Global AI in IoT Market Size, Forecast, and Trend Highlights Over 2025-2037
AI in IoT Market size was valued at USD 78.7 billion in 2024 and is expected to cross USD 186.9 billion by the end of 2037, rising at a CAGR of 7% during the forecast period from 2025-2037. In 2025, the industry size of AI in IOT is assessed at USD 83.6 billion.
Cross-sector digitization mandates have bolstered the market’s growth as AI has emerged as a central requirement for IoT to deliver functionality that is context-aware to multiple industries. The market is transitioning steadily from pilot-scale applications to platform-scale deployments, reflecting a maturity inflection point. In terms of the supply chain, recent audits across sensor, semiconductor, and edge hardware ecosystems have showcased a cost-pressure mismatch. A key facet is the rising demand for AI accelerators such as ASICs and TPUs, whilst foundry capacity remains concentrated with more than 73% of advanced nodes of 5nm and below controlled by two major players. Additionally, trends highlight an increase in AI inference workloads pushed to edge nodes, especially in the sectors of energy and logistics.
To understand the market’s growth curve, it is essential to analyze the CapEx of the major players in the sector. The table below highlights the CapEx details of the leading players in the market:
|
Company |
2024 CAPEX (approx.) |
Key AI-IoT Infrastructure Focus |
|
Microsoft |
USD 50.2 billion+ |
Cloud + Edge AI for Azure IoT and industrial automation |
|
Alphabet (Google) |
USD 48.4 billion+ |
TPU infrastructure, AI edge services, smart city initiatives |
|
Meta (Facebook) |
USD 35–37 billion |
AI hardware, metaverse IoT, edge compute investments |
|
Amazon |
USD 54.6 billion+ |
AWS IoT Core, edge AI for Alexa & logistics optimization |
|
NVIDIA |
USD 3.6 billion+ |
AI chips (GPUs), edge inferencing modules, Jetson platform |
The industry analysis highlights that AI-IOT integration is embedded into mission-critical systems across four primary deployment zones, i.e., industrial edge nodes, smart infrastructure, consumer endpoints, and mobile ecosystems. Additionally, OEMs in process-heavy sectors such as petrochemicals, automotive, and mining are embedding AI at sensor level to bolster decision-making at the asset layer. The trends highlight the potential of the market.
AI in IoT Sector: Growth Drivers and Challenges
Growth Drivers
- Regulatory compliance frameworks accelerating secure AI-IoT deployment: A major catalyst of the global AI in IoT market is the evolving regulatory compliance frameworks. The mandates have ensured stringent data privacy and cybersecurity standards driving growth in the market. In 2024, the National Institute of Standards and Technology (NIST) AI Risk Management Framework highlighted that organizations are required to adopt risk-based AI governance models for IoT deployments. The increase in secure and compliant AI-IoT systems is bolstering market penetration and have accelerated adoption timelines. Additionally, enterprises with improved security and compliance with regulatory standards emerge as competitive differentiator by bolstering improved deployment in regulated sectors.
- Optimization of semiconductor costs improving AI-IoT scalability:
A major economic indicator of the sector's growth is the cost optimization of semiconductors. The cost reduction has proven to be critical for enterprises and has assisted in widespread deployment of AI-IoT in numerous sectors. In terms of factors optimizing costs, TSMC highlighted in its earnings report in the fourth quarter of 2024 that wafer production efficiencies had improved by over 17% due to advancements in chip stacking, which in turn has lowered the unit cost of AI accelerators that are deployed in edge IoT devices. Additionally, investments in next-generation AI chip fabrication facilities are poised to reduce per-chip costs by over 20% by the end of 2026. The increasing affordability is poised to support the sector leveraging industrial automation.
Major Technological Trends in the Market
The rapid adoption of neuromorphic computing architectures within AI-IoT devices have bolstered real-time data processing at the edge and ultra-low power. The rising deployment trends have suggested a surging shift toward open-source AI frameworks tailored for IoT environments that have facilitated improved customization and interoperability across heterogenous devices. Another major trend has been the evolution of hybrid cloud-edge infrastructure that has reshaped implementation methodologies. The table below highlights the impact of technological trends on the AI in IoT market:
|
Technology Trend |
Industry Sector |
Adoption Metric |
Impact Indicator |
|
Neuromorphic Computing Chips |
Industrial Automation |
Increasing deployment in >15 major plants |
Significant reduction in edge latency and power consumption |
|
Open-Source AI Frameworks |
Consumer Devices |
35.5% YoY growth in IoT-specific AI libraries |
Enhanced device interoperability and developer ecosystem expansion |
|
Hybrid Cloud-Edge AI Deployment |
Smart Cities & Utilities |
Pilot projects in 12 metropolitan areas |
Improved data sovereignty and network efficiency |
Impact of Rising 5G Deployment on the Market
The market’s growth has been bolstered by network slicing and the ultra-reliable low-latency communications (URLLC) made possible via the improved 5G infrastructure. A significant improvement has been in the reduction of decision latency of AI models due to improved 5G connections, which in turn supports faster inference across distributed IoT devices. The table below highlights outcomes and impact area of 5G deployment on the AI in IoT market:
|
Impact Area |
Example Application |
Quantified or Directional Metric |
Business/Consumer Outcome |
|
Edge Inference Optimization |
Industrial robotics |
Up to 41% reduction in AI decision latency |
Faster fault detection and predictive maintenance |
|
Real-Time Mobility AI |
Connected vehicles |
30+ cities with URLLC-enabled 5G coverage” |
Enhanced V2X decision accuracy, improved safety |
|
Device-as-a-Service Models |
Intelligent logistics |
26% increase in intelligent device leasing |
Lower entry barriers, flexible scaling for enterprises |
Challenge
- Adhering to data localization mandates and privacy compliance: The strict data localization and privacy laws have posed considerable entry barriers for AI in IoT manufacturers. The challenge has been particularly persistent in the domestic markets of EU, India, and China. These regulations have pushed companies to store and process data locally which complicates cloud-based AI analytics. Additionally, a regional analysis of the laws has indicated a lack of interoperability impacting the global scalability for AI solutions that are reliant on centralized data models.
AI in IoT Market: Key Insights
| Report Attribute | Details |
|---|---|
|
Base Year |
2024 |
|
Forecast Year |
2025-2037 |
|
CAGR |
7% |
|
Base Year Market Size (2024) |
USD 78.7 billion |
|
Forecast Year Market Size (2037) |
USD 186.9 billion |
|
Regional Scope |
|
AI in IoT Segmentation
Component (Software, Hardware, Data Management Software, AI Platforms)
The software segment is poised to maintain a leading revenue share of 42.8% throughout the forecast period. The segment’s expansion is supported by the surging demand for advanced data analytics and predictive maintenance capabilities across industries. Additionally, IoT devices have proliferated multiple sectors as well as day-to-day lives of individual consumers, creating an exponential volume of data. Now, to manage the data, software solutions are required so as to effectively analyze the vast datasets. Another trend that has permeated the global AI in IoT market is the rampant shift towards adopting software centric-models. To leverage this shift, in January 2023, Qualcomm and Microsoft announced a collaboration to develop AI-IoT solutions for varied industries.
Services (Managed Services, Professional Services)
The managed services segment is poised to expand its revenue share during the forecast period. The growth of the segment is propelled by the rising outsourcing of complex AI-IoT operations to efficiently manage the data analytics and infrastructure without investments on in-house expertise. Managed services have allowed businesses to focus on core competencies whilst leveraging specialized service provider for the deployment of AI-IoT and outsource its maintenance. The trend has ensured sustained opportunities for vendors to offer bundled managed services to enterprises with the demand curve expected to spike by the end of 2037.
Deployment (Edge, Cloud, Hybrid)
The edge computing is poised to emerge as the predominant deployment approach throughout the forecast period and register a revenue share of 54.3%. The gradual shift towards edge computing has been fueled by the requirement for real-time analytics and reduction in bandwidth usage. Additionally, the collaboration between AWS, Intel, Nokia, and Ericsson in February 2024 exemplifies the commitment to expand edge computing capabilities by providing localized AI processing. The opportunities are expected to remain rife for deployment in transportation hubs, against the backdrop of smart city initiatives, and in manufacturing plants by leveraging Industry 5 principles.
Our in-depth analysis of the global market includes the following segments:
|
Component |
|
|
Services |
|
|
Deployment |
|
|
Application |
|
Vishnu Nair
Head - Global Business DevelopmentCustomize this report to your requirements — connect with our consultant for personalized insights and options.
