive maintenance, with anomaly detection on the rise

As the market has evolved, 3 noticeable predictive maintenance types have developed:

1. Indirect failure prediction
2. Anomaly detection
3. Remaining useful life (RUL)

The difference between these largely comes down to the objectives, methods of data analysis, and type of output/information they provide. RUL is the hardest to achieve due to resource demands and environmental factors that make it difficult to scale. Indirect failure prediction has been the most used approach, but our research indicates that anomaly detection is on the rise.

1. Indirect failure prediction

The indirect failure prediction approach generally takes a machine health score approach based on a function of maintenance requirements, operating conditions, and running history. This approach often relies on general analysis to yield this score, though supervised machine learning methods can be used if a significant amount of data is available.

Benefits:

• Scalability – Indirect failure prediction can be more easily scaled since they rely on equipment manufacturers’ specifications that are more or less the same across machines of the same type.
• Cost effective – Indirect failure prediction can use existing sensors and data, reducing the need for additional instrumentation.

Limitations:

• Failure time-window accuracy – Indirect failure prediction does not give a timeline of when machines will fail. This can be a problem for organizations with very costly downtimes (e.g., heavy equipment industries).
• Dependent on historical data – Indirect failure prediction’s effectiveness relies on the availability of extensive historical data for accurate modeling.

2. Anomaly detection

Anomaly detection is the process of finding and identifying irregularities in the data (i.e., data points that deviate from the usual patterns or trends). While the indirect failure prediction and RUL approaches use failure data to predict future failures, anomaly detection uses the “normal” asset profile to detect deviations from the norm. These deviations can indicate potential problems, such as faults, errors, defects, or malfunctions, that need to be detected and addressed before they cause serious damage or downtime.
This approach makes it easier when there is not a good repository of failure data, and it often relies on unsupervised machine learning.

Benefits

• Low data and hardware requirements – Anomaly detection models can identify issues without being trained on failure data. Further, since these models need less data, they do not demand high computing power.
• High scalability and model transferability – Anomaly detection models are trained on normal operation data, so they can easily be applied to different machines without retraining or adaptation.

Limitations

• Failure time-window accuracy – As with indirect failure prediction, anomaly detection models do not give a timeline of when machines will fail, which can be a problem for organizations with very costly downtimes.
• Presence of false positives – While most solutions in the market can distinguish between critical and noncritical anomalies, the choice of unsupervised machine learning models is still important as it can affect how well this distinction can be made (e.g., autoencoders and generative adversarial networks do not capture the complexity of normal operations).

3. Remaining useful life (RUL)

RUL is the expected machine life or usage time remaining before the machine requires repair or replacement. Life or usage time is defined in terms of whatever quantity is used to measure system life (e.g., distance traveled, repetition cycles performed, or the time since the start of operation).

This approach relies on condition indicators extracted from sensor data—that is, as a system degrades in a predictable way, data from the sensors match the expected degradation values. A condition indicator can be any factor useful for distinguishing normal operations from faulty ones. These indicators are extracted from system data taken under known conditions to train a model that can diagnose or predict the condition of a system based on new data taken under unknown conditions.

Predictions from these RUL models are statistical estimates with associated uncertainty, resulting in a probability distribution.

Benefits

• Failure prediction time-window – RUL is especially useful for industries where maintenance is very costly and needs advanced planning, such as heavy-equipment industries.
• Output robustness – Since RUL estimates rely on high-quality and detailed data, they tend to be more robust and reliable.

Limitations

• Resource demand – Training large models requires powerful computing hardware, especially if done on-premises.
• Model transferability and scalability – Different environments and usage patterns can cause different failure modes for the same type of equipment. This means the model needs to be retrained for each specific case, reducing its scalability and generalizability.

Highlight 3: Predictive maintenance software tools have 6 common features

Software is the largest segment of the predictive maintenance tech stack, making up 44% of the predictive maintenance market in 2022.

Our report shows that even though most successful predictive maintenance software vendors specialize in industries or assets, there are 6 common features between their various solution software suites:

1. Data collection
2. Analytics and model development
3. Pre-trained models
4. Status visualization, alerting, and user feedback
5. Third-party integration
6. Prescriptive actions

We will delve further into these features and offer an example snapshot for each from various software vendors. The examples are to help readers understand some approaches to these common features.

Feature 1: Data collection

Data collection tools within predictive maintenance software collect, normalize, and store data on asset health/condition parameters. They also collect other data types needed to identify and predict upcoming issues, such as business and process data.

Snapshot:

US-based predictive maintenance software vendor Predictronics offers PDX DAQ, an application that allows users to synchronize data collection from multiple sources for any given period of time. The solution creates a database that harmonizes all the timestamps from different sensors, which Predictronics claims yields the necessary information for analysis and producing real-time, impactful results.

Feature 2: Analytics and model development

Analytics and model development tools within Predictive Maintenance software analyze, interpret, and communicate data patterns, including analytics discovery (e.g., RCA, AD modules) and modeling (e.g., feature engineering and model selection and testing).

Snapshot:

US-based predictive maintenance software vendor Falkonry (recently acquired by IFS) offers Workbench within its Time Series AI platform, a low-code ML-based solution aiming to help users—specifically, operational practitioners, including production, equipment, or manufacturing engineers—discover patterns such as early warning or stages of deterioration in complex physical systems. It also aims to enable users to analyze large amounts of data and build predictive models.

Feature 3: Pre-trained models

Pre-trained models are just that: ready-to-use models typically designed for specific assets in specific industries. These models include capabilities and references for specific assets or failure modes (e.g., fouling for heat exchangers, wear and corrosion for fans, or valve leakage for compressors). These are meant to help end users see examples of models so they can build on them or develop custom predictive maintenance algorithms.

Snapshot:

US-based asset management software vendor AspenTech (recently acquired by Emerson), offers Mtell, an application that includes pre-populated, industry-specific asset templates to help users select sensors for common asset categories and AI functionality to create and deploy models quickly for PdM applications (e.g., for specific compressors, turbines, and blowers).

Feature 4: Status visualization, alerting, and user feedback

Status visualization, alerting, and user feedback tools within predictive maintenance software automatically communicate asset-related data/insights for various personas. These insights often include status dashboards and automatic alerts that trigger work orders or corrective actions, maintenance planning, and optimization. These tools also enable users to provide feedback concerning the accuracy of alerts.

Snapshot:

US-based analytics software vendor SAS Institute offersAsset Performance Analytics, which includes status dashboards and automatic alerts intended to notify operations staff and managers of impending failure so that organizations have time to identify and fix issues before they become costly problems.

Feature 5: Third-party integration

Third-party integration enables users to connect their predictive maintenance software to other software systems and workflow management tools, such as ERP, MES, CMMS, APM (more on APM integration in Highlight 4), and Field Service.

Snapshot:

SKF, a Swedish bearing and seal manufacturing company also offering maintenance products, offers a condition monitoring and predictive maintenance solution that interfaces with existing plant control systems (e.g., MES or SCADA) and other external dashboards (e.g., ERP). It also provides insights to operators in the field via alarms and visualization on handheld devices.

Feature 6: Prescriptive actions

Prescriptive action features typically suggest the optimal actions to take in case of an (upcoming) failure. These actions are typically prioritized by criteria that are set when the algorithm is designed.

The actions that are prescribed by the software vary depending on the nature and urgency of the issue. They may require multiple steps or interventions. For instance, some actions may involve automatically adjusting the equipment parameters or informing the maintenance and operation teams about the necessary procedures to ensure equipment efficiency.

Snapshot:

Marathon, a predictive maintenance software solution from Norway-based Arundo, provides a feature known as Investigations that aims to provide the workflow and instructions to resolve equipment problems according to prescribed corporate standards.

Highlight 4: Integration into the maintenance workflow is becoming important

In its early days, predictive maintenance was mostly a standalone solution developed by startups to address specific customer needs. However, our report highlights a notable trend of sophisticated predictive maintenance solutions integrating into larger APM and computerized maintenance (CMMS) solutions.

APM is a strategic equipment management approach designed to help optimize the performance and maintenance efficiency of individual assets and entire plants or fleets. APM aims to improve asset efficiency, availability, reliability, maintainability, and overall life cycle value.

Various APM vendors are introducing predictive maintenance software tools within their APM offerings. The solutions aim to tie the different capabilities into 1 thread:

• Knowing when a machine will fail and mapping how failures could affect production or output
• Estimating how much fixing or preventing an issue will cost
• Making recommendations on whether it is worth fixing or preventing a problem

By including a sophisticated predictive maintenance solution in an end-to-end asset flow, APM players are trying to become the main partners for their customers’ digitalization journeys.

Our report lists 9 key components of APM:

1. Asset health monitoring
2. Maintenance optimization
3. Reliability analysis
4. Integrity management
5. Performance optimization
6. Failure prediction <- Predictive maintenance resides here 7. Digital asset twin 8. Sustainability management 9. Energy optimization

We assess in our report that improving the failure prediction module of APM solutions is currently one of the key initiatives of leading APM vendors.

Highlight 5: Successful standalone solutions vendors specialize in an industry or asset

Our research found that 30% of predictive maintenance vendors offer standalone, industry- or asset-specific solutions. By tailoring their efforts to specific niches in which they have acquired domain knowledge, they can discern the types of equipment and industries in which their solutions offer the most end-user benefits.

Snapshot:

Israel-based data science company ShiraTech Knowtion uses its equipment expertise in its offering of Predicto, an industrial IoT platform focused on industrial maintenance teams. The platform enables reading and processing of sensor data from production plants, ideally based on its own multisensing devices (iCOMOX). The company has developed specific offerings for motors, pumps, conveyors, and pipes. These asset-tailored offerings enable the company to scale.

6 considerations for predictive maintenance vendors

Six questions that predictive maintenance vendors should ask themselves based on insights in this article:

1. Market growth and strategy: Given the market’s growth to $5.5 billion and the projected increase to $14.3 billion by 2028, how can our company align its strategy to capitalize on this market expansion?
2. Accuracy improvement: Considering the current lower-than-50% accuracy of many predictive maintenance solutions, what innovative approaches or technologies can we adopt to enhance the accuracy of our predictions?
3. ROI communication: How can we better communicate the positive ROI of predictive maintenance to potential customers, especially those who are skeptical due to past experiences with inaccurate solutions?
4. Industry specialization: Given that the most successful vendors are specialized in specific industries, assets, or use cases, should we consider narrowing our focus, and if so, in which areas?
5. Data collection and integration: Are we effectively collecting the right kinds of data (including business and process data) and integrating it into the right IT systems for optimal predictive maintenance?
6. Software tool features: Do our software tools encompass the 6 common features identified in the report (data collection, analytics and model development, pre-trained models, status visualization, third-party integration, prescriptive actions), and are they competitive in the current market?

8 considerations for those looking to adopt or update predictive maintenance solutions

Eight questions that those looking to adopt or update predictive maintenance solutions should ask themselves based on insights in this article:

1. Solution type suitability: Which type of predictive maintenance solution (indirect failure prediction, anomaly detection, or RUL) best aligns with our specific maintenance needs and operational goals?
2. Integration with existing systems: How easily can predictive maintenance solutions integrate into our existing maintenance workflows and asset management systems?
3. Vendor specialization: Should we look for a vendor specialized in our industry, specific assets, or use cases, and how would that benefit us over a generalist provider?
4. Data collection and analysis: Do we have the necessary infrastructure for effective data collection and analysis to support a predictive maintenance system?
5. Accuracy and trustworthiness: How can we evaluate and ensure the accuracy of the predictive maintenance solution to build trust within our maintenance team?
6. Scalability and future growth: How scalable are the predictive maintenance solutions, and can they accommodate our future growth?
7. Software features and functionality: Do the software tools offered by vendors have all the key features we need, such as data collection, analytics, and third-party integration?
8. Market trends and innovation: Given the evolving nature of the predictive maintenance market, how can we stay informed about the latest innovations and ensure that our solution remains cutting-edge?

The post Predictive maintenance market: 5 highlights for 2024 and beyond appeared first on IoT Business News.

IoT Analytics released a new analysis, based on the ’Industrial IoT & Industry 4.0 Case Study Report 2023’.

Key insights:

• Digitalization has become essential for industrial companies worldwide, as IoT Analytics expects the industrial IoT market to reach $145 billion in 2023.
• The Industrial IoT and Industry 4.0 Case Studies Report 2023 delves into 22 case studies, exploring their project objectives, technologies deployed, lessons learned, challenges, and outcomes.
• In this article, we share five learnings from the report: 1) Upgrading the ERP is often the first step in digital transformation, 2) cloud-native data storage and streaming are coming up, 3) first successful implementations of private 5G use cases, 4) digitalization becoming a prerequisite to achieving sustainability, and 5) the continued journey toward predictive maintenance.

Key quotes:

Rajini Nair, Analyst at IoT Analytics, remarks: “Upon analyzing the case studies outlined in the report, it becomes evident that digitalization is a key catalyst driving technological progress in industrial settings. This includes the enhancement of ERP systems and the migration of data to cloud platforms equipped with real-time streaming capabilities. Furthermore, digitalization proves essential in harmonizing companies with their sustainability objectives. Strategies such as the implementation of predictive maintenance algorithms and the adoption of private industrial 5G use cases are leveraged to improve operational efficiency. Looking forward, the technological landscape is transforming with the rise of AI, poised to shape the future of manufacturing.”

Digitalization has become crucial to manufacturers globally

Digitalization has become crucial for manufacturers in their respective competitive landscapes. IoT Analytics estimates the industrial IoT market to reach $145B in 2023, with a CAGR of 17.9% until 2030, as more and more companies undertake digital transformation initiatives.

For many, digitalization has already become a game changer:

• Carmaker Mercedes has achieved 25% greater efficiency in its S-class assembly after optimizing the value chain and introducing innovative technologies at its Germany-based Factory 56 facility.
• Energy giant TotalEnergies aims to generate $1.5 billion annually in savings with its digital solutions by 2025.
• Chemical company Covestro increased efficiency and reduced unnecessary downtime by shifting from calendar-based to condition-based maintenance.

These are just some of the benefits of the digital transformation initiatives our research uncovered as part of the 255-page Industrial IoT and Industry 4.0 Case Studies Report 2023. The report delves into 22 recent industrial digital transformation case studies, looking at initiatives related to digital transformation, data architecture, predictive maintenance, AI, and industrial 5G.

Benefits of case studies for digitalization journeys

Case studies by peers or companies in other industries are a great way to learn about digitalization, identify common challenges, develop a view of best practices, and understand how companies manage to scale.

The 22 case studies in our report offer readers a diverse set of manufacturing examples of current IIoT and Industry 4.0 projects, along with project objectives and takeaways from each. Our analysis of these takeaways yielded many trends in these companies’ digital transformation journeys, five of which we will delve into in this article (including selected highlights from the report):

1. ERP: An upgraded ERP is often the first step to digital transformation.
2. Cloud: Cloud-native data storage and streaming are increasingly accepted.
3. 5G: First manufacturers have successfully implemented private 5G use cases.
4. Sustainability: Digitalization is becoming a prerequisite to achieving sustainability objectives.
5. Maintenance: The journey toward predictive maintenance and remote monitoring continues.

Learning 1: An upgraded ERP is often the first step to digital transformation

Our analysis found that many manufacturers elect to prioritize upgrading their ERP systems to ensure their various data sources are connected before prioritizing other digital transformation initiatives. Since ERP systems are often the central nervous system of a business, prioritizing an updated ERP allows different departments to share and operate on the same data, reducing errors and improving efficiency.

Selected highlight: Celanese

In recent years, US-based chemical manufacturer Celanese has acquired several businesses or divisions from other companies. Celanese had been operating on a legacy SAP ERP system, and the acquired assets had different legacy ERP environments, making cross-section integration difficult. Celanese’s global CIO, Sameer Purao, did not want the company to invest in integrating the new acquisitions into older technology. Given this situation and Celanese’s adoption of a strategic, long-term approach to a scalable digital transformation plan, an ERP upgrade became necessary.

“Our previous ERP system had been a backbone, but it was close to 20 years old. Given its age, we didn’t want to invest in transforming until we upgraded that piece first. The acquisitions underscored that it wouldn’t make sense to invest in integrating them into older technology, so we opted to upgrade.” – Sameer Purao, senior vice president and global CIO, Celanese Corporation

In May 2023, Celanese announced that it had completed its upgrade to SAP S/4HANA. Further, since Celanese acquired DuPont’s Mobility & Materials (M&M) business just six months prior, it quickly cutover to upgrading M&M’s legacy ERP system as well, which is expected to be completed in the first half of 2024.

While there are other major aspects of Celanese’s digital transformation journey detailed in our report, this upgrade to its ERP provided a stronger backbone from which other digitalization solutions could be built. Another benefit of this upgrade is improved visibility and collaboration, enhancing transparency and teamwork and allowing for efficient data access across the enterprise.

Learning 2: Cloud-native data storage and streaming are increasingly accepted

The cloud market nearly doubled between 2020 and 2022, growing from $109 billion to $206 billion, based on our analysis of global cloud projects. While the COVID-19 pandemic certainly played a major role, it was not the only growth factor. Our analysis found that large-scale enterprise digitalization efforts and strong SaaS adoption also helped fuel this growth.

Cloud storage and data streaming allow companies to centralize and share their data with a smaller footprint than running their own on-premises servers, which comes with footprint and maintenance costs. Moving these services to the cloud also allows companies to scale without the need for significant capital investment in physical hardware.

Selected highlight: Michelin

In 2019, tire manufacturer Michelin started using Apache’s Kafka event streaming platform on-premises in its data centers to gain real-time insights and process data as continuous streams. However, as its operational footprint expanded, so did the resources it had to dedicate to maintaining the solution. By Q4 2019, Michelin’s IT department initiated its migration to the cloud, with Microsoft Azure as the cloud partner.

“One of the challenges with [streaming technology] Kafka was its operational complexity, especially as the footprint expanded across our organization. It’s a complex, distributed system, so we had to allocate a lot of our valuable technical resources and expertise to babysit it and keep it running.” – – Olivier Jauze, now CTO of Experiences Business Line, Michelin

By 2021, Michelin migrated its services to Confluent Cloud for Azure, a Kafka-based platform, to support its multi-cloud environment. Soon after, the company began exploring use case projects and has since migrated one of its most critical projects, online order management, to the cloud—replacing its on-premises orchestrator. By 2023, Michelin expanded its cloud-based event streaming architecture into several departments, including supply chain management, customer services, manufacturing, and R&D.

Through its adoption of cloud-native data storage and streaming, Michelin achieved the following benefits (among other things):

• Cost savings: Estimated 35% in cost savings in the cloud compared to on-premises operations
• Improved uptime: 99.99% uptime

Learning 3: First manufacturers have successfully implemented private 5G use cases

As 5G continues its public rollout globally, some manufacturers have successfully deployed private 5G networks to enable new use cases within their facilities. While faster speeds and lower latency may seem like key adoption drivers, our analysis found that improved reliability over Wi-Fi, enhanced cybersecurity, and the ability to access data locally are the core motivating factors.

Our analysis also found that during the public rollout of 5G, some companies did not simply dive into integrating 5G-specific technology. Instead, many integrated robust LTE solutions that were upgradable to 5G with relative ease (or so-called 4.9G solutions) once the technology evolved or became approved for industrial use.

