The Global AI in IoT Market: Intelligent Connectivity at Scale

The AI in IoT market size is projected to grow from USD 8.3 Billion in 2023 to USD 60.8 Billion by 2032, exhibiting a compound annual growth rate (CAGR) of 28.20% during the forecast period (2023 - 2032). The combination of artificial intelligence and Internet of Things is enabling advanced analytics, automation and intelligent connectivity for enterprise IoT applications. Embedding machine learning into IoT improves network reliability, derives predictive insights from sensor data, and allows for smarter IoT operations. Key segments, top companies, drivers and regional trends are shaping the growth trajectory of the AI in IoT market.

Key AI in IoT Market Segments

The AI in IoT market is segmented by components, technology, end user industry and geography:

• By components, the market is divided into platforms, software solutions and services. AI software solutions for IoT hold the largest share currently.
• By technology, machine learning and natural language processing are the leading AI technologies enabling IoT applications. Deep learning adoption is forecast to grow at the highest rate.
• By end user industry, manufacturing, energy, retail, transport and healthcare are the top segments. Manufacturing accounts for the largest market share.
• By region, North America holds the dominant market share. However, Asia Pacific will exhibit the fastest growth over the forecast period.

Major Companies Offering AI for IoT

Leading technology companies offering AI software and platforms for IoT include:

• Google - Google Cloud's IoT platform leverages AI for IoT analytics, edge processing and automation.
• Microsoft - Microsoft Azure integrates machine learning and IoT connectivity through Azure IoT Edge and Azure Machine Learning.
• IBM - IBM Watson allows IoT devices to be trained using various machine learning algorithms to identify patterns and act on insights.
• AWS - Amazon Web Services provide IoT services like AWS IoT Greengrass that enable local ML-powered analytics on edge devices.
• GE - GE incorporates computer vision, machine learning and predictive analytics into its Industrial IoT solutions for smart industry applications.

Key Drivers for the AI in IoT Market

Major factors propelling the growth of AI in IoT market:

• Data growth from IoT devices - Massive data generated from enterprise IoT sensors and devices requires AI to analyze in real time.
• Network connectivity challenges - Spotty connectivity makes edge intelligence using AI critical for IoT reliability and low latency.
• Complex IoT systems - Large scale IoT deployments with thousands of devices need AI to manage connectivity, security and data flows.
• Value from IoT investments - AI is key for extracting maximum ROI from IoT deployments by identifying insights and optimizing operations.
• Autonomous capabilities - Incorporating autonomy through AI is allowing enterprises to create self-running IoT systems for manufacturing, energy, smart spaces and more.

Browse In-depth Market Research Report (128 Pages, Charts, Tables, Figures) on AI in IoT Market

Regional Market Outlook

• North America - Early IoT adoption by US enterprises coupled with strong cloud infrastructure make North America the largest market for AI in IoT.
• Europe - The industrial manufacturing sector is driving adoption of AI software for predictive maintenance and quality control applications.
• Asia Pacific - Rapid urbanization in APAC economies is expanding the number of smart city IoT deployments enhanced by machine learning capabilities.

In summary, AI is adding the intelligence layer to enable value creation from IoT investments. By providing automation, analytics and intelligent connectivity, AI addresses key challenges in enterprise IoT ecosystems. With IoT adoption growing globally, the AI in IoT market outlook remains highly promising through 2027.