AI in IoT Industry - Regional Synopsis
Asia Pacific Market Forecast
The APAC AI in IoT market is estimated to maintain a dominant revenue share of 38.8% during the forecast period. A significant driver of the APAC market is the large-scale digitalization initiatives in multiple economies in the region. Moreover, the rise in adoption of AI-enabled smart manufacturing and a burgeoning consumer electronics ecosystem, has ensured a lucrative market in APAC. In terms of nationwide strategies, the National AI Strategy of India and the Society 5 roadmap of Japan are crucial indicators of sustained opportunities in the region.
The China market is poised to expand during the anticipated timeline. The market is shaped by strategic investments under the fourteenth 5-year plan and the New Infrastructure initiative. There has been a heightened emphasis on AI and IoT as pillars of the digital sovereignty that China has been seeking. Additionally, the integration of AI in IoT into smart home and wearable devices has signified that consumer electronics will offer considerably higher opportunities for deployment in the China market by the end of 2037.
North America Market Forecast
The North America AI in IoT sector is expanding at a CAGR of 14.7% during the forecast period, exhibiting the fastest expansion. A significant factor of the regional market’s expansion is the surging demand for data-driven decision-making capabilities across sectors ranging from automotive, healthcare, and manufacturing. With smart city initiatives attracting considerable investments in the U.S., Canada, and Mexico, the opportunities for IoT and AI integration have intensified. The table below highlights the major investments made in AI in North America:
|
Company/Investment |
Date |
Investment Details |
|
Applied Intuition |
March 2024 |
$250.5M Series E funding, $300.3M secondary offering, valuation of $6B for AI-driven autonomous vehicle software |
|
DigitalBridge & Intel |
January 2024 |
Launch of Articul8, a generative AI venture for enterprise solutions |
|
Cisco (Acquisition of Splunk) |
September 2023 |
Acquisition of Splunk for $28.1B, focusing on AI-driven IoT applications and data analytics |
The U.S. AI in IoT market is predicted to register a significant revenue share by the end of 2037. The regional market’s growth is underpinned by the greater application of AI in multiple industries, ranging from healthcare to autonomous transportation. The National AI Initiative has bolstered AI adoption supporting the market’s growth. Another facet of the market in the U.S. is supported by the proliferation of AI-powered IoT devices in consumer electronics and energy management.
Companies Dominating the AI in IoT Landscape
- Company Overview
- Business Strategy
- Key Product Offerings
- Financial Performance
- Key Performance Indicators
- Risk Analysis
- Recent Development
- SWOT Analysis
The market has remained highly competitive. Major tech giants such as Microsoft and Intel dominate the market. The leading players are consistently leveraging improving the integration of AI in IoT to expand the scope of solutions. In terms of strategic initiatives, the heightened R&D in edge AI and smart city project partnerships is poised to create sustained lucrative opportunities. The table below highlights the major players of the Ai in IoT market:
|
Company Name |
Country |
Revenue Share % (2024) |
|---|---|---|
|
Intel Corporation |
USA |
14.4% |
|
Microsoft Corporation |
USA |
12.6% |
|
Siemens AG |
Germany |
10.8% |
|
Samsung Electronics |
South Korea |
8.2% |
|
NEC Corporation |
Japan |
7.7% |
|
Honeywell International |
USA |
xx% |
|
ABB Ltd |
Switzerland |
xx% |
|
Infosys Limited |
India |
xx% |
|
Bosch Group |
Germany |
xx% |
|
Fujitsu Limited |
Japan |
xx% |
|
Telstra Corporation |
Australia |
xx% |
|
Huawei Technologies |
China* |
xx% |
|
NXP Semiconductors |
Netherlands |
xx% |
|
Maxis Berhad |
Malaysia |
xx% |
|
SK Telecom |
South Korea |
xx% |
Below are the areas covered for each company that is a key player in the AI in IoT market:
Recent Developments
- In October 2024, LightOn became the first listed generative AI startup in Europe. Its IPO was listed on Euronext Growth Paris and the company has integrated its Optical Processing Units with AI software.
- In March 2o24, NVIDIA introduced the 6G Research Cloud platform, and provides researchers with tools to bolster AI for cloud radio access network technology. The platform is specifically designed to support the development of 6G technologies.
Author Credits: Preeti Wani
- Report ID: 3317
- Published Date: Jun 09, 2025
- Report Format: PDF, PPT
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