Selected highlight: Airbus

To increase aircraft production and validation efficiency, European multinational aerospace corporation Airbus partnered with Ericsson, a Swedish multinational telecommunications company, in 2021 to implement private industrial 5G networks at 11 aircraft assembly manufacturing sites in Europe. The approach began with implementing 4G networks that either already had 5G capabilities or could seamlessly upgrade to 5G.

However, Airbus is not limiting this deployment to its European facilities. During a Q&A at the 5G Manufacturing Forum in November 2022, Hakim Achouri, the 5G and IoT solutions expert for digital aviation at Airbus, noted, “Airbus is going way beyond 11 networks at 11 sites, expanding beyond its core European manufacturing bases in France and Germany, to also deploy private 5G in Canada, China, Spain, the UK, and the US.”

With its implementation of private 5G networks at its production and assembly facilities, Airbus has realized the following benefits:

• Ability to implement advanced use cases: This includes site surveillance, efficient flight-to-ground data offloads, quality inspections, and the operation of automated guided vehicles (AGVs).
• Enhanced user experience: With increased speed, bandwidth, and reliability, employees at the production sites have access to more data, making operations smoother, more efficient, and more secure.
• Scalability through reusability: By developing a pattern in its strategy, Airbus was able to roll out private 4G/5G networks across its many sites with consistent quality and performance.

Learning 4: Digitalization is becoming a prerequisite to achieving sustainability objectives

We recently noted a trend of companies deploying digital twins to help realize their sustainability goals. But it is not simply digital twins assisting companies on this front—digitalization projects overall are helping companies monitor energy consumption, optimize resource usage, and reduce their environmental footprint in the manufacturing process.
Backing this awareness and trend toward sustainability are data points from our latest What CEOs Talked About report, where “sustainability” and related terms remained among the most discussed topics in boardrooms.

Selected highlight: TotalEnergies

French multinational energy and petroleum company TotalEnergies has publicly declared its ambition to achieve carbon neutrality by 2050. To meet this goal, the energy company has leveraged digital solutions to advance the implementation of sustainability measures on its offshore platforms.

For instance, TotalEnergies retrofitted their pipes with LoRaWAN-connected temperature sensors to detect gas leaks along their flare networks. As hydrocarbons are released, the temperature of the pipes significantly changes. When this change is detected, operators are alerted via emails for immediate action. This not only helps limit the release of hydrocarbons but also saves TotalEnergies money by reducing the loss of product.

Learning 5: The journey toward predictive maintenance and remote monitoring continues

According to our Predictive Maintenance and Asset Performance Market Report 2023–2028 (published in November 2023), the predictive maintenance market reached $5.5 billion in 2022. While the report notes several tailwinds supporting this interest and market growth, such as skill shortages and interest in reducing energy usage and CO2 emissions, costs are a major driver, as noted in our case studies report as well.

Equipment failure, especially during core operational hours, reduces productivity and adds repair expenses. To avoid these costs, companies often use preventative maintenance procedures, such as time-based inspections and repairs or condition criteria from sensors or physical measurements to trigger preventative intervention. However, intervening based on time can be inefficient since the equipment may not be in need of repair at that time, and data collection/monitoring requires personnel to conduct these tasks.

By implementing digital solutions, companies can remotely monitor the condition of critical equipment and establish conditions in which intervention is actually needed well before failure occurs.

Selected highlight: Battalion Oil Corp

US-based Battalion Oil Corp partnered with Novity, a US-based predictive maintenance solutions company, to pilot a predictive maintenance solution to detect valve leaks within their compressors and reduce unexpected compressor downtime. Initially, Battalion would sporadically measure valve cap temperatures using handheld devices to identify potential gradual leaks that could lead to a failure. While the checks were intended to be conducted daily, varying daily maintenance tasks and priorities often disrupted these important checks.

“Predictive automation is a game-changer for the oil and gas industry. By analyzing data in real-time and making accurate predictions about future events, drilling companies can optimize their operations to maximize efficiency, reduce costs, and improve safety. This technology has the potential to transform the way we do business and stay competitive in today’s market.” – John Smith, CEO of Oil and Gas Exploration Company

An initial step in the solution was to use a crank angle sensor and pressure transducers. However, physical crank angle sensors are usually the most difficult and expensive sensors to install, so the engineers developed a virtual crank angle sensor based on physics-based and data-driven methods using data from the pressure sensors.

After validating that the rotational position calculated by the virtual sensors matched the position provided by the physical sensors, engineers applied prognostic methods to the data from the virtual crank angle sensor and physical pressure sensors. The result was predicted gradual valve failures several weeks in advance—five to seven days on average before temperature checks indicated a gradual leak.

The digital transformation journey carries on

The Industrial IoT and Industry 4.0 Case Studies Report 2023 delves further into the above-mentioned and 18 other case studies of ongoing digital transformation projections. While these companies and many others are advancing in their digital transformation journeys, there is still a long road ahead for many companies, some of which still rely on analog, pen-and-paper methods in their facilities. Even still, many companies are already experiencing real value, e.g., Mercedes’ achieving 25% greater efficiency and Battalion observing signs of gradual valve failures several weeks in advance.

Digitalization has become more than a nice-to-have for manufacturers today—it has become crucial for them in their respective competitive landscapes. The market reflects this assessment: according to our enterprise IoT market dashboard, the IIoT market size in 2023 is approximately $145 billion, with a forecasted CAGR of 17.9% between 2023 and 2030.

Looking ahead, AI continues to become a major theme in companies’ digital transformation initiatives. According to our continual series What CEOs Talked About, the topic and its related terms have already been of high and growing interest in boardrooms throughout 2023. We see a plethora of generative AI projects across the board, even in the industrial space (which we will report on soon). We will continue to monitor this space and highlight interesting case studies from adopters.

The post Industry 4.0 check-in: 5 learnings from ongoing digital transformation initiatives appeared first on IoT Business News.

A new report from IoT Analytics highlights eight notable trends helping to advance and promote digital twins.

Four of these trends are discussed in detail in this article. These trends are shaping the future of the digital twin market and influencing investment priorities for companies across various industries.

Key insights:

• According to our Digital Twin Market Report 2023–2027, the digital twin market is expanding, with a projected CAGR of 30% between 2023 and 2027.
• 29% of global manufacturing companies have either fully or partially implemented their digital twin strategies. Further, job posts related to digital twins have increased by 11% compared to October 2021, while openings for other tech topics have declined in the same timeframe.
• The report notes eight notable trends helping to advance and promote digital twins, four of which are discussed in this article.

Digital twin market snapshot

Data from our Digital Twin Market Report 2023–2027 indicates that 29% of global manufacturing companies have either fully or partially implemented their digital twin strategies, marking a noticeable increase from 20% in 2020. Moreover, the proportion of these companies not contemplating the implementation of digital twins appears to have reduced to 9% in 2023, down from 33.6% in 2020.

Supporting this trend, an analysis of job postings on SimplyHired suggests a growing demand for digital twin expertise. Postings mentioning “digital twin” increased by 11% in October 2023 compared to just two years prior, while openings for most other tech topics declined in the same timeframe. Notably, among the 60 tech-related skill sets we tracked, digital twin-related skills experienced one of the most significant growths.

Based on these observations and additional insights from our report, our current projection estimates that the global digital twin market could grow at a CAGR of approximately 30% between 2023 and 2027.

Against the backdrop of this growing market, the report notes eight trends that help promote the advancement and adoption of digital twins. Here, we will focus on four:

1. Digital twins deployed to meet sustainability goals
2. Digital twins employed as virtual sensors in complex conditions
3. Partnerships between cloud hyperscalers and OT and simulation specialists
4. Initiatives promoting interoperability of digital twins across multifaceted systems

Before we dive into these trends, and to provide context, it is helpful to understand how IoT Analytics defines digital twins and the digital twin market.

Defining digital twins and the digital twin market

In our March 2023 Decoding Digital Twins article, we define digital twins as a virtual model replicating the behavior of an existing or a potential real-world asset, system, or multiple systems. This definition captures a macro concept of digital twins, but our report and previous article present a three-dimensional, cuboid model to help classify digital twins so apple-to-apple comparisons can be made. Each axis of the cuboid represents one dimension of a digital twin:

1. Life cycle phase: The X-axis represents the six life cycle phases a digital twin is used for, from design to decommissioning.
2. Hierarchical levels: The Y-axis represents a digital twin’s five hierarchical levels, from information to multi-system.
3. Use/purpose of implementation: The Z-axis represents the seven most common uses for digital twins, such as simulation and prediction.

Based on this model, there are 210 potential combinations (5 x 6 x 7 = 210); however, our research indicates that many digital twin initiatives are tailored to multiple combinations.

In terms of the digital twin market, our market model only considers software spending for digital twins, which we break into two scopes:

• Broad digital twin market – includes the revenue for all software solutions that provide capabilities that are used for digital twins, such as solutions that integrate data sources into a digital twin and are capable of simulation, visualization, and predictions
• Narrow digital twin market – only considers spending for digital twin-specific software, such as software intended to model the digital twin data

Though hardware and services related to digital twins can bolster the capabilities of digital twin software, we only view them as supporting services for the software, and we do not consider them in our digital twin market model. That said, this ability to bolster capabilities means they can aid digital twin market growth, as shown in some of the trends below.

Digital twin market trends

We will now look at four trends helping digital twin market growth.

Trend 1: Digital twins deployed to meet sustainability goals

Sustainability was discussed in approximately 21% of recent CEO earnings calls and has remained a consistent topic throughout 2023. This pairs with our report’s analysis that the pursuit of sustainability goals is a tailwind macro factor for the digital twin market.

To achieve their sustainability goals, many companies are exploring digital twins. Due to their ability to simulate real-world conditions and deliver real-time information, organizations can optimize resource usage, reducing carbon emissions and improving supply and transportation networks.

According to Capgemini Research Institute’s 2022 digital twins report, 57% of organizations agreed that one of the key drivers for their digital twin investments was improving their sustainability, and 51% agreed that digital twins would help achieve their organization’s environmental sustainability goals.

In our report, a former VP at an industrial automation vendor shared, “Digital solutions provide the visibility, analysis, and insight needed to address the challenges inherent in sustainability goals. A digital twin strategy as part of an overall digitalization plan can be a crucial capability for asset-intensive industries and needs to encompass the entire asset lifecycle, process, and value chain from design and operations through maintenance and strategic business planning.”

Example: Aden, a Chinese integrated facility service provider, created a digital twin for one of its commercial centers in Chengdu, China. The digital twin was designed to help facility managers inspect, maintain, and repair building assets. 3D simulations assist facility managers in visualizing, predicting, and optimizing energy consumption, and the expected benefits include lower annual energy consumption, water usage, and waste.

Trend 2: Digital twins employed as virtual sensors in complex conditions

Virtual sensors approximate data that otherwise cannot be obtained via physical sensors, often due to physical sensors being impractical, costly, or hazardous to employ. Companies are now building digital twins to model hardware and calculate data based on other conditions. This not only allows the collection of data from complex equipment but also enables operators to track equipment performance and predict maintenance and downtimes.

Example: In large motor applications, such as room-sized motors that pump high volumes of gas, oil, or other chemicals, operators need to monitor the motors’ temperatures—especially if the motors are high-powered and repeatedly started. If a motor is too hot during a restart, the components could cause serious damage. Unfortunately, using a direct, physical sensor within a motor is often impractical, and operators must work from an assumptive time it takes for the motor to cool (with an additional safety buffer time). This means motors can be down longer than necessary, impacting efficiency and revenue.

To address this issue, Siemens developed a prototype virtual sensor based on a digital twin. It offers a simulation of how a physical sensor would operate if it were possible to install it within a motor. Using AR headsets, operators can see a simulation of the motor and its interior with a demonstrator superimposed over it, and they can see the motor’s temperature.

Trend 3: Partnerships forged in the clouds: Hyperscalers team up with OT and simulation specialists

In the last few years, cloud hyperscalers like AWS and Microsoft Azure have introduced digital twin platforms, e.g., AWS IoT TwinMaker and Azure Digital Twins, that allow for interconnecting various data sources and building digital twin topology. However, these companies realize they cannot deliver end-to-end digital twin solutions by themselves and are thus partnering with OT and simulation companies to add capabilities to their networks.

Hyperscalers and OT companies

OT companies provide industrial data management capabilities and connections to millions of local physical assets. By partnering with hyperscalers, OT companies can reach broader audiences looking for digital transformation solutions by offering typical cloud benefits like storage and computation power.

Example: In 2021, Siemens and AWS announced an expansion of their partnership, with digital twin technology being an area of focus. The companies aimed to accelerate Siemens Xcelerator adoption and democratize new digital twin solutions using AWS IoT TwinMaker, a service intended to make creating digital twins that incorporate multiple data sources faster and easier.

Hyperscalers and simulation companies

Simulation companies bring specialized expertise in creating accurate, high-fidelity models of physical entities, be it machinery, buildings, or entire ecosystems. By partnering with a hyperscaler, simulation companies can harness these cloud services’ data storage and computational power to create more robust, responsive, and accurate data twins that can be scaled and integrated seamlessly into broader IT ecosystems.

Example: In 2023, Ansys and Microsoft announced a partnership to help customers envision digital twins on a large scale. In cooperation with Tata Consultancy Services, Ansys and Microsoft integrated Ansys’s Twin Builder’s physics-based simulation capabilities with Azure Digital Twin and IoT data to allow Twin Builder users to run scenarios and obtain predictions on how their systems will behave.

Trend 4: Initiatives promoting interoperability of digital twins across systems from different vendors

Agreement on integration standards among the various digital twin technology providers is crucial for building cross-system digital twins. With standards, manufacturers can offer services that can be applied to unique situations with other digital twin technology and software.

Recognizing this, countries and industry organizations have taken several steps to address this need:

Plattform Industrie 4.0 and CESMII

Plattform Industrie 4.0 and the Clean Energy Smart Manufacturing Innovation Institute (CESMII) partnered to establish standards for manufacturers in Germany and the United States to better enable smart, sustainable competition. The partnership addressed similar challenges related to Industry 4.0 and Smart Manufacturing.

DTC digital twin interoperability framework

The Digital Twin Consortium (DTC), a collaborative partnership of industry, academia, and government experts, released the Digital Twin System Interoperability Framework to “unify a nascent ecosystem of high-value, multi-vendor services that can seamlessly ‘plug into’ a multi-dimensional, interoperable system of systems.”

DTC and IDTA collaboration

DTC and the Industrial Digital Twin Association (IDTA) announced a liaison agreement to collaborate on standardization requirements, enabling interoperability through discussions, aligning work in horizontal domains, and collaborating on open-source projects, contributions, and reference implementations.

DTC and OPC Foundation collaboration

DTC and the OPC Foundation announced a liaison agreement to “accelerate the development and adoption of digital twin-enabling technologies,” promoting interoperability standards and processes to advance the use of digital twins in manufacturing across multiple industries.

Considerations for digital twin vendors

3 questions digital twin vendors should ask themselves based on research findings discussed in this article:

1. Sustainability goals: Given the emphasis on sustainability and the role of digital twins in achieving it, is my company’s digital twin solution well-equipped to support sustainability objectives? Are there new features we need to develop?
2. Interoperability: Is our digital twin solution currently designed to be interoperable with other systems and technologies, especially those from different vendors?
3. Product development: How aligned is our product development roadmap with the emerging trends highlighted in the report, especially around end-user and technological advancements?

Considerations for adopters

3 questions adopters should ask themselves based on research findings discussed in this article:

1. Infrastructure readiness: Do we have the necessary infrastructure and resources in place to support the deployment and effective use of digital twins? If not, what investments are required?
2. Data integration: How compatible are our current data sources and systems with digital twin technologies, especially in terms of sensor data (both physical and virtual/soft)?
3. Interoperability concerns: As we use multiple software solutions across our operations, how important is interoperability between digital twin technologies and our existing systems?

The post Digital twin market: Analyzing growth and 4 emerging trends appeared first on IoT Business News.

IoT Analytics, a leading provider of market insights and strategic business intelligence for the Internet of Things (IoT), AI, Cloud, Edge, and Industry 4.0, today released the results of the quarterly company earnings call analysis.

This analysis is based on a comprehensive dataset of Q3 2023 earnings calls from 4,000+ leading US-listed firms. The findings from Q3 2023 show that three pivotal themes are currently trending in CEO discussions: 1. AI and Generative AI, 2. AI chips, and 3. sustainability. These influential topics have captivated boardrooms worldwide and are shaping the future investment priorities for companies across various industries.

KEY INSIGHTS:

• According to the latest “What CEOs talked about” report, three themes gained noticeable traction in earnings calls in Q3 2023: 1) AI and most of its related application topics, 2) AI chips, and 3) sustainability.
• ChatGPT is losing traction as the AI keyword of choice, and economic worries and uncertainty appear to be easing.

KEY QUOTES:

• Knud Lasse Lueth, CEO at IoT Analytics, comments: “I’m encouraged to see that as concerns of a potential recession fade, the emphasis on sustainability remains robust. AI, particularly generative AI, is emerging as the dominant theme of 2023. It’s evident that generative AI isn’t just another passing trend like blockchain or the metaverse. CEOs must take decisive action now to be at the forefront of this technological revolution.”
• Philipp Wegner, Principal Analyst at IoT Analytics, adds that “The surge in discussions around AI strategy and AI chips in Q3 2023 is a clear indicator that businesses are moving beyond the ‘what’ and ‘why’ of AI to the ‘how.’ CEOs are now grappling with the logistical challenges of integrating AI into their existing infrastructures, and that’s where the real transformation begins.”

The big picture

In Q3 2023, topics related to economic worries remained prominent in boardroom discussions globally but continued to decline quarter-over-quarter (QoQ). Mentions of the most talked about topic, inflation, dropped 5% QoQ to 47% of calls. Supply chain worries saw the smallest drop, 2% QoQ, while recession experienced the largest drop of 38% QoQ, now appearing in 11% of earnings calls.

Key quote on the macro environment: “Our base case today assumes a mild recession.” – Mark Mason, CFO, Citigroup, July 14, 2023

Key rising themes in Q3

AI : In Q3 2023,the broader topic of AI rose fairly steeply to 29% (+37% QoQ), and its subfield generative AI continued to rise in importance to 10% (+56% QoQ). During their quarterly earnings calls, CEOs appeared to be separating AI and many of its subfield topics from discussions about ChatGPT, which declined this QoQ (as discussed below in “Declining themes”).

Our analysis also shows a marked incline in the mentions of AI strategy and AI infrastructure, rising 128% and 103% QoQ, respectively.

Key CEO quote on generative AI: “Generative AI is at the forefront of customer conversations. However, enterprises are also realizing that they cannot have an AI strategy without a data strategy to base it on.” – Frank Slootman – CEO, Snowflake, August 23, 2023

AI chips : Mentions of GPUs greatly outpaced mentions of CPUs, with the former climbing 102% QoQ to 2.8% in Q3 2023 earnings calls and the latter climbing 47% QoQ to 1.7%. Coinciding with this trend is GPU chipmaker Nvidia climbing 146% in mentions to 1.9% compared to Intel only climbing to 1.2% (+48% QoQ) and AMD to 0.8% (+11% QoQ) in reference to AI chips.

“We’ll actually take the Nvidia hardware as fast as Nvidia will deliver it to us. Tremendous, tremendous respect for Jensen and Nvidia. They’ve done an incredible job. And frankly, I don’t know if they could deliver us enough GPUs.” – Elon Musk – CEO, Tesla, July 19, 2023

Sustainability, energy transition, and renewable energy : Mentions of sustainability, energy transition,and renewable energy slightly rebounded to 21.4% (+9.2% QoQ), 5.3% (+15.4% QoQ), and 5.2% (+10.9% QoQ), respectively. These topics are lower than their peaks in Q1 2022; however, since Q3 2022, each topic has remained generally consistent in its percentage of earnings call mentions.

“We don’t talk a lot about grid … but increasingly here in the U.S., people appreciate how critical grid modernization will be to the energy transition.” – Larry Culp – CEO, General Electric, August 28, 2023

Declining themes in Q3

ChatGPT: As mentioned, ChatGPT experienced a decline in its number of mentions in the earnings reports, dropping 34% QoQ to 2.5%. Last quarter, we saw a transition from CEOs specifically discussing ChatGPT to them discussing enterprise-wide applications of generative AI. That transition still appears to be occurring, as the other AI topics saw significant rises in mentions:

• LLM rose 98% QoQ to approximately 2%.
• Computer vision rose 60% QoQ to 1%.
• Chatbot rose 58% to 1%.

Remote work: The topic of remote work dropped the most of the key topics we tracked, falling 48% QoQ to 0.5% of earnings calls. This decline comes amid new concerns of a COVID-19 infection surge due to a newly detected SARS-CoV-2 variant. Early studies show that antibodies from vaccinations and past infections may enable immune systems to detect and combat the variant sufficiently, which could be easing boardroom concerns of a significant surge (of note, mentions of Corona dropped 8% QoQ to 0.9% of earnings calls).

This decline in discussions around remote work also comes amid increasing so-called return-to-office mandates, with 90% of US companies expected to require employees to work in person at least a few days a week by the end of 2023.

Deep-Dives

#1 AI

In the first quarter of this year, ChatGPT was the hot new (AI) topic for CEOs. In Q2, generative AI shared the stage with ChatGPT as AI proponents discussed other generative LLMs. Now, in Q3, ChatGPT is no longer the hot topic, but rather, generative AI, AI strategy, AI infrastructure, and AI Chips—with companies realizing that ChatGPT is just one tool of many in the new AI portfolio. However, AI is an evolving topic, and OpenAI continues to conduct research and development into ChatGPT, so there is no reason to suspect ChatGPT will completely fade from discussions in the near term.

AI use cases like coding and chatbots are starting to climb

AI use cases like coding and chatbots are also starting to climb, but they have not yet reached the same level as the aforementioned topics. These use cases will likely roll out in the next 6–12 months, so we assess these (and other) topics to grow in Q4 and into 2024.

Of the AI umbrella (not counting AI chips, which we dive into more below), generative AI was the most talked about by CEOs. LLMs, AI infrastructure, and AI strategy saw significant rises in discussions, though they only appear within 1%–2% of the earnings reports overall.

Technology and communication services sectors lead in AI discussions

The technology and communication services sectors lead most AI and AI subfield discussions. 67.6% of technology sector earnings calls mentioned the general topic of AI, while 50.8% of the communications services sector earnings calls discussed it. Generative AI was also fairly high for both sectors, with it mentioned in 33.9% of technology sector earnings calls and 24.2% in communications services sector calls. Of note, the industrial sector showed the third highest interest in generative AI, with 6% of their earnings calls mentioning the topic.

Coinciding with the topic of AI and subfields is a rise in AI strategy and infrastructure discussions. Though hovering between 0.5% and 1% of earnings calls, they rose 128% and 103%, respectively. This could be a sign that as companies look to AI to increase productivity and assess future investments, they are also considering AI implementation strategies.

Key CEO quotes on AI and its subfields

“Generative AI really [instantiated] AI in software, which means developers play a bigger role rather than data scientists. And that’s where you really see the business impact, and I think that impact will be large over the next three to five years…” – Dev Ittycheria – CEO, MongoDB, September 01, 2023

“The application of AI has both horizontal and vertical components. Horizontal is building out the AI infrastructure.” – Anirudh Devgan – CEO, Cadence, July 24, 2023

#2 AI Chips

Also coinciding with the rise in AI discussions are GPUs, most noteworthy Nvidia, the leading GPU vendor in the market. While general discussions of GPUs rose approximately 102% QoQ to 2.8% of earnings calls, Nvidia rose 146% QoQ to 1.9%. On the chipset front, CPUs only saw a 47% climb QoQ to 1.7% of earnings calls. Meanwhile, on the vendor front, Intel saw a decent climb in discussions (~48% QoQ), and AMD a subtle climb (~10% QoQ).

GPUs are becoming the core of choice for AI applications largely due to their architectural advantages over CPUs. While CPUs are optimized for task switching and fast sequential execution with only a few, large cores, GPUs often have many more, smaller cores designed for parallel processing. Deep learning involves performing many mathematical operations, including floating-point arithmetic (often used in rendering graphics) simultaneously, making GPUs a natural fit.

GPUs also offer better cost efficiency for scaling. Though more expensive than CPUs, the time savings they offer for training large language models can more than compensate for that cost. Given that the race is on for AI market dominance, time can actually be money in this case.

Key CEO quotes on AI chips

“I think you can look at 2023 as really a year of planning for AI, because as I said, there’s tons and tons of GPUs being purchased.” – Jayshree Ullal – CEO, Arista Networks, July 31, 2023

#3 Sustainability

Since their peaks in Q1 2022, the rate of discussions of sustainability, emissions, energy transition, and renewable energy in earnings calls have remained generally consistent each quarter, with each topic generally ticking up and down QoQ. This consistency signals a continued awareness of climate impact considerations in the sectors without it being a growing discussion topic in general.

That said, our analysis showed a general trend of CEOs emphasizing real-world projects for energy transition and renewable energy. It is worth highlighting that this emphasis comes amid a year (even quarter) of record temperatures. The US National Oceanic and Atmospheric Administration (NOAA) found that July 2023 had the warmest monthly sea surface temperature of any month and declared August 2023 the warmest August since NOAA started keeping global climate records 174 years ago.

Basic materials, utilities sectors and EMEA companies lead discussions on sustainability

The basic materials and utilities sectors led the discussions on sustainability—45.7% and 40.9% of their respective earnings calls—with utilities taking the general lead in discussions of emissions, climate, batteries, and renewable energy (including solar power). Of note, the energy sector had the second-highest mentions of emissions (39.3%) and the fourth-highest mentions of sustainability (30.8%).

By region, our analysis showed that European, Middle Eastern, and African (EMEA) companies talked about sustainability the most in Q3 2023, with mentions rising approximately 17% QoQ to 38.5%. Meanwhile, Asia-Pacific (APAC) companies continued to increase their number of mentions over North American companies—the former reaching 28.1% in Q3 2023 while the latter remained stagnant around 17%.

Key CEO quotes on sustainability, energy transition, and renewable energy

“The main areas of investment will be in generative AI, next-generation social infrastructure, and renewable energy.” – Junichi Miyakawa – CEO, SoftBank, August 06, 2023

“The downturn in the global economy is not—across the board—even, and consequently, there [is] still a lot of capital being moved […] And it holds for the energy transition, which is almost a given that we have to move forward one way or another.” – Tom Erixon – CEO, Alfa Laval Corporate AB, July 20, 2023

What it means for CEOs

5 things CEOs should ask themselves based on findings in this report:

1. Generative AI and data strategy: How is our company planning to leverage generative AI? Are we strategizing how to deal with this technology breakthrough and do we have a solid data strategy to ensure its effective application? Are we willing to play the “waiting game” and become a smart follower as other companies charge ahead with their generative AI plans.
2. AI chips: With GPUs seemingly becoming the hardware of choice for AI processes, how are we positioned in terms of hardware infrastructure? Do we have access (directly or through strategic partners) to the compute capacity we may need?
3. Macroeconomic concerns: With inflation, supply chain worries, and recession discussions seemingly on the decline, are we prepared for a potentially better than anticipated 2024?
4. Remote work and in-person mandates: With some companies calling employees back to the office and others continuing to operate remotely or flexibly hybrid, what are we communicating to our teams?
5. Sustainability: With an increasing focus on sustainability, what is our strategy to achieve net-zero? Are we really doing enough and have we baked in unforeseen challenges into our calculations, such as high electricity demand through the upcoming AI wave?

What it means for those serving CEOs

There is an opportunity for employees, service providers and other stakeholders to help CEOs excel at the topics they care about. Here are 5 questions those people serving CEOs could ask themselves based on findings in this report:

1. Generative AI implementation: How are we helping the CEO prioritize and implement generative AI projects? Are we helping in aligning the teams behind the opportunity and help secure the infrastructure that may be needed?
2. Making the most of generative AI: Beyond ChatGPT and obvious use cases such as chatbots or coding, what other generative AI technologies are on the horizon that might be relevant to our operations? How can we ensure that our CEO is briefed on these potential opportunities?
3. Economic pulse: While macroeconomic concerns like inflation and recession are declining in discussions, how are we ensuring that our CEO gets regular, concise, and clear updates on these topics and their potential impacts on our operations?
4. Work model adaptation: How can we help the CEO formulate a remote/hybrid work policy that ensures productivity, ongoing learning, employee happiness and safety for the employees?
5. Sustainability initiatives: Do the company’s current projects and investments reflect the increasing importance of sustainability and renewable energy? How can we help the CEO better communicate these initiatives to shareholders and the public?

The post What CEOs talked about in Q3/2023 appeared first on IoT Business News.

IoT Analytics, a leading provider of market insights and strategic business intelligence for the Internet of Things (IoT), has published its latest research on the global cellular IoT module and chipset market for Q2/2023.

The report reveals that 66% of IoT modules shipped in Q2 2023 had no dedicated hardware security and 29% had no security features at all, exposing them to potential risks and vulnerabilities.

The research analyzes the security features of 772 unique modules from 36 vendors and 150+ chipsets from 13 vendors that IoT Analytics tracks. It shows that only 30% of the modules available on the market, had dedicated hardware security features. Additionally, the article highlights the differences between the global and North American markets, where the latter has a higher share of non-dedicated hardware security features, such as TrustZone or secure boot.

KEY QUOTES:

Commenting on the importance of IoT security, Principal Analyst Satyajit Sinha noted:

“As cybercrime operates much like a business, criminals invariably opt for the path of least resistance. Implementing multiple layers of security increases the time and cost required for hackers to breach a system, thus making it more likely for them to abandon the effort and seek out less well-protected targets.”

Mr. Sinha added, “Cellular IoT modules are crucial for connectivity in IoT devices across industries. They provide a vital connection to the internet and are managed remotely. Ensuring their security is vital for safeguarding the broader IoT ecosystem.”

KEY INSIGHTS:

• The cellular IoT module market was stagnant in Q2’23 according to IoT Analytics latest data.
• Although IoT modules with dedicated security features are increasingly adopted, 66% of IoT modules shipped in Q2’23 had no dedicated hardware security and 29% had no security features at all.
• Recent demonstrations of vulnerabilities in non-dedicated hardware security features should drive the market further towards hardware-based security. Post-quantum cryptography is also an important consideration in IoT module security.

Updated cellular IoT module market

29% of cellular IoT modules shipped in Q2 2023 had no dedicated security features and only 34% had hardware-based security. Overall, the shipment and revenue of the $6.7 billion market (2022) remained generally flat in Q2’23 quarter-over-quarter, with 0% shipment and 0% revenue growth. Reasons for this stagnation include a weakened demand environment, which we discussed in our Q1’23 analysis of the cellular IoT module market.

IoT module security at the center of attention

With markets stagnating, we are putting a spotlight on cellular IoT module security by looking at the security features of 772 unique modules from 36 vendors and 150+ chipsets from 13 vendors that we track. IoT module security is of particular interest right now in light of the US Congress’ 7 August 2023 letter to the US Federal Communications Commission (FCC) regarding potential security risks of using Chinese cellular IoT modules.

Our analysis of the updated tracker and forecast shows the following breakdown of IoT module security features out of the aforementioned modules/chipsets available on the market in Q2’23:

• 30% had dedicated hardware security features, often embedded in chipsets or standalone components implemented through hardware security modules
• 42% had non-dedicated hardware security features, or features used to either create secure environments for processes to run or ensure only authorized firmware is loaded on the device
• 28% had no security features

However, the share of purchased/shipped modules with these security classifications in Q2’23 differs, with a significant difference between the global and North American markets as well:

While the global market shows a relatively balanced share of these three categories, the North American market skews heavily toward non-dedicated hardware security features. The low share of cellular IoT modules without security features in the North American market indicates that module security is a concern for its consumers, though there appears to be a reliance on non-dedicated hardware security features, such as TrustZone or secure boot.

This indication is consistent with recent concerns that the US Congress expressed to the FCC regarding the security of Chinese-made cellular IoT modules within US infrastructure (either directly or as part of the manufacturing supply chain), such as FirstNet Authority networks and devices used by first responders across the country (Quectel and Fibocom have published press releases responding to the US Congress’s concerns in early September 2023).

Why dedicated hardware security is the way forward amid supply chain concerns

Software and network security solutions have historically overshadowed dedicated hardware security features in IoT since they are more visible and easier to address, while dedicated hardware security features can be more complex and costly to implement. An alternative to software and network security solutions are non-dedicated hardware security features, such as ARM’s TrustZone, which creates a secure environment for processes to run, and secure boot, which ensures systems boot without intrusions.

Unfortunately, researchers recently demonstrated side-channel attacks against TrustZone during the Black Hat Asia 2023 conference. For their part, ARM has responded to this demonstration by stating that the attack is not unique to ARM’s Cortex-M architecture or TrustZone; rather, it’s a failure in application code—such attacks “may apply to any code with secret-dependent control flow or memory access patterns.” However, such attacks, no matter the core system they possess, demonstrate that adding dedicated hardware security solutions to these non-dedicated hardware security solutions can enhance the overall security of a module.

Shahram Mossayebi, Ph.D., founder and CEO of Crypto Quantique, explained the following to IoT Analytics when asked about cellular IoT module security:
“[W]e rely on security features such as TrustZone, but to achieve trust, we need to go beyond them. A root of trust is a set of cryptographic features (which soon must be quantum secure) for encryption, digital signature, and device identity. The hardware root of trust is the foundation for building trust with any IoT [device] and it is a crucial part of hardware security.”

With a hardware-based root of trust, manufacturers and consumers can ensure the authenticity of the modules—helping to address cloning and counterfeiting—and protection of the device’s keys. Once manufacturers can guarantee the authenticity and security of these keys, they can add additional security components like TrustZone and secure boot.

Where hardware security should be implemented

Implementing security measures at the device level during manufacturing is a foundational step, aiding in establishing device authenticity and partially curbing the infiltration of counterfeit components in the supply chain. However, this strategy only offers a partial solution since vulnerabilities still exist, particularly in the potential theft and cloning of device identities within supplier factories. Thus, an even more nuanced approach is required to bolster the defenses against such nefarious activities that seek to undermine the system from its very core.

To combat these risks more effectively, embedding hardware security at the MCU level within typical modules is highly recommended. This strategic positioning not only presents a formidable barrier against cloning and counterfeiting issues but also fosters the establishment of secure authentication protocols and the creation of unique device identities. Secure MCUs can provide a seamless integration of essential security features, such as robust authentication processes, potent encryption capabilities, and secure boot functionalities. These functionalities come together to create a fortified environment, essential for the optimal functioning of connected IoT applications, thereby ensuring a safer, more reliable network where devices can communicate and operate with an enhanced level of security and trust.

IoT module security outlook: Post-quantum security is becoming crucial for IoT

Currently, the general life span of most IoT devices is 8–12 years, with automotive 5G module applications lasting 10–15 years. With these long life spans, when building cellular IoT modules, it is essential that manufacturers look beyond current threats; specifically, they should start planning for the commercialization of quantum computing and the potential for state actors and cybercriminals to crack complex, commonly used encryption methods.

In October 2019, Google announced quantum supremacy in the journal Nature with its 54-qubit Sycamore processor, which Google claims was able to perform a complicated task in 200 seconds that would take the world’s most powerful supercomputer 10,000 years to perform. Many countries and companies are also advancing with quantum computing, such as the Chinese Academy of Sciences and QuantumCTek, a quantum information technology developer. Other Google competitors, such as IBM, Microsoft, Amazon, and Intel, along with several new startups, have all invested heavily in developing quantum computing hardware in recent years.

While quantum chips have not reached widespread commercialization yet, manufacturers can start considering quantum security solutions today. Governments are already looking at standards and quantum-proofing solutions for their agencies and companies, and the following are just some examples:

• In January 2022, the French National Agency for IT Systems Security (ANSSI) published its views and recommendations for PQC transition, offering a 3-phase process expected to last at least until 2030.
• In July 2022, the US Department of Commerce’s National Institute of Standards and Technology (NIST) announced its selection of four quantum-resistant cryptography algorithms, constituting “the beginning of the finale of the agency’s post-quantum cryptography (PQC) standardization project,” which NIST expects to complete and publish in 2024.
• In August 2023, the US National Security Agency (NSA), Cybersecurity and Infrastructure Security Agency (CISA), and NIST published a PQC migration readiness sheet to help the government and private sector start planning their quantum readiness.

Further, some companies are already developing post-quantum solutions. For example, Thales Group offers 5G security solutions with end-to-end encryption and authentication to safeguard organizational data as it moves across front-haul, mid-haul, and back-haul operations. These solutions rely on Thales’ 5G Luna Hardware Security Modules (HSMs). Further, in February 2023, Thales Group announced that it successfully piloted what it called a post-quantum resilient, end-to-end encrypted call using its Cryptosmart mobile app and its 5G SIM.

What it means for cellular IoT module manufacturers

5 key questions that cellular IoT module manufacturers should ask themselves based on the insights in this article:

1. Product strategy and security implementation: How can we realign our product strategy to prioritize the implementation of dedicated hardware security features without significantly escalating costs?
2. Response to political and legislative changes: How are we positioning ourselves to address the potential political and legislative changes affecting the market, particularly concerning the US Congress’s concerns regarding Chinese cellular IoT modules?
3. Security standards and compliance: Are we in line with the recent security standards and guidelines issued by agencies like ANSSI, NIST, and NSA, and are we preparing for the expected security transitions in the coming years?
4. Consumer education and advocacy: How can we educate consumers on the importance of dedicated hardware security features and advocate for a broader shift towards these in the market?
5. Post-quantum security solutions: Are we collaborating with communications companies and other stakeholders to develop and pilot post-quantum security solutions that can safeguard organizational data across various operations effectively?

What it means for users of cellular IoT modules

5 key questions that device/equipment makers and end users that adopt cellular IoT module should ask themselves based on the insights in this article:

1. Security implementation: Given the demonstrated vulnerabilities in non-dedicated hardware security features, what strategies should we adopt to integrate dedicated hardware security features without escalating costs significantly?
2. Compliance and legislation: In light of the concerns raised by the US Congress regarding the use of Chinese cellular IoT modules, how can we ensure compliance with evolving regulations and maintain the trust of our North American consumers?
3. Post-quantum security: Given the advancements in quantum computing, what steps should we take to incorporate post-quantum security solutions in our cellular IoT modules, keeping in mind the projected long life span of these devices?
4. Research and development: How can we foster innovation in our R&D department to develop unique hardware security features that offer robust protection against present and future threats?
5. Customer education: How can we educate our customers on the security features we use, developing trust into the security of the devices they use?

The post Cellular IoT module market Q2 2023: 66% of IoT modules shipped without dedicated hardware security appeared first on IoT Business News.

The semiconductor market saw its first market growth since 2021 amid continued trade tensions, slow economic growth, and chip shortages.

IoT Analytics, a premier source of market insights and strategic business intelligence for the Internet of Things (IoT), has unveiled new research on the IoT semiconductor market.

This comprehensive report delves into the current status and market trends, along with the drivers, challenges, and opportunities for IoT semiconductor firms and IoT device/equipment manufacturers.

A key trend underscored is the increasing incorporation of AI chipsets in edge devices. This integration facilitates quicker and more intelligent data processing and decision-making at the source. Further investigation reveals how AI is capitalizing on NVIDIA chipsets, which are predominantly employed for high-performance computing and deep learning applications. Instances of industrial AI platforms based on various NVIDIA GPUs, including Jetson AGX Orin and Jetson Orin Nano, are presented. Additionally, a comprehensive analysis of other significant trends and technological advancements in the IoT semiconductor market is provided.

The findings are derived from the IoT Chipset and IoT Module Trends Report 2023, which is grounded in thorough research and interviews with industry experts and stakeholders. It serves as a crucial resource for anyone keen on comprehending the current landscape and future trajectory of the IoT semiconductor market. The report can be procured from the IoT Analytics website.

KEY QUOTES:

Knud Lasse Lueth, CEO at IoT Analytics, comments that “In an age underscored by chip shortages, geopolitical tensions, and the ascendancy of AI, the semiconductor landscape pulsates with innovation. The unfolding narratives around IoT semiconductors not only offer solutions to pressing global challenges like sustainability and energy efficiency, but also seize fresh horizons, such as harnessing AI at the edge.”

Satyajit Sinha, Principal Analyst at IoT Analytics, added that:

“The ongoing trade tensions between the US, China, and Taiwan have significantly impacted global chip supply chains, leading to disruptions, increased costs, and delays in production. The semiconductor industry is experiencing a significant transformation due to the rising demand for AI chipsets and IoT connectivity. However, the industry also faces challenges, such as a severe shortage of AI GPUs and automotive chips. Also, it affects IoT chips based on mature nodes.”

The post Latest study highlights increased incorporation of AI chipsets in edge devices appeared first on IoT Business News.

A new study conducted by IoT Analytics, a leading provider of market insights and strategic business intelligence for the Internet of Things (IoT), has uncovered the best practices and common pitfalls of IoT software go-to-market and commercialization strategies.

While IoT continues to create winners and losers, excelling at IoT software commercialization is key to being amongst the winners. The study identified seven crucial factors for successfully commercializing IoT software, including running own webinars, deploying social media tactics and helping customers with their most pressing challenges such as IoT integration. Not only this, it also highlights the importance of learning from both successful and unsuccessful IoT commercialization ventures.

The study aims to help IoT software vendors excel at IoT software commercialization and be among the winners in the competitive IoT market. It is part of the IoT Software Go-to-Market & Commercialization Report 2023, highlighting insights from 60 IoT software executives on their current go-to-market strategies, including their views on what works and what does not.

KEY QUOTES:

Knud Lasse Lueth, CEO at IoT Analytics, comments that “The complex nature of IoT makes marketing and selling IoT software challenging. Reflecting on past IoT marketing mishaps, such as Android Things, and learning from those that are successful in the market can help avoid repeating mistakes and instead focus on the things that work.”

Dimitris Paraskevopoulos, Senior Analyst at IoT Analytics, added that

“Webinars have emerged as the #1 key factor for a successful go-to-market strategy for IoT software vendors. By leveraging the power of webinars, vendors can simultaneously educate customers and their own teams, improve their professional social media presence, and support customers through the complex IoT integration process. When managed effectively, webinars are a valuable asset for IoT software vendors looking to succeed in the market.”

KEY INSIGHTS:

• 7 factors are considered important for a successful IoT software commercialization according to the IoT Software Go-to-Market & Commercialization Report 2023.
• Running own webinars and deploying social media tactics but also helping customers with their most pressing challenges like IoT integration play a key role.

Successful IoT software commercialization: 7 important considerations according to IoT executives

Learning from IoT software failures and successes

Not every IoT software venture marks a success story, as illustrated by Google’s Android Things. Google launched the IoT OS platform in 2018 with the vision to empower a nexus of connectivity through an array of smart devices. However, it could not foster community engagement and support. Ultimately, Google ended new device registrations and projects in January 2021 and shut down Android Things in January 2022.

While some of the criticism for Android Things relates to the product itself, such as Android Things devices being bigger and more expensive than typical IoT form factors or exhibiting integration challenges with various different types of hardware, it apparently faced IoT software commercialization issues as well. For starters, there seems to have been an awareness issue. As one Android developer in a public forum stated, “I have Android Studio installed and do a little Android development. I should have heard about Android Things. I had not.” Another IoT marketing-related issue that users brought forward was the lack of community support, especially for specific IoT use cases and common IoT devices in various verticals.

Experiences like this showcase why it is important to learn from successful and unsuccessful IoT commercialization ventures. IoT Analytics’ 160-page IoT Software Go-to-Market & Commercialization Report 2023 (published in August 2023) highlights insights from 60 IoT software executives on their current go-to-market strategies, including their views on what works and what does not.

Here are the 7 important considerations which, based on our research, improve a company’s chances of being successful in the IoT software market.

1. Creating own portfolio of webinars

The number 1 tool that IoT software executives said worked for their companies is running their own webinars (Note: We queried for 19 different marketing tools). 81% of surveyed vendors indicated that this tool brought success in terms of ROI, with 50% of the respondents marking “very successful.”

Webinars offer a great opportunity for a company’s technical experts to present information about the products and answer technical questions, making the webinars engaging and interactive. By managing their own webinars, companies get to own the script and format, providing them with the time they need to offer demonstrations or run a thorough Q&A.

Further, companies can build a portfolio of webinar recordings that customers can access later. With a portfolio, the marketing teams can decide on general categories that are of interest to their company’s target industries and provide content within those categories. Examples of such categories include introduction to IoT topics, IoT in business topics, IoT case studies, and hands-on workshops.

IoT software commercialization success example: The What is IoT? webinar that Israel-based Friendly Technologies ran in November 2017 has led to widespread awareness for the company. As of September 2023, the YouTube upload of the webinar—which discusses various IoT standards and IoT device management practices—has been viewed by more than 176,000 people.

2. Improving professional social media presence

76% of the IoT executives indicated that managing their own social media content for professionals (e.g., LinkedIn) brought success in terms of ROI (18% “very successful” and 58% “somewhat successful”). Though not as high in the “very successful” category, its overall performance suggests that IoT software vendors can find success with this tool. This can be especially true if a vendor pairs this channel with another marketing tool—e.g., marketing own webinars on LinkedIn.

Managing professional-oriented social media content can be as simple as having the main company account discuss new technology and software, but several vendors found higher engagement by leveraging employee and advocate posts, especially when using third-party communications management platforms. Employee advocacy is a cost-effective approach that can establish trust and credibility, as people in an employee’s network are more likely to trust what their employee connection says, and it can help with reach and visibility.

IoT software commercialization success example: Microsoft is known to run a global employee advocacy program, allowing employees to access content tailored either to their region or to a global scale and expand the reach of social media campaigns. The former CMO of Microsoft France, Sébastien Imbert, estimates that with 10,000 employees in the program, Microsoft could see 350 million–500 million impressions per year and achieve $5 million–$10 million in equivalent advertising value.

3. Educating own team and sales force

The (perhaps surprising) top success factor for driving customer adoption, according to IoT software executives, is companies educating their own teams (not their customers), especially their own sales forces, about their products (rated 4.3 out of 5, with 1 being not important at all and 5 being extremely important). The following are 3 best practices identified in the report to support team/sales force education:

1. Tailored training: Tailor training sessions based on each team’s involvement and needs. For instance, sales teams require training on how new software works and how customers can get engaged.
2. Access to resources: Ensure their teams have access to resources like eBooks, white papers, toolkits, and internal experts that can assist their learning journeys.
3. Hands-on, cross-functional workshops: Run interactive sessions with practical learning and real-life scenarios specific to the new IoT software.

IoT software commercialization success example: The product manager of one IoT software vendor noted that communication and education between their sales team and the product management team, including their leadership was crucial. Further, the product manager added that service-level agreements for product managers to respond to sales inquiries quickly, a library of documentation for repetitive inquiries, and a “single source of truth” to capture customer requests and feedback proved to be very valuable.

4. Providing excellent, dedicated support

Overall, IoT software executives marked providing dedicated support as the second most important factor for customer adoption (4.2/5 on average). It is interesting to note that while North American and European IoT software executives remained aligned on their top three customer adoption factors, APAC executives only aligned with them on providing dedicated support, marking it as their most important adoption factor (4.4/5 on average).

This point of regional alignment is not surprising. As customers adopt and implement IoT solutions, having direct access to excellent, knowledgeable, and specialized support becomes an important factor for them. Dedicated customer support ensures customers receive tailored, specialized support for their needs, especially when the support team is well-trained and educated on the products. Further, since customers are likely making a significant investment in their IoT solutions, having the vendor–customer relationship feel more like a partnership can help with overall customer satisfaction.

IoT software commercialization success example: An example of excellent customer support, discussed in the report, is from Red Hat, with 5 key elements identified:

1. Customer portal: An online portal offering access to product documentation, knowledge base articles, and video classrooms.
2. Technical account managers: A service for customers requiring a more tailored level of support, offering a dedicated technical advisor who understands their customers’ unique environment and needs.
3. Support policies: Policies detailing the lifecycle and levels of support so customers know how long the products will receive updates and support.
4. Global reach: With a global presence, Red Hat offers timely support regardless of where a customer is located.
5. Certified ecosystem: Red Hat works with a vast ecosystem of certified partners, ensuring that third-party applications and hardware work seamlessly with Red Hat products, and if an issue arises, Red Hat can often collaborate with these partners to find solutions.

5. Supporting customers with technical integration

The number 1 customer adoption roadblock, according to IoT software executives, is “complexity of technical integration.” The VP of manufacturing/operations in a North American company provided that their “customers report that they often must deal with multiple vendors with overlapping service, [which] usually results in significant slowdowns.”

The following are 4 things IoT software vendors can do to help their customers master technical integration:

1. Provide comprehensive documentation and support: Along with offering excellent, dedicated customer support, detailed user manuals can help customers through the integration process. Further, community forums enable customers to gain insights from others who have faced and overcome similar integration challenges.
2. Offer dedicated training and education: Provide on-site training and online courses specifically addressing integration into common tools and frameworks.
3. Build integration-specific customer feedback loops: Customer support teams can establish feedback loops with customers to learn about their integration challenges and work with development teams to improve integration capabilities based on the feedback.
4. Offer IoT integration services: Build internal teams or partner with reliable system integrators so that various “integration” services can be offered to customers.

IoT software commercialization success example: German IoT platform provider Software AG offers a number of IoT professional services to help companies adopt, learn, and manage their digital transformation solutions, and it also offers a readiness guide that explains the typical digital transformation journey, the pain points, and other considerations.

6. Helping customers overcome internal resistance to change

IoT software executives marked “resistance to change” as the second-ranked customer adoption roadblock. A core theme in the survey responses revolved around familiarity with old and new software. The VP of a company in the UK noted “there is a tendency to not want to adopt new solutions, especially by relatively older employees.”

The following are 5 things IoT software vendors can do to help their customers reduce internal resistance to change:

1. Provide data that supports the value proposition: Offer data-driven evidence on how the software can improve efficiency, save time, reduce costs, or provide any other tangible benefits.
2. Engage key stakeholders early: Identify and engage decision-makers and influencers within the customer’s organization from the onset. If they see value in the software, they can become champions who drive adoption.
3. Offer pilots: Allow customers to run pilot programs. This lets them test the software in a limited capacity, reducing risk and giving them a taste of the potential benefits.
4. Share case studies: Share success stories from other similar enterprises. When potential users see that their peers have benefited, they may be more inclined to adopt.
5. Provide communication templates: Provide the enterprise with communication templates or tools they can use to convey the importance and benefits of the software to their teams.

IoT software commercialization success example: The IT manager of an IoT software vendor in the Philippines shared the following successful strategy: “Usually, the customer’s concerns are around familiarity. They are so used to an old model that when we introduce new software, they are afraid/overwhelmed. We can alleviate that by having highly trained individuals who can explain the new systems thoroughly and point out similarities of the new software to the one that the customer is already familiar with so that they can better understand.” This goes back to vendors putting emphasis on training and educating their own teams as well as building up knowledge to understand other software and how it compares.

7. Considering regional adoption rates and strategic rollouts

When designing a go-to-market strategy, IoT software vendors should consider in which region they roll out their software first. 70% of the surveyed vendors indicated that North America had “very quick” or “quick” adoption of software, with Central Europe and East Asia following at 58% and 54%, respectively.

Regions with faster IoT software adoption typically have a higher demand for the software and a willingness to invest in IoT solutions. Focusing on these regions that have faster adoption rates can help vendors realize ROI faster. However, this does not mean that other regions should be ignored. Rather, when going to market, focusing on regions with faster adoption rates affords vendors more customer success stories that they can reference for potential customers in other, slower regions.

10 questions IoT software vendors should ask themselves now

This article highlights 7 of many insights that IoT software executives in the IoT Software Go-to-Market & Commercialization Report 2023. Based on the insights presented here, executives at IoT software vendors should discuss these questions to help avoid becoming the next Android Things:

1. How can we expand our portfolio of IoT webinars and ensure that they address the specific needs and interests of potential and existing customers more effectively?

2. Are we utilizing the potential of our own employees to enhance our presence on professional social media platforms like LinkedIn?

3. How can we improve our team education strategies to make sure every member is not only informed but also adept at communicating the unique selling points of our products?

4. Are our support teams sufficiently equipped with the resources and training to offer exceptional, dedicated support to our customers?

5. How can we innovate our integration tools to reduce complexity and facilitate a smoother transition for customers shifting from legacy systems?

6. What strategies are we implementing to lessen resistance to change among customers (e.g., helping customers involve key stakeholders)?

7. Are we considering the regional adoption rates adequately while strategizing our market rollouts?

8. How can we foster a community where customers can share their experiences and learn from each other, potentially reducing the resistance to change?

9. How effective are the mechanisms we have put in place to gather continuous feedback from our customers, ensuring that our products are constantly evolving to address their pain points (e.g., technical integration)?

10. How can we leverage customer success stories more effectively to build trust and accelerate adoption (e.g., in regions with slower uptake rates)?

The post New study reveals the hidden secrets of successful IoT software commercialization appeared first on IoT Business News.

This article is based on insights of the 82-page Digital Operation Signals – Industrial IoT Solution Spotlight (July 2023) report, published by Microsoft with research conducted by IoT Analytics. The report takes a deeper look at 300 recent IIoT initiatives, their challenges, their successes and particularly how they are implemented. IoT Analytics surveyed key stakeholders working on their respective employers’ IIoT initiatives between October and December 2022 and conducted in-depth interviews with a subset of them.

State of Industrial IoT in 2023

Industrial IoT (IIoT) in 2023 is on the way to becoming mainstream:

• Two-thirds of industrial organizations reported they are executing an IoT strategy.
• IoT projects have a 14% higher success rate than five years ago.
• The median time for IIoT projects to break even has decreased from 24 to 20 months over the same period.
• Common challenges such as budget availability, project complexity, and data management have diminished by approximately 50%.

While IIoT is becoming more mainstream, a core question persists: should companies try to buy a readily available IIoT solution, should they custom-build an IIoT solution, or is there a middle option?

The research shows that there is no universally best approach to IIoT implementation. However, there is often a right approach for individual projects.

Build, buy, or buy and integrate?

Finding the right approach for individual IIoT projects depends on several organizational factors, including:

• Available budget
• Desire to differentiate from competition
• Break-even / ROI goals
• Use cases at hand

The research found a growing trend toward the buy approach: 30% of projects that began in 2021 or 2022 used the buy approach compared to only 9% of projects completed in or before 2020. This growth has come at the expense of a reduced preference for the buy-and-integrate approach, which dropped from 50% to 28%.

“We clearly see a trend that people prefer proven standardized solutions”

IoT solutions providers have recognized this trend as well. David Shook, Chief Data Officer of US-based Uptake, which helps customers realize IoT solutions, explains, “We clearly see a trend that people prefer proven standardized solutions rather than building something from scratch.”

However, many organizations are still opting for the build and buy-and-integrate approaches. The report offers insight into the decision-making process for each approach.

1. The build approach to IIoT solutions

47% of respondents stated their IIoT initiatives used the build approach, with 40% stating that their custom-built solutions exceeded their expectations. Different industries have different solution footprints. For example, 89% of respondents from the buildings industry reported using the build approach, while 33% from the machinery industry reported the same.

“If you build it, you own it.”

Key reasons to build

In the words of a US cloud integration advisory firm VP, “If you build it, you own it.” This sentiment captures the core benefit of the build approach: organizations that build their IIoT solutions own the intellectual property rights, and they can incorporate any features they desire. The approach provides the freedom to customize the entire IIoT solution, from how it integrates with new and current equipment to the user interface/user experience. In addition to this, organizations don’t have to lock in with a vendor.

Key reasons not to build

The decision to build an IoT solution comes with costs in terms of money, effort, and time. First, organizations either need a robust IT department or a reliable partner to not only build and integrate the solution for them but also to maintain and update the solution.

Next, developing a solution can come with high or unexpected costs, with large funding often taking time to get approved. 20% of respondents experienced budget constraints, the largest challenge faced with this approach, and the strategy director for a Spanish electronics company explained, “Huge funds were required for this initiative, and it took a long time for us to collect such a large sum of money.”

Finally, building an IIoT solution typically leads to the longest project timeline out of the three approaches, from start to large-scale roll-out. The report shows that the stakeholders reported a median of 9 months just to develop the business case—versus 6 months for the buy approach. The other phases of development and launch, including median time to amortize investments, were also longer than the buy approach.

2. The buy approach to IIoT solutions

With IIoT becoming more commonplace and IoT developers from various industries sharing lessons learned, more off-the-shelf solutions are coming to market, though availability is still limited. As organizations standardize their operations with standard industrial hardware or IT architecture, tried-and-tested IIoT solutions can integrate with these tools for better operability and analysis. For new companies, starting with a ready-made solution allows them to build IT/OT architecture around their IIoT solution rather than trying to integrate after the fact—a ground-up approach.

“It is rarely necessary to go for a custom-made solution in the first stages”

Key reasons to buy

Newer or smaller organizations with limited budgets and resources can benefit from ready-made solutions. A director of logistics for a European machinery equipment company noted that “it is rarely necessary to go for a custom-made solution in the first stages of [a business] journey” since companies need to learn and understand their customers’ needs, adding that “starting with standard products accelerates projects and reduces overall cost.”

