PUBLISHER: TechSci Research | PRODUCT CODE: 1881582
PUBLISHER: TechSci Research | PRODUCT CODE: 1881582
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The Global AI in IoT Market, valued at USD 63.17 Billion in 2024, is projected to experience a CAGR of 8.9% to reach USD 105.36 Billion by 2030. Artificial Intelligence in IoT (AIoT) integrates AI with Internet of Things infrastructure, enabling connected devices to autonomously collect, analyze, and act on data without human intervention. Main market drivers include the demand for enhanced operational efficiency and cost savings through automation, exemplified by predictive maintenance and optimized resource management. The increasing volume of data from proliferating smart devices further necessitates AI for real-time processing and actionable insights.
| Market Overview | |
|---|---|
| Forecast Period | 2026-2030 |
| Market Size 2024 | USD 63.17 Billion |
| Market Size 2030 | USD 105.36 Billion |
| CAGR 2025-2030 | 8.9% |
| Fastest Growing Segment | Manufacturing |
| Largest Market | North America |
Key Market Drivers
The demand for real-time data processing and advanced analytics stands as a primary driver for the global AI in IoT market. AI in IoT facilitates immediate analysis of extensive datasets from connected devices, transforming raw data into actionable intelligence at the edge and in cloud environments. This enables quicker, more informed decision-making, essential for applications like anomaly detection, proactive risk management, and dynamic resource optimization. According to Zilch, in April 2024, the company announced an extended collaboration with Amazon Web Services to accelerate AI innovation across its offerings, leveraging AWS's AI and machine learning services like Amazon SageMaker and Amazon Bedrock.
Key Market Challenges
The complexity of integrating artificial intelligence with diverse existing Internet of Things infrastructures presents a significant impediment to the growth of the global AI in IoT market. Many legacy IoT systems lack the computational capacity or architectural flexibility required for advanced AI applications. This necessitates extensive hardware and software modifications, creating a substantial barrier for organizations seeking to leverage AIoT solutions. The absence of standardized protocols and the prevalence of proprietary technologies across various IoT platforms further contribute to widespread interoperability issues.
Key Market Trends
Distributed Edge AI Processing represents a pivotal trend, shifting AI computations closer to the data source on IoT devices or local edge infrastructure. This decentralization dramatically minimizes latency, enabling real-time decision-making essential for critical applications such as autonomous industrial systems and responsive operational control. In manufacturing, processing data at the edge facilitates immediate anomaly detection and allows for rapid, proactive adjustments to machinery, preventing costly downtime.
In this report, the Global AI in IoT Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:
Company Profiles: Detailed analysis of the major companies presents in the Global AI in IoT Market.
Global AI in IoT Market report with the given market data, TechSci Research offers customizations according to a company's specific needs. The following customization options are available for the report: