Mordor Intelligence has published a new report on the AI in IoT market, offering a comprehensive analysis of trends, growth drivers, and future projections
AI in IoT Market Overview
According to Mordor Intelligence, the AI in IoT market size was valued at USD 60.71 billion in 2025 and is estimated to increase to USD 74.04 billion in 2026. The market forecast indicates that the market will reach USD 199.46 billion by 2031, growing at a CAGR of 21.95% during 2026–2031. Growth in the industry reflects how businesses are embedding artificial intelligence directly into devices, sensors, and connected systems. This approach allows machines to analyze data and make decisions closer to where the data is generated. As a result, organizations reduce network congestion and improve response time for real-time applications.
The expanding role of edge intelligence is also strengthening the share across sectors such as manufacturing, transportation, utilities, and healthcare. Companies are increasingly using AI-enabled IoT solutions to monitor equipment, detect operational issues, and automate routine processes. These applications support improved productivity while reducing downtime and operational costs.
AI in IoT Market Growth Drivers
Edge AI and Real-Time Decision Making
One of the key market trends is the growing use of artificial intelligence at the edge of networks. Instead of sending all sensor data to centralized cloud systems, organizations are deploying AI models directly within devices or gateways. This approach supports faster decision-making because devices can analyze data locally. In industrial environments, this capability helps machines detect faults, adjust operations, and respond to anomalies without delays. As companies focus on operational efficiency and automation, edge-based analytics continues to influence AI in IoT market growth.
Expansion of 5G and Connected Infrastructure
The rollout of advanced communication networks is strengthening the industry. Faster connectivity allows connected devices to exchange data efficiently while supporting high-bandwidth applications such as smart transportation systems and remote monitoring platforms. These improvements enable organizations to deploy larger IoT networks while maintaining reliable performance. As a result, connectivity upgrades are becoming an important factor in the AI in IoT market forecast, particularly in sectors that rely on large volumes of device data.
Predictive Maintenance in Industrial Operations
Manufacturing companies are increasingly adopting predictive maintenance systems powered by AI-enabled IoT platforms. Sensors placed on equipment collect performance data that AI models analyze to identify patterns linked to potential failures. This approach helps companies avoid unexpected shutdowns and maintain stable production operations. Predictive maintenance programs are therefore strengthening the AI in IoT market share within industrial sectors and are expected to remain a central part of market trends.
Energy-Efficient Device Management
Energy optimization is becoming a priority across the global market. AI-enabled monitoring systems help organizations track energy consumption across buildings, factories, and infrastructure networks. By analyzing operational patterns, these systems can automatically adjust lighting, temperature, and machinery usage. This capability supports sustainability goals while reducing operational expenses, contributing to steady AI in IoT market growth.
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AI in IoT Market Segmentation
By Component
- Connectivity Management
- Network Bandwidth Management
- Real-time Streaming Analytics
By Deployment Mode
By Technology
- Machine Learning and Deep Learning
- Natural Language Processing
- Context-Aware Computing
By IoT Connectivity Type
- LPWAN (LoRa, NB-IoT, Sigfox)
- Short-range (Wi-Fi, BLE, Zigbee)
By End-user Vertical
- Transportation and Mobility
By Geography
- Australia and New Zealand
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Key Players in the AI in IoT Market
- Amazon Web Services Inc. (Amazon Inc.)
- Google LLC (Alphabet Inc.)
Conclusion
The artificial Intelligence IoT market is entering a period of strong adoption as businesses continue integrating artificial intelligence into connected systems. Organizations across industries are using AI-enabled IoT platforms to automate decision-making, improve operational efficiency, and monitor infrastructure in real time. These capabilities are supporting broader digital transformation initiatives within the global AI in IoT industry.
Edge computing is expected to remain an important factor influencing trends, as companies look for faster analytics and reduced reliance on centralized cloud processing. At the same time, improvements in connectivity infrastructure and device performance are creating new opportunities for large-scale IoT deployments. Industrial automation, predictive maintenance, and smart resource management are also shaping the long-term AI in IoT market forecast. As businesses continue investing in intelligent devices and connected systems, the demand for integrated AI and IoT solutions will expand across sectors.
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