Reduced implementation time is another benefit of the buy approach. The research found that with this approach, the median time required to complete the first two phases of an IIoT project was 9 months, compared to 16 months for the build approach. Since the buy approach offers ready-made, reliable solutions, organizations and vendors only need to customize the solution to the organization’s needs and equipment.

The research also found that 43% of respondents that used the buy approach experienced reduced break-even points, with a median time of 12 months from the first project-related expense to reaching the commercial break-even point compared to 20 months for other approaches.

Finally, the buy approach allows an organization to remain slim. The external developers of ready-made solutions will often offer continued support and updates for the solutions, meaning the organization does not need to maintain an internal team just for this purpose.

Key reasons not to buy

While the buy approach limits necessary resources and shortens implementation time, only 13% of respondents stated that the approach exceeded their expectations. The report shows that 30% of projects using ready-made solutions were missing end-user capabilities, and 20% faced challenges with addressing cyber threats.

13% of projects experienced both internal cooperation and resistance to change issues as well. Because commercial IIoT solutions come with their own processes, workflows, and (sometimes) equipment, organizations may find it difficult to integrate the solution into their own processes and architectures. A senior engineer of a German chemicals company stated, “To support the maintenance team for IoT devices, the change management team had to do several hands-on trainings.”

3. The buy-and-integrate approach to IIoT solutions

38% of IIoT initiatives in the dataset use the buy-and-integrate approach. Buying and integrating an IIoT solution allows organizations to combine proven technology and product support with the freedom to customize the solution to their IT/OT and user experience needs. It also helps address some of the limitations of the build and buy solutions, such as implementation time and end-user capabilities.

The report shows that the electronics and machinery industries saw the most build-and-integrate solutions (57% and 52% of projects, respectively).

“Buying and integrating allows to combine proven technology with the freedom to customize”

Key reasons to buy and integrate

Opting for the buy-and-integrate approach can often come out of necessity, including some of the following factors:

• Lack of off-the-shelf solutions that meet an organization’s IT/OT architecture
• Limitations on capability in fully developing and/or maintaining a solution
• Budgetary constraints
• Cyber security needs not met by available solutions

The decision to use this approach can also include preferential reasons, including:

• The freedom to customize a majority of the solution
• Creating a defendable competitive advantage that a widely available off-the-shelf solution cannot provide
• Limiting reliance on vendors, balancing necessary support and updates with the ability to adapt to changes in-house.

One respondent, the chief experience officer of a US pharmaceuticals company, stated a combination of necessity and preferential factors: “We did not have adequate in-house knowledge in IT or operations to consider building from scratch. We did not want to be entirely dependent on third parties for maintenance. A tailored solution was essential to ensure operator confidence, so a hybrid model was best.”

Complex integration projects can also benefit from the buy-and-integrate approach, where a custom-built solution would be too costly and ready-made solutions are not designed to handle the complexity. An engineering manager for an FMCG manufacturer said, “Because the size of our plant is too large, it became really difficult for us to sync our machines with the various sensors and software tools in use.” Opting for the buy-and-integrate approach allowed the company to integrate the various commercial software tools and their various OT equipment.

Key reasons not to buy and integrate

While the buy-and-integrate approach finds a positive middle ground between the other two approaches, it also absorbs some of the disadvantages of those approaches. First, ready-made solutions are often built with specific applications in mind, so engineers and developers need to understand the solutions and work with vendors to develop additional integration services. This requires additional management of internal and external stakeholders.

Additionally, though the buy-and-integrate approach may be ideal for complex projects, the complexity of implementation and integration was the top challenge faced by adopters of this approach (19% of projects). Second to this was organizations lacking IT capabilities to customize and integrate the solutions (15% of projects), requiring further dependency on vendors to develop and maintain solutions.

Finally, the development of additional integration services becomes an additional project for the organization, meaning uncertain costs can come into play.

These reasons are some of the factors leading to this approach having the longest break-even time of the three options.

Which approach to choose

While there is no universal best solution, the report shows that organizations should carefully weigh which approach best fits their budget, their desire to differentiate themselves from competitors, their break-even goals, and the use cases.

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According to IoT Analytics, a leading global provider of market insights and strategic business intelligence for the Internet of Things (IoT), the industrial IoT gateways market accelerated significantly from 2021 to 2022, growing ~14.7% to reach $860 million (38% of the overall IoT gateways market).

KEY QUOTES:

Knud Lasse Lueth, CEO at IoT Analytics, comments that:
“Industrial IoT gateways are critical for connecting legacy systems with modern technology. They also play an important role to support the migration of manufacturing applications to the cloud. In the future I also expect a number of smaller applications to sit directly on IIoT gateways, leveraging containerization technology, more powerful storage and computation and in some cases even AI chips for ML inference.”

Kalpesh Baviskar, Analyst at IoT Analytics, added that:

“IoT gateways have emerged as a highly cost-effective solution for deploying IoT systems with multiple sensors. They play a crucial role in connecting legacy equipment and devices that were previously unconnected.”

“In recent years, we have seen the integration of high-performance processors and AI chipsets into IoT gateways, transforming them into edge IoT gateways. These edge gateways can perform local data processing and analytics, significantly reducing the amount of data that needs to be sent to the cloud. This can lead to significant cost savings and performance improvements for IoT applications.”

KEY INSIGHTS:

• According to the IoT Gateway Market Report 2023–2027, the $0.9B industrial IoT (IIoT) gateway market experienced accelerated growth between 2021 and 2022, which is set to continue on the back of several favorable tailwinds.
• IIoT gateways are enabling IT and OT convergence by securely and efficiently sharing data between floor-level OT equipment and IT equipment or the cloud—with implementation typically as part of one of four broader IoT architectures.
• There are several IIoT gateway advancements e.g., in security, edge computing, and storage.

The vital role of industrial IoT gateways in bridging IT and OT

IIoT gateways: Market and role

The industrial IoT gateways market accelerated significantly from 2021 to 2022, growing ~14.7% to reach $860 million (38% of the overall IoT gateways market), and we forecast continued growth at least through 2027. The factors driving this growth include the following:

• Connecting the unconnected. Many companies are retrofitting their legacy equipment with sensors and controllers, using IIoT gateways to perform necessary protocol and data transformation and transfer the data to an IT endpoint.
• Software applications are migrating. Companies with connected equipment are moving some key applications to the cloud, with IIoT gateways emerging as the main nexus point for information flow in and out of industrial premises. Some applications are also now run locally on the gateway itself.
• More powerful hardware. New, enhanced gateways with embedded multi-core processors, AI chipsets, and secure elements are enabling faster and more secure data processing and transmission (to an IT endpoint or cloud).

These factors reflect our assessment that IIoT gateways are becoming the juncture for IT and OT convergence.

Note: When we refer to IIoT gateways, we refer to (ruggedized) hardware that connects sensors, IIoT devices, and industrial equipment to cloud or on-premises servers or PLCs/IPCs operating on distinct industrial networks. For an exact definition, refer to our report.

How IIoT gateways connect the IT and OT worlds

Many companies maintain legacy equipment that does not have sensors or control devices. Even if the legacy equipment has sensors or controllers that connect locally, such as to a human-machine interface or panel PC on the factory floor, it may not offer connectivity options or use messaging protocols that end equipment (like an IT server or cloud) uses. Meanwhile, companies that possess IoT-enabled equipment may desire to move data off-premises (e.g., to remote IT equipment or the cloud) or enhance local data computation for automated responses before transmitting the data.

In cases like these, IIoT gateways can connect with standalone or integrated sensors—either wirelessly or wired through I/O module masters—to transmit data to IT or cloud servers. As described below, they fit within many architectures found in industrial IoT solutions.

IIoT gateways within IoT architectures

Whether a company builds or buys an IoT solution, the solution will align with an IoT architecture to collect and transmit data to the endpoint. While a direct sensor-to-cloud architecture does not require the use of an IIoT gateway, IIoT gateways are commonly found in 4 general types of IoT architectures.

1. Sensors/devices to PLC/IPC to IIoT gateway to cloud

In industrial environments with existing automation hardware, the sensors/devices to PLC/IPC to IIoT gateway to cloud architecture is very common. Field sensors or actuators are connected to I/O module masters. These I/O module masters transmit data to the on-premises PLC or IPC. The PLC/IPC is then connected to the IIoT gateway, which serves as a bridge between the PLC/IPC and the cloud.

This architecture can be very powerful but also potentially dangerous. The IIoT gateway can technically be configured to remotely access the entire architecture that sits below the PLC/IPC. While this setup enables any data to flow between IT and OT and thus any imaginable use case, it also has the biggest potential attack surface (potentially the entire facility), e.g., in case of a misconfigured security architecture.

2. Sensor to I/O modules to IoT gateways to cloud

In the sensor to I/O module master to IoT gateways to cloud architecture, simple sensors connect to I/O module masters. The I/O module master then uses wired or wireless connectivity standards to transfer data to IIoT gateways, bypassing any PLC or IPC. This architecture proves to be highly effective in scenarios where multiple sensors are arranged into clusters—the I/O module master acts as the central node for each cluster of sensors, efficiently gathering and transmitting data to the cloud via an IIoT gateway.

3. Sensors in devices to IoT gateway to cloud

In the sensors in devices to IoT gateway to cloud architecture, devices equipped with single or multiple onboard sensors are connected directly to the IIoT gateway. This architecture is often deployed where non-standalone IoT devices are used (i.e. devices that cannot connect to the internet by themselves).

4. Sensors to IoT gateway to cloud

In the sensors to IoT gateway to cloud architecture, IIoT gateways enable connections between sensors and cloud servers directly. This architecture can for example be found when retrofitting specific sensors on an asset (e.g., for condition monitoring) with the desire to bypass all other existing networks (to not interfere with them and create a new security risk).

Advancements in the capabilities of IIoT gateways

As IIoT gateways have become more common in IIoT solutions, they have become capable of offering more for their users. In general, IIoT gateways typically offer 8 key functions:

• Protocol translation
• Data management
• Device management
• Computation
• Communication
• Resource management
• Security management
• Managing quality of service

As the IIoT gateway market has grown, these functions have advanced. The following are just some examples of advancements.

“A growing number of customers [are] requiring proof of security level from manufacturers for their industrial IoT equipment.”

Security management

As the number of connected devices continues to increase, the risk of cyberattacks and unauthorized access becomes more significant. This is especially true for companies looking to connect factory equipment to external IT or cloud servers. Fortunately, to address these risks, IIoT gateway vendors are proactively incorporating security features into their products and adhering to industry-specific regulations and standards, allowing OT monitoring and control to reside securely behind layers of policies and access controls.

A notable series of standards is IEC 62443, approved in 2021, which directs all IEC 62443-certified products to adhere to specific product development requirements from the early stages of design. This set of standards has become mandatory technical requirements in many countries, and according to Pascal LeRay, Head of Cyber Security at Bureau Veritas, “a growing number of customers [are] requiring proof of security level from manufacturers for their industrial IoT equipment.”

In our research, IIoT gateway companies noted the importance of incorporating security standards in their products. Teltronic’s CEO, Juan Ferro, stated that “the sudden irruption of cybersecurity in the industry has been interpreted by Teltronic as an opportunity to improve both [our] products and associated processes,” adding that the pre-emptive adoption of security standards placed them ahead of other companies in their sector.

Along with standards, IIoT gateways are increasingly incorporating hardware security, using embedded secure elements either within processors or on the PCB/modules as trusted platform modules (e.g., TPM 2.0). Ultratronik’s A1 IoT gateway integrates NXP’s EdgeLock SE051 secure element, and Eurotech’s RELIAGATE 10-14 series maintain IEC 62443-4-1, -4-2, and PSA Level 1 certifications and have a TPM 2.0 security chipset—OPTIGA TPM SLM 9670 from Infineon Technologies.

“The milliseconds of latency [between] an industrial robot and many real-time systems can be the difference between a safety hazard and a productive assembly line.”

Computation

IoT gateways in general have trended toward more processing power. In industrial solutions, this has helped companies move data processing and computation toward the solution’s edge—nearer to the data collection point—saving them bandwidth and communications power and freeing their IT and cloud servers to manage other tasks. Additionally, there has been a trend of integrating AI chipsets into some IoT gateways to facilitate edge computing. A noteworthy example is AAEON’s AIOT-AVID IoT Video Analysis Gateway, which incorporates Intel’s Myriad X vision processing unit (VPU).

The ability to process and automate data in real time can mean much for a company’s bottom line, as one senior VP stated, “The milliseconds of latency [between] an industrial robot and many real-time systems can be the difference between a safety hazard and a productive assembly line.”

Data and resource management

Local data storage helps enable data processing at the edge. Further, some industrial use cases may call for data sorting and analysis before being transmitted to an IT or cloud server, either due to limited network connectivity or the desire for more efficient use of IT equipment.

The need for local data storage has led to eMMC flash memory and SSD solutions on IoT gateways in general. In mid-2022, Robustel launched three ARM-based IIoT gateways with varying DDR and eMMC sizes to meet application needs. A few months later, Compulab announced its IOT-GATE-RPI4, a Raspberry Pi-based IIoT gateway that offers up to 128 GB of eMMC memory and mPCIe slots for SSD storage expansion up to 256 GB. Other examples include MOXA’s AIG-301 series IIoT gateway with 16 GB of eMMC and Belden’s Hirschmann OpEdge-8D with 64 GB of SSD flash memory.

Device management

With integrated storage comes the ability to containerize applications for deployment on IoT gateways, including device management software. Traditionally, deploying applications on IoT gateways involved installing them directly on the equipment’s operating system, which had limitations in terms of scalability, flexibility, and ease of management. However, companies are increasingly using containerization as a deployment strategy for applications on IIoT gateways, offering platforms like Kubernetes and runtimes like Docker. These technologies provide a way to create lightweight and isolated runtime environments, known as containers, where applications can run consistently across various platforms and environments.

Many gateway OEMs are also building app stores with hundreds of ready-made applications that end users can deploy to their gateways (and in the cloud), such Bosch Rexroth’s ctrlX store, Siemens’s Industrial Edge Marketplace, and Advantech’s WISE-Marketplace.

Key Benefits of IIoT Gateways

In our analysis of 65 case studies, we identified numerous benefits of IIoT gateway implementations based on various use cases. The following are 3 of the main benefits companies cited.

1. Better IT/OT integration

Indeed, this is a key goal of implementing IIoT gateways, and our analysis shows that many companies have achieved this goal. A common goal of IT/OT integration is remote monitoring and response. As an example, Vitesco Technologies Italy used Zerynth’s 4ZeroBox, an on-premises IIoT system for real-time monitoring and predictive maintenance. This solution enabled Vitesco to predict pneumatic valve malfunctions 24 hours in advance, which reduced assembly downtime and increased productivity.

2. Reduced labor costs

IIoT gateways are often deployed for automation purposes and as such can reduce labor costs, human effort, and human errors. While Vitesco saw a 50% reduction in its manual labor requirement with its 4ZeroBox application, Colombian steel manufacturer Corpacero cut costs associated with repair labor after partnering with Senzary to deploy RotaryIQ and InsightsIQ solutions for predictive maintenance and remote machine management.

3. Energy savings

Enterprise energy management analytics software provider Wattics partnered with Kontron to use Kontron’s KBox A-101 as a central ‘edge node’ for Wattics Sentinel software at the customer’s site. It connects to the local energy grid and the Sentinel grid, facilitating meter configuration, reliable data collection, pre-processing, compression, and secure communication.

IoT gateway market outlook

With many companies seeking to either retrofit their equipment or enhance their IoT solutions, we have seen solid growth in the IIoT gateway market (8.1% CAGR) between 2018 and 2022, with acceleration specifically from 2021 to 2022. We assess that this trend will continue since use cases in manufacturing and certain applications continue to demand real-time processing, low latency, and secure data handling. Further, the following 5 trends, which are discussed in more depth in the IoT Gateway Market Report 2023–2027, support this assessment:

1. IoT gateways are becoming more modular, allowing IIoT gateway vendors to offer a range of options and configurations to meet customer needs and enable easy scalability.

2. IoT gateways are supporting more wireless connectivity options, such as secure cellular solutions with eSIM/iSIM technology, enabling IIoT gateways to handle multiple connected devices in an expanded perimeter of operations.

3. IIoT gateway vendors are collaborating to combine hardware and software solutions, simplifying deployments and reducing costs.

4. OT hardware is starting to consolidate (e.g., I/O module masters shifting to IIoT gateways)

5. Virtualization of workloads (e.g., virtual PLCs) allows IPCs and IIoT gateways to perform tasks that were previously tightly coupled to other pieces of hardware.

IIoT gateways play a pivotal role in bridging the gap between legacy machinery and modern systems, facilitating retrofits and brownfield installations. As industries strive for global connectivity and centralized management of OT devices, IIoT gateways will continue to play a major role in integrating operations across various locations.

What it means for IoT gateway vendors

5 key questions IoT gateway vendors should ask themselves based on the findings of the report:

1. Do our IIoT gateways remain compliant with updated security standards?

2. Do our customers require AI edge capabilities as a general offering?

3. Have we explored local data storage options to increase computation while decreasing latency?

4. Should we containerize our edge IIoT applications? And if so, how?

5. Are our general solutions enabling seamless IT/OT integration for customers? If not, should we focus on tailored solutions for our customers?

What it means for IoT adopters

5 key questions IoT adopters should ask themselves based on the findings of the report:

1. Have we assessed the various available IIoT gateways and their potential impact on our overall IoT strategy?

2. Which IoT architecture(s) are we using? Can an IIoT gateway offer improvements?

3. Do our current IIoT gateways meet current security standards? If not, what updates do we require to meet these standards?

4. Have we assessed the possible benefits of edge computing (e.g., automating controls locally based on the data)?

5. Should we leverage local data storage and containerized applications for better device management and updates?

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According to IoT Analytics, a leading global provider of market insights and strategic business intelligence for the Internet of Things (IoT), the eSIM/iSIM market is set to surpass 500 million units in 2023 as it brings in the new age of cellular IoT.

More information can be found in IoT Analytics’ new Global IoT eSIM Modules and iSIM Chipsets Market Tracker, which provides quarterly data on worldwide IoT eSIM modules and iSIM chipsets from 2018 to Q1 2023.

KEY QUOTES:

Satyajit Sinha, Principal Analyst at IoT Analytics, comments:

“Looking ahead, it’s evident that eSIMs are positioned to become the primary SIM technology in the next 2-3 years, surpassing their counterparts. This shift is expected to be followed by the emergence of iSIMs, which are predicted to gain popularity due to their advanced security features, including a hardware root of trust. We’ll likely see a gradual transition from eSIMs to iSIM technology, as iSIMs are expected to become the preferred choice in the long term due to their inherent security advantages.”

KEY INSIGHTS:

• eSIM/iSIM is transforming the dynamics of the cellular IoT market, offering increased flexibility, reduced provisioning time, smaller form factor, enhanced security, and sustainability.
• The eSIM/iSIM IoT market is poised to surpass the 500-million-units mark in 2023.
• Two factors will likely drive the growth of eSIM and iSIM in the cellular industry: cybersecurity regulations and GSMA specifications.

Entering the new age of cellular IoT: eSIM/iSIM market to surpass 500 million units in 2023

Market overview

The cellular IoT market is undergoing a significant shift: physical subscriber identity module (SIM) cards as we know them are becoming virtualized in the form of embedded SIMs (eSIMs) or integrated SIMs (iSIMs).

In 2023, the IoT module eSIM/iSIM market is poised to surpass the 500-million-unit mark. Just in the first quarter, over 450 million IoT modules were already capable of supporting eSIM or iSIM—roughly 16% of the 2.8 billion active global cellular IoT connections. This data indicates the growing demand for flexible, fast, and efficient connectivity solutions in the new age of cellular IoT.

eSIM/iSIM is transforming the dynamics of the cellular IoT market

The rise of eSIM/iSIM technology is not just a mere technological advancement; it is a paradigm shift. It is about the seamless integration of IoT devices, the simplification of connectivity, and the enhancement of user experience. The use of eSIMs/iSIMs can help businesses decrease time to market and improve the efficiency of IoT deployments.
This technology offers several advantages over traditional SIM cards, including:

1. Increased flexibility for IoT solutions

eSIM/iSIM technologies offer increased flexibility and reduced provisioning time for IoT devices. By allowing devices to be provisioned with different carrier profiles remotely, they enable seamless switching between networks without the need for physical SIM card changes. This flexibility is particularly beneficial for businesses deploying IoT devices in multiple countries or regions. Additionally, the ability to remotely provision and update eSIM/iSIM saves time and simplifies the deployment process, especially in large-scale IoT deployments, empowering businesses to adapt quickly and optimize their IoT deployments.

Several car companies, including BMW, Audi, Tesla, and Volkswagen, have implemented eSIM technology to offer connected car services. Through their respective platforms, these companies can remotely activate, manage, and switch mobile network profiles. This allows for more flexibility and scalability in IoT deployments.

2. Compact eSIM/iSIM enables smaller IoT devices

eSIM and iSIM technology allows for more compact IoT device designs. This makes devices smaller and more lightweight than traditional SIM-card-based devices. Notably, eSIM/iSIM technology has facilitated the development of smart labels, which are paper-thin devices that offer precise, accurate, and secure tracking of small and lightweight items.

DB Schenker, the logistics arm of Deutsche Bahn, implemented an ultra-thin smart-label solution to track small freight consignments globally. Sensos, an Israeli group company of the Sony Semiconductor Solutions Corporation, developed the solution, which leverages Kigen’s iSIM technology embedded within Sony Semiconductor Solutions’ low-power wide-area (LPWA) chipset.

3. Enhanced security with embedded secure elements in eSIM/iSIM

eSIM/iSIM technology incorporates embedded secure elements, providing advanced security features compared to traditional SIM cards. The secure element acts as a hardware root of trust for asymmetric encryption, ensuring secure end-to-end communication. The GSM Association’s (GSMA) IoT SAFE specifications leverage a single eSIM/iSIM as a hardware root of trust.

Meanwhile, chipset vendor Sony Semiconductor Israel’s ALT1250 and ALT1350 chipsets integrate two secure elements for application security and UICC identity (Sony Semiconductor Israel was formerly known as Altair Semiconductor and is now a group company of Sony Semiconductor Solutions Corporation).

The eSIM in Tesla vehicles enables features such as remote vehicle monitoring, software updates, and over-the-air (OTA) updates for the vehicle’s firmware. The eSIM acts as a hardware root of trust by securely storing cryptographic keys and certificates used for authentication and encryption.

4. Sustainable eSIM/iSIM technology reduces waste and emissions

eSIM/iSIM technology eliminates the need for physical SIM cards, reducing electronic and plastic waste. Additionally, the elimination of physical SIM card shipments to IoT modules or devices helps reduce emissions associated with transportation. These environmental benefits make eSIM/iSIM a sustainable choice for IoT connectivity.

Journey to 500 million: eSIM market penetration increased, iSIM is emerging, and GSMA streamlines deployment

Per IoT Analytics’ Global IoT eSIM Modules & iSIM Chipsets Tracker, eSIM penetration within cellular IoT modules experienced a significant increase, with quarterly shipments of eSIM-capable modules rising from 7% in Q1 2018 to 31% in Q1 2023. Notably, there was a period of stagnation in this growth during 2021; however, from Q1 2022 onward, we observed a consistent adoption rate through Q1 2023.

Meanwhile, iSIM is still an emerging technology in IoT. Sony Semiconductor Israel’s ALT1250 is the only iSIM-based cellular IoT chipset that reached mass shipments.

So far, the implementation of eSIM/iSIM IoT standards has been slower than initially anticipated. This is primarily due to the complexities of remote SIM provisioning and different standards for consumer IoT and machine-to-machine (M2M) technologies.

To address this issue, GSMA developed new eSIM IoT specifications, namely SGP.31 and SGP.32, that are designed to complement the existing M2M (GSMA SGP.02) and consumer IoT (GSMA SGP.22) eSIM standards. The new specifications allow for remote control and configuration of eSIMs via a dedicated management module, adapting from the current eSIM Consumer and IoT Specification.

This approach eliminates the need for user interaction when provisioning, simplifying IoT connectivity and reducing the time to market for IoT deployments. Moreover, this enhancement may eliminate the need for carrier integration, giving enterprises the same flexibility and control as consumers, thus marking a significant advancement for IoT implementations.

The release of GSMA SGP.31 and SGP.32 marked significant changes in eSIM IoT deployment in three ways:

• Introducing the eSIM IoT Remote Manager (eIM)
• Transforming Local Profile Assistance (LPA) into IoT Profile Assistant (IPA)
• Replacing Subscription Manager Secure Routing (SM-SR) with Subscription Manager Discovery Server (SM-DS) and IPA in the architecture

These changes streamline both remote profile management and provisioning processes and eliminate the need for SM-SR in eSIM IoT deployments.

The future of eSIM/iSIM in cellular IoT

Looking ahead, we expect eSIM/iSIM technology to further increase its penetration in the cellular IoT market.

Currently, the market is still dominated by a combination of physical SIM cards, uSIM, and soft SIMs (software-based UICCs in a trusted execution environment), with a combined (shipment-based) market share of approximately 67%. (Note that Soft SIMs are not considered to be secure, as they lack an anchor with a hardware root of trust.)

As the industry progresses, we assess that eSIMs will become the dominant SIM technology in the next 2–3 years. Afterward, with the next cycle of module hardware, iSIMs are likely to start grabbing market share since they offer enhanced security features and are anchored with a hardware root of trust, making them a more secure option. In the long run, it is expected that even the eSIM market will migrate toward iSIM technology, with iSIM then dominating the market.

Two factors will likely drive the growth of eSIM and iSIM in the cellular industry:

1. Cybersecurity regulation

The importance of robust security measures in cellular IoT cannot be overstated. Cybersecurity regulations are playing a pivotal role in strengthening IoT security, particularly through the implementation of hardware-based solutions.

Given the recent activity around EU and US technology regulation, it is likely that the coming years will see new laws mandating stronger IoT security, potentially requiring the use of a hardware root of trust.

In this context, eSIM/iSIM technology emerges as a practical solution for implementing chip-to-cloud security. By leveraging the secure element as a hardware root of trust, it is possible to enable asymmetric encryption, thereby bolstering the overall security framework. It is noteworthy that cellular IoT vendors are already guided by GSMA’s IoT SAFE specifications, which provide valuable insights and guidelines in this area.

2. GSMA specifications

GSMA’s SGP.31 and SGP.32 will play a crucial role in the future of eSIM/iSIM in cellular IoT. By streamlining the remote profile management and provisioning processes, these specifications will simplify the deployment of IoT devices and reduce the time to market. Furthermore, the introduction of eSIM and the transformation of LPA into IPA will provide businesses with greater control over their IoT deployments, enabling them to adapt quickly to changing market conditions and customer needs.

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IoT Analytics has conducted an extensive keyword analysis based on a comprehensive dataset of approximately 75,000 earnings calls from leading US-listed firms.

The findings from the second quarter of 2023 reveal crucial discussions led by CEOs, focusing on three pivotal themes: Generative AI applications, bank challenges, and economic uncertainty. These influential topics have captivated boardrooms worldwide, ultimately shaping the future investment priorities for companies across various industries.

KEY QUOTES:

Philipp Wegner, Principal Analyst at IoT Analytics, comments:

“CEOs are now discussing how their companies can use generative AI applications. The discussion shifted to actual deployment of Large Language Models.”

KEY INSIGHTS:

• According to the latest “What CEOs talked about” report, three themes noticeably gained traction in earnings calls in Q2/2023: 1. AI & Generative AI, 2. Bank troubles, and 3. Reshoring.
• Discussions around economic uncertainty, sustainability, and supply chain disruptions lost traction.

The big picture

In Q2 2023, economic uncertainty remained the most discussed theme in boardrooms globally.

There was a notable decline in the number of CEOs discussing inflation, with only 50% mentioning the keyword (a 21% decrease from the previous quarter). Similarly, other related topics also experienced a decrease in prominence, with interest rates being discussed by only 33% (-13%) of CEOs and the term “recession” being mentioned in just 18% (-15%) of all earnings calls in Q2/2023. Despite these slight variations in the focus on economic topics among CEOs, it is important to note that overall, economic uncertainty remains a prevailing concern in boardrooms.

Key CEO quote on the macro environment:

“We expect macro headwinds will continue with the potential for a recessionary environment across both the U.S. and Europe.” – Ian Broaden – Executive Vice President and Chief Financial Officer, McDonald’s, May 2, 2023

Key upcoming themes

(Generative) AI

Generative AI discussions, specifically around use cases and applications, continue to increase.
The mention of Generative AI experienced a significant increase of +129% in the last quarter, with 6% of discussions specifically referencing it. Additionally, the broader topic of AI was discussed in 21% of earnings calls (+21%), while the more technical term, “large language model” (LLM), saw a 229% increase in mentions, and was present in 1% of all earnings calls.

Banks

CEOs discussed banks more frequently in Q2 2023 (+36%). Following the banking turmoil involving several institutions including Silicon Valley Bank (SVB) and Credit Suisse in Q1 2023 companies discussed about a potential fallout as well as stricter lending regulations from some (regional) banks.

Key CEO quote on banks:

“We have seen a number of banks pulling back from auto lending, which is kind of a hallmark of banks through difficult markets, and that’s created a bit of a pricing opportunity for us, as well as improvement in share – financing share for us.” – Marion Harris – CEO, Ford Motor Company Credit Company, 02 May 2023

Reshoring

Discussions around reshoring increased by +30% in Q2 2023. 1.3% of all companies and 5% of industrial companies talked about the topic. Given the ongoing tensions between China and the USA, many US-based companies appear to prioritize enhancing the resilience of their supply chains, and some have concluded that bringing production closer to home is the solution.

Key CEO quote on reshoring:

“Reshoring continues to be a prevalent topic among our customers, and we expect near and longer-term benefits from this trend.” – Frank Dellaquila – CFO, Emerson Electric Co., 03 May 2023

Declining themes

Sustainability and climate change

Despite record temperatures around the world (e.g., temperatures in the North Atlantic Ocean increased to records highs), discussions on climate (-16%), emissions (-25%) and sustainability (-17%) experienced a decline in Q2/2023.

Supply chain disruptions

With supply chains slowly improving and supply shortages easing, discussions regarding supply chains in general (-19%), and supply chain disruptions (-54%) in particular, decreased strongly in Q2/2023.

Deep dives on select themes

#1 (Generative) AI

The release of ChatGPT by OpenAI in November 2022 ignited an unprecedented discussion about the use cases of generative AI in boardrooms. Generative AI was mentioned by 6% of all CEOs in Q2/2023 – a remarkable increase of +129%, compared to the previous quarter. Discussions have transitioned from specifically discussing the tool ChatGPT itself (mentioned by 3.7% in Q2, an increase of 28%) to actual enterprise-wide applications of generative AI. Moreover, an increasing number of CEOs also delved into technical details: The keyword LLM (large language models, the foundation for ChatGPT) was discussed by 1%, representing a substantial increase of +229% compared to the last quarter.

In Q2/2023, numerous companies started to roll out generative AI as part of their core product. For instance, the online flower shop 1-800-flowers.com launched MomVerse, an AI-powered poetry tool to assist individuals in expressing their love for mothers on Mother’s Day. E-commerce giant eBay has also started to use generative AI to support its marketplace sellers in composing suitable product descriptions. Lastly, travel company Booking Holdings has rolled out ChatGPT as a virtual travel assistant. These are just three examples of companies who are infusing generative AI into their business.

Unsurprisingly, the companies that talked most about generative AI in Q2/2023 were from the Technology sector (22.2% of all tech earnings calls) and Communication Services (22.1%). Consumer Cyclical (3.7%), Consumer Defensive (3.4%) and Industrials (2.8%) also had their fair share in debates.

When it comes to the various generative AI and LLM tools mentioned during these calls, OpenAI clearly dominates the field. OpenAI‘s ChatGPT accounted for over ~99% of the mentions among generative AI tools. Other tools such as Google’s Bard, Meta’s LLaMA or Aleph Alpha were only sporadically mentioned as examples.

Key CEO quotes on generative AI:

“With the emergence of generative AI capabilities, we moved quickly to create a fun and playful way to intertwine the emerging AI technology with our gift-giving experience. Just in time for Mother’s Day, we launched the 1-800-FLOWERS MomVerse.” – Chris McCann – Chief Executive Officer, 1-800-flowers.com, 11 May 2023

“Generative AI has a number of exciting use cases outside of descriptions, and we’re exploring numerous potential applications across our marketplace that can enable truly magical customer experiences.” – Jamie Iannone – CEO, eBay Inc, 26 April 2023

“There are current challenges given that current LLMs sometimes produce inaccurate outputs. Nevertheless, we are excited to be exploring how we can make use of these technologies for the benefit of our customers. Some of our brands, like KAYAK and OpenTable, are experimenting regenerative AI plug-ins, while others are building ways to integrate the technology into their own offerings.” – Glenn Fogel – President and Chief Executive Officer, Booking Holdings, 4 May 2023

“We are in advanced stages to apply generative AI across our portfolio, and we are working as an early release partner of OpenAI and together with other vendors. We are planning to announce new disruptive AI use cases.” – Christian Klein – CEO, SAP SE, 21 April 2023

#2 Supply chains

Long lead times and strained supply chains have been a persistent concern for CEOs. We previously highlighted supply chain disruptions as a prevalent topic of discussion, such as in our Q4 2022 analysis, or Q3 2021 analysis.

In Q2 2023, supply chain disruptions were mentioned in 4% of all earnings calls. That is a decrease of -54% compared to Q1 2023. The tone of these discussions has shifted, as many companies now discuss how they have successfully overcome these disruptions and managed the challenges. Although the Global Supply Chain Pressure Index has receded back to pre-pandemic levels, not all earnings calls mirror that sentiment, with some companies still grappling with longer-than-desired lead times.

Key CEO quote on supply chains:

“We have seen now that the supply chain disruption has normalized, and we will see that the inventory level will decrease starting actually in Q3 of this year.” – Yves Mueller – Hugo Boss AG, 4 May 2023

“Last 2 or 3 years have seen extreme swings on inventory up and down, given the supply chain disruptions which we all faced in the industry. I think we now see more normalized trade inventory levels. And from what we see across the board, most trade inventory levels in the Q1 were pretty much normalized.” – Marc Bitzer – Chairman and Chief Executive Officer, Whirlpool Corporation, April 25, 2023

“Our inventories will remain high throughout the year also to preserve our agility in a context where the fluidity of the supply chain is not yet fully restored.” – Antonio Picca Piccon – Chief Financial Officer, Ferrari N.V., 4 May 2023

#3 Climate change

In 2023, global temperatures have risen by 1.1 °C from pre-industrial levels, and news regarding climate-related catastrophes continues to make headlines regularly (e.g., major floodings in Pakistan, record heat in the North Atlantic or severe droughts in the western Mediterranean).

Our analysis reveals a significant increase in discussions related to climate and sustainability during earnings calls from Q1 2019 to Q1 2021. However, since then, the prevalence of these topics has leveled off or even experienced a slight decline. In Q2 2023, 20% of CEOs discussed sustainability (-17% compared to the previous quarter), and 11% focused on the climate (-16%) during their earnings calls.

Economic uncertainty and the emphasis on AI use cases seem to have sidelined the sustainability and climate topic. Amazon, for example, quietly gave up parts of its climate pledge recently. Additionally, several companies, including Yamaha (as seen below), have acknowledged falling short of their previously set targets.

On a positive note, numerous vendors offering sustainability-related products are experiencing significant adoption. Microsoft and Siemens, for example, highlight the considerable customer demand for sustainability-related products.

Key CEO quote on climate and sustainability:

“Our Cloud for Sustainability is seeing strong adoption from companies in every industry, including BBC, Nissan and TCL as they deliver on their respective environmental commitments.” – Satya Nadella – Chairman & CEO, Microsoft Corporation, Apr. 25, 2023

“We are in the sweet spot with automation and digitalization and in particular, with the sustainability offerings we have for our customers to help them transitioning in their business models.” – Ralf Thomas – CFO, Siemens AG, May 17, 2023

“As for the sustainability efforts, in fact, we have made greater progress in some of the areas, but the sustainable timber usage ratio was affected by the change in the model mix. So, we have not achieved much numerical results to mention yet.” – Takuya Nakata, CEO, Yamaha Corporation, 9 May 2023

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IoT Analytics published the Q1/2023 update of their “Global Cellular IoT Module and Chipset Market Tracker & Forecast” – an interactive dashboard and structured market tracker that includes quarterly data on worldwide cellular IoT modules and chipsets from 2018 to Q1 2023, and forecast data from Q2 2023 to 2027.

KEY QUOTES:

Satyajit Sinha, Principal Analyst at IoT Analytics, comments:

“The cellular IoT module market experienced a decline in Q1 2023, due to cautious end-user spending, device makers reducing inventory, and the ongoing semiconductor chip shortage. The slow recovery of the Chinese market and global uncertainties have significantly impacted the market. However, this Q1 market weakness is seen as a bump in the road, with more than 6 billion cellular IoT connections expected by 2027, driven by various sectors and the emergence of 5G technologies.”

KEY INSIGHTS:

• In Q1 2023, global cellular IoT module revenue declined 6% YoY; shipments declined 16%.
• The key reasons for the decline are: 1. Cautious end-user spending; 2. Inventory reductions; and 3. Chip supply issues.
• The top five cellular IoT module companies—Quectel, Fibocom, Telit Cinterion, Sierra Wireless, and LG Innotek—currently account for 66% of the global market.
• The Q1 market weakness is seen as a bump in the road, with six billion cellular IoT connections expected by 2027, driven by various sectors and the emergence of 5G technologies.

Global cellular IoT module market declined 6% in Q1 2023 in a weakening demand environment

The Cellular IoT Module Market: Overview

This month, IoT Analytics updated the in-depth Global Cellular IoT Module and Chipset Market Tracker & Forecast, which provides a quarterly look at the revenues and shipments of the companies providing IoT modules and chipsets for cellular IoT deployments.

According to the latest data, the market declined 6% in Q1 2023 on a revenue basis and 16% on a shipment basis (year-on-year). It is important to note that the cellular IoT module market only accounts for roughly 3% of the global IoT enterprise market, so the impact this segment has on the total IoT market is limited. Yet, it is an indication that the general IoT market weakened in Q1 2023. Earlier this year, we forecasted IoT enterprise spending to grow 19% in 2023.

The decline in the cellular IoT module market in Q1 can be attributed to three main factors:

1. There has been cautious end-user spending on the back of economic uncertainties.

Spending for IoT connectivity modules has slowed on the back of budget constraints in a globally uncertain economic environment characterized by high inflation, trade tensions, political instability, and post-pandemic ripple effects in China. Our data show that the retail industry and the Eastern Europe regions are the biggest reasons for the Q1 decline.

“The primary reasons for this decline were the slow recovery of the Chinese market and uncertainties in the global market.” – – Quectel, Q1 2023 financial results

2. Device makers are reducing their inventories.

In response to the economic uncertainties and fluctuating market conditions, device makers that build IoT modules into their products have focused on reducing costs and managing inventory more efficiently. As these companies deploy a lower-inventory strategy to avoid overstocking and minimize costly excess inventory, orders are getting delayed and order quantities get reduced. This has decreased demand for cellular IoT modules.

“Some of our customers pushed out orders to later this year due to their inventory stock levels.” – A cellular IoT module company, Q1 2023

3. A few companies are still facing a shortage of semiconductor chips.

Although lead times for most standard semiconductors have improved steadily since the peak in early 2022, these lead times remain elevated and particularly high for specific chips, particularly in the automotive industry, e.g., vehicle-to-everything (V2X) connectivity modules. LG Innotek, Adient, Cars.com, and Group 1 Automotive are some of the companies that highlighted the chip shortage in their investor reporting in Q1 2023.

“We are experiencing weaker demand and ongoing tightness in the semiconductor chip supply.” – LG Innotek, Q1 2023 financial results

Competitive landscape of the top five cellular IoT module companies

The top five cellular IoT module companies (based on revenue)—Quectel, Fibocom (including Rolling Wireless), Telit Cinterion, Sierra Wireless, and LG Innotek—account for 66% of the global cellular IoT module market in revenue. Recently, #2 Fibocom and #3 Telit Cinterion boosted their positions in the global ranking due to M&A activities in the space.

Here are some of the Q1 highlights from the top 5 vendors:

1. Quectel: As the market leader in shipment and revenue, Quectel experienced an 11% YoY decline in cellular IoT module revenue, a higher YoY decline than in Q4 2022. According to the company, the primary reasons for this decline were the slow recovery of the Chinese market and uncertainties in the global market.

2. Fibocom: Fibocom completed its full acquisition of Rolling Wireless at the beginning of 2023. This acquisition was the key driver for its cellular IoT module revenue growth, which increased by more than 40% YoY in Q1 2023. The acquisition also expanded Fibocom’s portfolio scope in the automotive, FWA, and other mobility industry verticals.

3. Telit Cinterion: Established in early 2023 as a result of the merger between Telit and Thales’s IoT module unit, Telit Cinterion holds third position in cellular IoT module shipment and revenue. Since it is a newly formed entity, there are no benchmarks for comparing its growth or decline.

4. Sierra Wireless: Semtech completed its full acquisition of Sierra Wireless at the beginning of 2023. Sierra Wireless secured fourth position, but its cellular IoT revenue declined by 25% YoY due to lower market demand.

5. LG Innotek: As a pure automotive communication module provider, LG Innotek ranks fifth with a 5% share of global cellular IoT revenue. The company’s cellular IoT module revenue declined by 6% quarter-on-quarter due to weaker demand and ongoing tightness in the semiconductor chip supply.

Outlook for the broader cellular IoT market

According to IoT Analytics’ Global Cellular IoT Connectivity Tracker & Forecast (Q2/2023 Update), the cellular IoT market grew 27% in 2022. The market is expected to continue to grow significantly, reaching more than 6 billion connections by 2027. Various sectors, such as intelligent metering, transport, supply chain management, logistics, and automotive telematics, drive this growth.

Technology innovation also plays a key role for market growth.

The following three key technology trends are visible:

1. 5G coming up : 5G and 5G Recap technologies are expanding their footprint in the market. 5G shipments, for example, are expected to account for 12% of global cellular IoT modules by 2027. Fixed Wireless Access (FWA) and Automotive CV2X are major use cases for 5G technology.

2. New LPWA cellular modules threatening incumbents : New LPWA cellular modules from MCU-based companies such as ST Microelectronics and Renesas compete with traditional cellular module players such as Quectel or Fibocom. MCU players promise better scalability, reduced bill of materials (BoM), and accelerated time-to-market while maintaining full control over the supply chain.

3. The rise of 3GPP-based satellite connectivity : The implementation of 3GPP-based satellite connectivity is becoming increasingly popular, with major chipset manufacturers such as Mediatek, Qualcomm, and Sony Semiconductor showcasing their latest developments in this area. Sony Semiconductor already launched ALT1350, the first cellular IoT LPWA chipset to offer satellite connectivity, which opens up new possibilities for IoT devices to communicate beyond traditional network boundaries. This integration of satellite connectivity into LPWA chipsets is expected to drive further innovation and growth in the IoT market.

The post Global cellular IoT module market declined 6% in Q1 2023 appeared first on IoT Business News.

IoT Analytics, today published insights on the enterprise IoT market, including a new market evaluation, spending outlook, and a discussion of common IoT vendor strategies.

KEY QUOTES:
Knud Lasse Lueth, CEO at IoT Analytics, comments:

“The IoT is evolving. Software for example is becoming a more important part of the IoT stack, more specifically IoT applications. AI is also starting to play a bigger role. We are observing that IoT vendors deploy 5 distinct strategies for “winning” in this changing IoT market. The partner ecosystem for example is becoming a crucial element in any IoT vendors’ go-to-market and IoT delivery.”

KEY INSIGHTS:

• IoT enterprise spending reached $201 billion in 2022, significantly lower than many had previously predicted.
• IoT adopters will focus on building the IoT software backbone, developing IoT applications, and infusing AI in the coming five years. 47% of IoT applications are expected to have an AI element by 2027.
• Five things vendors focus on as they evolve their IoT strategies: ecosystem, solutions; AI vision; acquisitions; and open standards.

In 2017, BCG published a much-cited and discussed analysis, asking: “Where are the growth opportunities in enterprise IoT?” The authors discussed the growth opportunities along the IoT tech stack from 2015 to 2020. The conclusion: The top layers of the tech stack (services, applications, and analytics) will grow the fastest between 2015 and 2020 and will see the highest spending.

Today, six years later, we wonder: How accurate was the assessment by various industry analysts back then, and what does it take to win in a changing enterprise IoT market between 2023 and 2027?

Evaluating the IoT market vs. past predictions

According to our January 2023 IoT market update, IoT enterprise spending reached $201 billion in 2022, up from below $100 billion in 2018. For comparison, this represents roughly 5% of the global IT market in 2022. While we had to lower the outlook for the forecast period of 2023–2027 in our January 2023 update, the market is still expected to grow by +19% annually and reach $483 billion in spending by 2027.

The IoT market is expected to reach $483 billion by 2027

The number of global active IoT connections grew by 18% in 2022 to 14.4 billion active IoT endpoints. In 2023, IoT Analytics expects the global number of connected IoT devices to grow another 16% to 16.7 billion. While 2023 growth is forecasted to be slightly lower than it was in 2022, IoT device connections are expected to continue to grow for many years to come.

How accurate were industry predictions in 2017?

We compare our market tracker that is based on actual revenues of 170+ companies in the IoT market to industry predictions of several third-party data providers that were cited by BCG in its 2017 article.

Our verdict: Industry predictions were directionally correct but too bullish on the pace of IoT adoption and on how fast different technology categories would shift.

1. Total market size

• Industry prediction for 2020: $250 billion
• IoT Analytics IoT spending tracker: $136.6 billion. According to our estimates, the IoT market came out 45% lower than estimated. The market grew substantially in the 2015-2020 time frame but did not explode as had been projected by many (some segments, such as services, had been forecasted to grow 40%+ every year).

2. Tech stack changes:

• Industry prediction for 2020: Services, applications, data analytics, and software platforms would substantially outgrow other parts of the tech stack.
• IoT Analytics IoT spending tracker: According to our data, this did happen. However, data analytics, applications, and services captured 39% of the market in 2020 and not 60% as forecasted by some data providers.

3. Segment changes:

• Industry prediction for 2020: Discrete manufacturing, utilities, and logistics would make up the largest share of the market.
• IoT Analytics IoT spending tracker: Our data also show these three segments as being among the largest, but our view is that discrete manufacturing is even bigger than predicted.

Although we believe that general industry predictions (including our own predictions) were too bullish, we do see strong evidence that the market is growing further and now believe that the projected 2020 IoT market size of $250 billion will be surpassed at some point in 2024.

The IoT market in 2023 and beyond

IoT technology in 2023 adds value to organizations in all verticals, from manufacturing (e.g., factories) to retail (e.g., warehouses) and transport (e.g., cars). The IoT market has moved past headlines such as the infamous “3/4 of all IoT projects fail” (Cisco 2017).

87% of all IoT projects meet or exceed expectations

In 2023, 87% of all IoT projects met or exceeded expectations, based on a 2023 survey of 300 IoT decision-makers that will be published in an upcoming IoT Analytics adoption report. Some companies have connected millions of connected IoT devices (e.g., Walmart, Tesla, and Hapag-Lloyd) and are looking to expand with more sophisticated software tools. Despite several key challenges remaining related to interoperability, skills and know-how, and chipset supply, companies do not question if they should do IoT but rather how it will be scaling from here.

IoT technology maturity framework

To understand how the IoT tech stack is changing and where the growth opportunities in IoT are going forward, one needs to consider a typical technology-focused maturity curve an IoT adopter goes through:

Stage 1: Enabling the asset

In the first stage, whether it is a smart washing machine, a heavy asset in a factory, or a ship at sea, companies need to invest in sensors and local controllers/gateways to be able to process IoT data. Despite a renewed edge computing investment cycle that is seeing many companies invest into more powerful and flexible hardware, many companies at this point have passed the first hurdle of ensuring they have basic IoT data to work with. We expect the spending for IoT hardware/devices to be the lowest growth category at 14% until 2027.

Stage 2: Establishing connectivity

In the second stage, enterprise end users establish and simplify the connectivity to their IoT hardware. While some technologies used have been around for decades (e.g., certain field buses), companies in recent years have invested heavily into higher bandwidth connectivity (like ethernet), wireless connections (e.g., 4G/5G and LPWAN), and more modern and lightweight protocols (e.g., OPC-UA and MQTT). Spending on connectivity is expected to grow by 18% until 2027.

Stage 3: Creating the software backbone

Data normalization and analysis are key to the third stage of IoT maturity. Companies invest in the software backbone that allows them to access various IoT data sources and build valuable services, e.g., using cloud storage and platform services, centralized data lakes, containerization, and modern databases. Many companies are currently in a major investment phase in this part of the maturity curve. That is why we expected spending related to IoT Platforms and middleware to grow 30% and 34% for Infrastructure as a Service (IaaS) until 2027.

Stage 4: Building value adding IoT applications

In the fourth stage of IoT maturity, IoT end users build cloud native or edge-based applications that make use of IoT data at scale. The ability to connect to any asset (stage 1) in a standardized fashion (stage 2) and having those data easily accessible (stage 3) enables a number of IoT use cases. Some of the early innovators (e.g., several automotive OEMs) have reached this stage and are building all kinds of internal (e.g., for their factories) and external (e.g., for their cars) IoT applications. We expect more companies to reach this stage of maturity in the coming years, which is why we expect the spending on IoT applications to exhibit a CAGR of 29% until 2027.

Stage 5: AIoT = infusing AI into IoT

Enabling business with AI is the fifth stage of IoT maturity. This is where companies explore ways to augment existing applications and build new applications by embedding AI. Machine vision and predictive maintenance are two of the most common AI-enabled IoT use cases today. Recent breakthroughs in generative AI may add a new dimension and are a driver for companies to rapidly adopt AI further.

The shift toward AIoT: Nearly half of all IoT applications to be AI-infused by 2027

Although some companies are still struggling to enable their assets (stage 1) and establish connectivity (stage 2), the future of IoT is the convergence of AI and IoT, also often referred to as AIoT.

The future of IoT is the convergence of AI and IoT

In 2022, we conducted a survey of 500 senior IT and engineering staff at manufacturing companies. 15% of those companies indicated having fully implemented their AI strategy (results are part of the Industry 4.0 Adoption Report 2022). Two key use cases with an AI component that were cited were machine vision and predictive maintenance, both scoring a consistently high ROI for these companies.

Based on the data we have and the discussions we lead with various organizations, we estimate that approximately 6% of IIoT applications today are AI-based, meaning that AI algorithms play a core role in enabling the use case (i.e., when using machine learning for vision detection in quality control). Another 11% of applications are classified as AI-augmented, meaning that AI does play a role for the use case, but the use case is not dependent on that AI functionality (e.g., AI-augmented AGV/AMR routing instead of using rules decided by operators).

We see a strong push toward embedding AI into IoT applications (e.g., by moving from condition monitoring to predictive maintenance) and expect a strong increase in the next years.

By 2027, we forecast nearly half of all IIoT applications to have some AI element with the share of AI-augmented applications tripling in that time frame (from 11% to 34%). Many software vendors are currently undergoing large internal exercises on how they can augment their existing software offerings with the use of AI. In May 2023, for example, SAP announced 15 new business AI capabilities across the existing ERP product portfolio, including nine new generative AI scenarios.

Not everything is required to be AI-based, however. Many legacy non-AI IoT applications that are already deployed may not be touched. Many rule-based applications will remain sufficient for some clients and uses cases, and not every dashboard will need to be AI-augmented.

The hype around ChatGPT and Generative AI is likely to impact the AI strategy of companies in the coming years. It is still early to tell if and how quickly the implementation of generative AI in IoT will lead to new large-scale use cases. Generative AI models predominantly focus on text and images, with only a few models centered around sensor data at this point.

Ravi Kumar, CEO, Cognizant, 2 February 2023: “We see a strong push now to bring AI into the business landscape, with the expectation that AI will reengineer enterprises as completely as enterprise software did three decades ago.”

Winning in IoT: How vendors are positioning themselves

With users more focused on building the software backbone, developing applications, and infusing AI, the combined IoT software opportunity is expected to amount to $193 billion by 2027. In 2022, no single vendor had more than 3% market share in the $201 billion global IoT market, and no single vendor had more than 9% market share in the IoT software market. (Note: IoT Analytics tracks 170+ vendors and their market share by IoT segment—see the most recent update of the IoT Enterprise Spending Dashboard.)

No single vendor has more than 3% market share in the IoT market

IaaS (top three vendors: 86% market share) and wireless connectivity (top three vendors: 44% market share) are the only IoT tech stack elements that are largely consolidated at this point—the other areas leave plenty of room for innovation and consolidation.

Here are examples of some of the strategies that leading IoT vendors are pursuing as they gear up for the next five to ten years in the IoT market:

Strategy 1: Multiplying the opportunity by building a strong ecosystem of partners

The complexity of IoT has led some of the leading organizations to build an ecosystem of complimentary partner companies to help in their go-to-market and delivery. This strategy is most notable with the leading hyperscalers Microsoft, AWS, and Google.

For example, at Hannover Messe 2023 (the world’s leading industrial fair), we counted 35 partners co-exhibiting with AWS, 25 with Microsoft, and 24 with Google (see our Hannover Fair event report for more details). Although these companies are technically also customers of the hyperscalers, significant time and resources go into developing joint solutions, building architectures together, and marketing the joint offerings. AWS, for example, marketed joint solutions with Element Unify, HighByte, Deloitte, and TensorIoT at the fair.

Strategy 2: Focus on solutions that solve customer problems

A few years ago, many vendors focused on selling a platform that would allow IoT adopters to build applications themselves. However, many IoT adopters, especially SMEs, have found that they do not have the resources to make this happen. Some of the vendors that previously provided an IoT platform have adjusted accordingly and moved on to providing IoT solutions to individual problems and use cases, rather than a universal, hard-to-maintain platform. In some cases, these solutions bundle existing hardware or sensors with access to cloud-based software so that IoT adopters can receive everything they require from one vendor.

For example, in 2022, Swedish sealing and bearing company SKF launched SKF Axios, a wireless predictive maintenance solution geared toward monitoring equipment and improving equipment uptime. The solution leverages several AWS cloud services and provides necessary sensors, gateways, wireless connectivity, and a ready-to-use application so that customers have the entire solution ready to go.

Strategy 3: Embedding a bold AI vision into the strategy

As the IoT enterprise market is starting to look at the fifth stage of maturity (AIoT), some vendors appear to be bolder and more committed to leading the AI race than others.

For example, Japanese industrial automation vendor Yokogawa is building the vision of industrial “autonomous operations” into the company strategy, believing that the future of manufacturing is AI-based. In March 2023, Yokogawa announced the adoption of Yokogawa’s Autonomous Control AI at an ENEOS Materials Chemical Plant. The field test demonstrated that AI could control distillation operations more effectively than existing human-controlled approaches, resulting in stable product quality, high yield, and energy savings.

Strategy 4: Acquiring missing puzzle pieces

Rather than partnering, some companies opt to acquire certain IoT technologies or applications that they consider high value.

In May 2022, for example, Emerson Electric acquired Aspen Technology to create a leading industrial software company. The acquisition, among other things, gives Emerson Electric access to a strong Industrial AI portfolio, including numerous asset intelligence solutions.

In June 2022, Siemens acquired Senseye, a provider of AI-powered solutions for industrial machine performance and reliability.

As part of our recent State of IoT—Spring 2023 report, we looked at the 100 most recent acquisitions in the IoT space. We found that the largest group (26%) of acquired companies was in the applications space—many with a strong AI footprint.

Strategy 5: Betting on open standards

Open standards promise to solve one of the biggest inhibitor to large scale IoT adoption: Missing interoperability and compatibility among various IoT devices and systems.

By aligning their solutions with open standards, vendors hope to significantly improve the customer experience, fostering innovation, flexibility, and scalability in their IoT deployments.

Schneider Electric, for example, is actively promoting the use of IEC 61499, a shared source runtime execution engine, developed by Universal Automation. The standard aims to create hardware-independent applications to bridge the existing gap between IT and OT.

In our Hannover Messe 2023 event report, we highlighted that we noticed several big brands aligning behind the Asset Administration Shell (AAS) framework to develop interoperable digital twins. Among many companies, Microsoft, Siemens, and SAP seem to be three of the most notable supporters.

Conclusion

IoT continues to offer tremendous opportunities, even if the market is not advancing as fast as some had predicted in the past. IoT enterprise spending is expected to increase to $483 billion by 2027. In a maturing IoT market, the biggest growth opportunity lies in the software, especially with (AI) applications.

The biggest IoT growth opportunity lies in software

Nearly half of all applications in 2027 will be AI driven. Leading IoT vendors, such as hyperscalers, industrial automation vendors, and connectivity providers, and also many start-ups position themselves to stay relevant in an AI-first IoT market. With a clear IoT strategy, companies have an opportunity to position themselves in what remains one of the biggest market opportunities of our generation.

The post Winning in IoT: The evolving IoT market appeared first on IoT Business News.

IoT Analytics today published its State of the IoT-Spring 2023 report on the current state of the Internet of Things including market update and forecast, latest trends, and more.

KEY QUOTES:

• Knud Lasse Lueth, CEO at IoT Analytics, comments:
  

  “Despite general economic uncertainty, the state of the IoT market right now remains predominantly positive. Industrial IoT projects and Industry 4.0 in particular stand out as driving forces in the current market environment. On the flipside we have recently seen IoT-related layoffs in the IT industry and we also do see that investment flows into IoT-focused start-ups has declined significantly.”

• Satyajit Sinha, Principal Analyst at IoT Analytics, adds: “As we look towards the future of IoT connectivity, two trends are noteworthy. The first is the convergence of LPWAN technologies, shifting the industry towards a multi-connectivity solution view. This shift will likely lead to new multi-LPWAN connectivity modules, providing end-to-end connectivity in verticals such as logistics and mobility. The second trend is the growing popularity of LEO-based satellite IoT connectivity, which offers extensive coverage, minimal delays, and strong reliability. With satellite IoT connections expected to grow at a CAGR of 25%, integrating satellite connectivity options into LPWA chipsets is expected to drive further innovation and growth in the IoT market.”

IoT connections market update—May 2023

The latest IoT Analytics “State of IoT—Spring 2023” report shows that the number of global IoT connections grew by 18% in 2022 to 14.3 billion active IoT endpoints. In 2023, IoT Analytics expects the global number of connected IoT devices to grow another 16%, to 16 billion active endpoints. While 2023 growth is forecasted to be slightly lower than it was in 2022, IoT device connections are expected to continue to grow for many years to come.

IoT connections forecast

According to our analysis, by 2027, there will likely be more than 29 billion IoT connections. Compared to our last IoT device market update a year ago, we lowered our five-year IoT market outlook for two important reasons:

1. Chipset supply to remain constraint for years to come in the face of surging demand

Chipset supply chains have considerably improved in 2023 as demand has weakened in the face of a slowing economy. Despite the demand slump, current chip lead times remain elevated compared to pre-COVID-19 levels. We believe that once the economy recovers and a new demand wave kicks in, chipset supply will become much more constraint again. While it is true that a lot of chip manufacturing capacity is being planned as we speak, fueled by government initiatives such as the US Chip and Science Act (2022) and the EU Chips Act (2022), it may take many years until supply matches or surpasses demand for the majority of different types of chipsets.

Make no mistake, the investments into new chip manufacturing capacity are enormous. TSMC has increased its capital expenditure from approximately $15 billion in 2019 to $42–$44 billion in 2022. Similarly, in 2023, Samsung announced that it plans to invest $230 billion in South Korea over the next 20 years to build new chip production capacity. However, these investments take time to materialize. Semiconductor plant constructions typically take three to four years to complete, and it can take another three to four years for facilities to reach full capacity.

2. China uncertainties

In the last years, China was the leading country for new IoT device connections, with active cellular IoT connections in China alone surpassing two billion in 2022. However, the high growth years may be coming to an end with the country facing a number of issues, including technological supply shortages on the back of renewed US–China trade tensions, most notably in the semiconductor industry. In October 2022, the US placed an export ban on China, causing significant disruption to these industries. Consequently, chip companies are relocating their facilities outside of China. Some companies, such as Infineon, TSMC, AMAT, and ASML, have announced that they are moving parts of their production out of China.

The leading IoT connectivity technologies: three technologies making up nearly 80% of the market

Global IoT connectivity is dominated by three key technologies: Wi-Fi, Bluetooth, and cellular IoT.

1. Wi-Fi. Wi-Fi makes up 31% of all IoT connections. In 2022, more than half of Wi-Fi-enabled devices shipped worldwide were based on the latest Wi-Fi 6 and Wi-Fi 6E technologies, which promise faster and more reliable wireless connectivity. The adoption of these technologies has made communication between IoT devices more efficient, leading to improved user experiences and overall performance. Wi-Fi technology is leading IoT connectivity in sectors such as smart homes, buildings, and healthcare.

2. Bluetooth. 27% of global IoT connections rely on Bluetooth. Bluetooth Low Energy (BLE), also known as Bluetooth Smart, has been continuously developed to allow IoT devices to maintain reliable connectivity while consuming limited power. As a result, BLE is now the preferred option for battery-powered IoT devices such as smart home sensors and asset tracking devices. Even the industrial sector is starting to show increasing interest in IO-Link Wireless technology, which is based on IEEE 802.15.1 (the technical standard for Bluetooth) and allows for wireless communication between sensors/actuators and an I/O master.

3. Cellular IoT. Cellular IoT (2G, 3G, 4G, 5G, LTE-M, and NB-IoT) now makes up nearly 20% of global IoT connections. According to the Global Cellular IoT Connectivity Tracker & Forecast (Q1/2023 Update) by IoT Analytics, global cellular IoT connections grew 27% YoY in 2022, strongly surpassing the growth rate for global IoT connections. This growth is due to the adoption of newer technologies such as LTE-M, NB-IoT, LTE-Cat 1, and LTE Cat 1 bis, as older technologies such as 2G and 3G are phased out. Although 5G module shipments also grew more than 100% YoY in 2022, the growth rate is still slower than many had expected. In 2023, the top five network operators—China Mobile, China Telecom, China Unicom, Vodafone, and AT&T—managed 84% of all global cellular IoT connections. In terms of IoT revenue, the top five network operators make up 64% of the IoT network operator market, with China Mobile, AT&T, Deutsche Telekom (including T-Mobile), China Unicom, and Verizon leading the market.

The analysis shows a few notable shifts over the years, for example:

I. China Mobile jumped from fifth place in 2012 to first place in 2021 and is expected to remain there in the foreseeable future.
II. AT&T, Verizon, and Deutsche Telekom have consistently ranked in the top five from 2010 to 2022 and are expected to maintain their positions through 2027.
III. China Unicom joined the top five in 2022 and is projected to remain among the leading network operators through 2027.

IoT connectivity trends to look out for

While the general IoT connectivity landscape only changes slowly (e.g., some devices remain connected for a decade or even longer), new IoT connectivity technologies do have an impact on the landscape in the long run. Here are two interesting developments we are monitoring (for more also visit our Embedded World conference 2023 takeaways and our MWC 2023 takeaways):

1. LPWAN technology convergence

In 2022, the LPWAN industry saw two significant events that shifted the focus from competition among LPWAN connectivity technologies to co-existence and convergence of those technologies. UnaBiz‘s acquisition of Sigfox and Semtech’s acquisition of Sierra Wireless paved the way for LPWAN companies to provide multi-connectivity of several LPWAN technologies at the same time. To make this convergence happen and be able to deploy any LPWAN technology, UnaBiz, for example, now collaborates with The Things Industries, Actility, Soracom, LORIOT, and others. This means that UnaBiz has become more than just a technology provider but rather a solution provider that also bundles all different technologies and orchestrates them on their own software platform. UnaBiz is just one example that shows how the industry is shifting from a single LPWAN technology view to a multi-connectivity solution view.

We anticipate that this LPWAN convergence may lead to the emergence of new multi-LPWAN connectivity modules in the future that would provide end-to-end connectivity in verticals such as logistics and mobility.

2. LEO-based satellite IoT connectivity

LEO satellite connectivity for IoT is gaining popularity because it provides extensive coverage, minimal delays, and strong reliability. The technology is especially useful in the agriculture, maritime, and logistics industries. LEO satellites are closer to Earth than traditional satellites, resulting in reduced latency and faster data transmission, which are essential for real-time data processing. This type of connectivity is more resilient and reliable, ensuring consistent communication, even in challenging environments or during natural disasters. Advancements in LEO-based IoT satellite connectivity continue to optimize performance and enhance the user experience.

According to IoT Analytics, satellite IoT connections are expected to grow from six million to 22 million between 2022 to 2027, at a CAGR of 25%. While this growth is expected to have a minor effect on the overall market, the integration of satellite connectivity options into LPWA chipsets by companies like Qualcomm could accelerate adoption. Sony Semiconductor already launched ALT1350, the first cellular IoT LPWA chipset to offer satellite connectivity, which opens up new possibilities for IoT devices to communicate beyond traditional network boundaries. This integration of satellite connectivity into LPWA chipsets is expected to drive further innovation and growth in the IoT market.

Other State of IoT (Spring 2023) research highlights

The 137-page report highlights a number of current developments in the IoT market. Here are three developments that are discussed in more depth in the report:

1. Predominantly positive IoT sentiment going into the second half of 2023

Despite a number of macro uncertainties and some (IoT-related) layoffs, the IoT market remains largely intact going into the second half of 2023. Most market participants have a predominantly positive outlook, with industrial IoT projects and Industry 4.0 initiatives driving the market. Below are some recent representative quotes from chip companies with a focus on IoT:

“We continue to secure major greenfield design wins, even amid macro uncertainty. The IoT market has incredible potential, with thousands of new applications on the horizon.” – Matt Johnson – President & CEO, Silicon Laboratories (1 February 2023)

“The industrial IoT markets are performing better than our expectations.” – Kurt Sievers – President & CEO, NXP Semiconductors (31 January 2023)

2. IoT platforms market is consolidating

Several major companies that were selling IoT platforms recently announced discontinuations, including Google’s IoT Core, Bosch‘s IoT Device Management, IBM’s Watson IoT Platform, and SAP’s IoT services. The reasons for the strategic shift away from IoT vary. The market dominance of Microsoft Azure IoT and AWS IoT in “generic” IoT platforms certainly played a role, in conjunction with the “the lack of profitability” in the offered IoT services. Several of these companies have announced a shift toward creating solutions specific to particular verticals or relying more on a few select partners to continue to support IoT initiatives (e.g., Google–Litmus Automation partnership).

“IoT services themselves don’t make enough money. The services like AWS IoT Core and Azure IoT Hub are expensive to build and maintain and by themselves they are likely not profit-making.” – Former IoT Product Lead, Microsoft

3. IoT-focused start-ups are struggling to secure funding

The amount of money invested in global IoT start-ups decreased significantly in the last 12 months. In the first quarter of 2023, we tracked 52 IoT-related funding rounds totalling $840 million, a 45% reduction in the value of investment in IoT start-ups companies compared to Q1/2022. Some of the larger recent IoT-related funding rounds include a $150 million Series D for US-based chipset manufacturer Astera Labs in November 2022 and a $43 million Series C for China-based connectivity chipset company XINYI Information Technology in March 2023.

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IoT Analytics, a leading global provider of market insights and strategic business intelligence for the Internet of Things (IoT), AI, Cloud, Edge, and Industry 4.0, published its IoT Software Adoption Report 2023 based on an extensive survey of 100 software end users in manufacturing, real estate, retail, and other industries.

This article details the IoT software landscape and lists 8 of the leading IoT software companies in 2023 highlighted by survey participants.

Key insights:

• IoT software spending reached $53 billion in 2022 and continues to grow strongly.
• The latest IoT Software Adoption Report 2023 highlights the top 100+ IoT software vendors used today based on an extensive survey of IoT users.
• The most common IoT software companies include Microsoft, AWS, Siemens, IBM, Cisco, Oracle, PTC, and MongoDB.

Key quotes:

Knud Lasse Lueth, CEO at IoT Analytics, comments:

“We have seen quite some shifts in the IoT software landscape during the last five to eight years. Given where the market is now, with some large companies having recently exited the space while others are putting the foot on the gas, I would not be surprised to see several new, smaller players capture a significant portion of this fast-growing market in the coming years.”

The big picture: The IoT software market in 2023

IoT software spending reached $53 billion in 2022 (according to the IoT Analytics Global IoT Enterprise Spending analysis). The market grew a staggering 31% in 2022 because of renewed enterprise focus on IoT after the COVID-19 recovery; strong growth in the number of actively connected IoT devices to 14.4 billion worldwide; and a software technology replacement cycle causing companies to invest in containerized solutions, software-as-a-service, low-code user interfaces, and AI-enhanced software. With the number of active IoT devices projected to reach nearly 30 billion by 2027, IoT software market growth is guaranteed.

6 IoT software architecture choices

Companies pursue dozens of IoT use cases (examples include remote monitoring, predictive maintenance, and machine vision)—see our 2021 IoT use case analysis. Those use cases require software that can be realized in six ways. Companies can

1. Add their IoT devices to existing software (e.g., ERP, MOM, PLM, or SCADA)
2. Build IoT software in-house
3. Hire a third party to build IoT software
4. Use several open-source software components (e.g., Apache Kafka and Eclipse Mosquitto)
5. Buy IoT software components (e.g., platforms and middleware)
6. Buy entire IoT offerings

Option 1, adding to existing software, promises stability, reliability, and security. However, the past few years have shown that this approach has shortcomings, which have given rise to options 4, 5, and 6. For option 5 and 6, there are hundreds of commercial offerings that are specifically designed for IoT device data, do not come with the “baggage” of older enterprise architectures, and bring an element of scalability.

Our analysis focuses exclusively on companies that have chosen options 5 or 6.

The methodology of this analysis
IoT Analytics, in Q4 2022, surveyed 100 senior executives across manufacturing, real estate, retail, and other industries in North America, Europe, and Asia to better understand the IoT software market. All respondents procured and used IoT software. The vendors mentioned by the respondents are the basis for the IoT software companies’ landscape in this article. The accompanying 164-page IoT Software Adoption Report 2023 analyzes these companies’ spending patterns, adoption, decision-making criteria, payment habits, and much more. For more information, request a sample of the report here.

The IoT software stack

For this analysis, we divided the IoT software stack into four main components: applications, middleware/platforms, devices/edge, and security. Within these four components, we highlight 11 types of IoT software (although there could be more, especially in the IoT application layer):

1. Remote asset access software allows an asset to be controlled or monitored remotely on one system while being displayed on a separate client device.
2. Augmented reality or virtual reality software is used to visualize and create AR/VR.
3. Digital twin software is used to create and manage a virtual replication of a real-world entity.
4. IoT platforms are specialized software tools to build and manage IoT solutions.
5. Edge management platforms are used to provision and manage remote devices at the edge.
6. Databases for IoT datasets are used to capture the data produced by IoT devices.
7. Other IoT middleware tools enable one or more kinds of communication or connectivity among several applications or application components in a distributed network.
8. Data ingestion tools for shopfloor/operational assets gather and transfer structured, semi-structured, and unstructured data from the source to the target destinations.
9. Message broker/protocol conversion tools translate a message from the sender’s formal messaging protocol to the receiver’s formal messaging protocol.
10. IoT security software is cybersecurity software that focuses on increasing the security of IoT setups.
11. Operating system for IoT devices/assets is operating system software that manages IoT devices and software resources for connected products or machines in the field and provides common services for computer programs.

The IoT software landscape 2023

Many small companies

IoT Analytics tracks more than 1,000 large and small vendors offering software for IoT scenarios. Although two companies are clearly leading the market, the overall landscape remains fragmented. As verifying which vendor fits into which IoT software type is almost impossible, we decided to present a chart entirely created by IoT end-users from our survey (rather than a secondary research analysis). These are the IoT software companies our survey participants used, and from our point of view, it is a good view of the market even though several vendors are missing. Some vendors may feel they should also feature in another IoT software category.

Recent IoT software divestitures

The recent announcements of IoT software discontinuation by three heavyweights (Google, SAP, and IBM) have rattled the IoT community. Nevertheless, the results of this survey show that a significant number of users are still leveraging these to-be-retired services. Our view is that there is a natural market consolidation in IoT software, and more specifically in IoT platforms, that we started to report on in 2021. We know of more IoT software companies that are exiting the market, as their IoT visions have not materialized.

IoT software companies are doubling down on IoT

However, we are tracking many other thriving IoT software companies that are doubling down on a longer-term IoT vision. The survey results confirm there is no appetite to stop investing in IoT software on the end-user side, although the high growth for the IoT platform segment seems to be over and end-users are putting more money, for example, into individual applications. Due to the recent IoT divestitures, end-users are also becoming more careful about choosing their software vendor partner.

8 leading IoT software companies in 2023

Here is a look at 8 of the top IoT software companies that survey participants highlighted.

1. Microsoft

According to our estimates, Microsoft is the IoT software market share leader, with a 9% share of the market in 2022 (Source: IoT Analytics Global IoT Enterprise Spending dashboard—vendor market share view). Almost 60% of the respondents in this survey use Microsoft software as part of their IoT setups. Microsoft has an offering in all 11 of the analyzed IoT software types. Some of Microsoft’s most prominent IoT software solutions include Azure IoT Hub, Defender for IoT, Azure IoT Edge, and Azure RTOS.

2. Amazon Web Services

AWS is the global market-leading cloud provider and has made several IoT software investments since the launch of its IoT Core service in 2015. Survey respondents use AWS IoT software products in six of the 11 IoT software types. Prominent examples besides AWS IoT Core include AWS IoT Greengrass and Amazon DynamoDB IoT. As a result, we can expect AWS IoT software to continue to grow. The survey results show that users expect to continue to increase IoT software spending with AWS, particularly companies in North America and smaller and medium-sized companies.

3. Siemens

Even though the company has moved away from heavily marketing its Mindsphere IoT platform, Siemens continues to invest in IoT. Two of the main strategic initiatives for Siemens include the Siemens Xcelerator portfolio of modern cloud-based SaaS-based software offerings (including industrial IoT applications) and the new Industrial Edge offering (including several IoT applications). Like Microsoft and AWS, Siemens received a high customer satisfaction rating in this survey, consistent with previous IoT Analytics surveys on IoT and IoT-centric topics.

4. IBM

Despite the deprecation of the IBM Watson IoT platform announced in November 2022, IBM remains one of the leading IoT software vendors (for now). Due to the company’s strong penetration rate in enterprises, many companies have used IBM’s tools for their IoT setups. It will be interesting to see how the picture changes in 2024, as customers must move their IoT deployments off IBM Watson IoT by 1 December 2023.

5. Cisco

Cisco has been a player in the IoT software landscape for years. Some prominent IoT offerings include the Cisco Edge Intelligence platform and the company’s IoT security products (e.g., Cisco ISE).

6. Oracle

Oracle is an enterprise software powerhouse and a cloud hyperscaler (although much smaller than the market leaders). Oracle’s IoT setups include the Oracle IoT Cloud Service and Oracle databases (e.g., Oracle Database).

7. PTC

PTC has been executing its IoT vision since the acquisition of Thingworx in 2013. To date, ThingWorx remains one of the leading IoT platforms, but it is not the only IoT tool PTC has to offer. Other prominent PTC tools for IoT scenarios include Kepware (message broker/protocol conversion tool) and Vuforia (AR/VR).

8. MongoDB

MongoDB has established itself as the commercial IoT database of choice for many IoT setups. Moreover, the company is on an impressive growth path in the wake of general workload movements to the cloud: the company’s top line more than tripled during the last three years to more than $ 1 billion per year (IoT is a portion of that). In addition, our survey participants gave MongoDB a high satisfaction rating for their IoT offering.

Looking ahead

These are just 8 of the 100+ IoT software companies we analyzed as part of the research. Although some parts of the IoT software landscape are consolidating (as highlighted above), the landscape remains dispersed. Smaller vendors still have room to fill the gaps and find their niches. The technological shifts happening right now (e.g., more powerful edge computing, new protocols, cloud-native software development, and containers) provide tremendous opportunities for any company to jump in and offer a more modern and native software experience. We have seen quite some shifts in the software landscape during the last five to eight years, and given where the market is now, it will not be surprising to see several new, smaller players capture a significant portion of this fast-growing market in the coming years.

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