AI in IoT Market - Global Industry Size, Share, Trends, Opportunity, and Forecast, Segmented By Technology (Machine Learning, Deep Learning, Natural Language Processing), By Industry Vertical (BFSI, IT and Telecom, Retail and E-commerce, Manufacturing, Healthcare, Energy and Utilities, Transportation and Mobility, Others), By Region, By Competition 2020-2030F

Market Overview

The Global AI in IoT Market, valued at USD 63.17 Billion in 2024, is projected to experience a CAGR of 8.90% 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.

According to GSMA Intelligence, the global IoT market is projected to comprise 25.2 billion connections in 2025, establishing a vast ecosystem for AIoT solutions. However, a significant challenge to market expansion is the complexity of integrating AI with diverse existing IoT infrastructures. Many legacy IoT systems lack the computational capacity for AI applications, requiring extensive hardware and software modifications and addressing interoperability issues across platforms.

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. This illustrates direct investment in advanced analytical capabilities for real-time applications.

Enhanced automation and operational efficiency also significantly propel the AI in IoT market. AI algorithms empower IoT devices to operate with greater autonomy, streamlining industrial processes and minimizing manual oversight. This results in optimized resource utilization, precise quality control, and proactive identification of potential issues, thereby substantially reducing operational costs and improving overall productivity. For instance, according to Oxmaint, in August 2025, facilities implementing IoT and AI-powered predictive maintenance achieved a 35-50% reduction in unplanned downtime while decreasing maintenance costs by 25-30% compared to reactive approaches. This pervasive benefit underpins the market's growth, with the AI in IoT market expected to grow at a compound annual growth rate of 26% by 2024, as stated by Shoplogix in its November 2023 article '20+ Amazing Industrial IoT Statistics and Trends for 2024'.

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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.

These integration complexities directly hinder market expansion by prolonging deployment cycles and elevating the overall cost of ownership for enterprises. Achieving seamless data flow and communication between disparate devices and cloud-based AI processing units poses considerable technical challenges. According to GSMA Intelligence, in 2024, 32% of enterprises identified the integration of IoT technology with other existing technologies as a key deployment challenge. This persistent difficulty in achieving harmonious integration deters potential adopters, particularly those with considerable investments in existing, fragmented IoT ecosystems, thereby slowing the rate of AIoT adoption across industrial sectors.

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. According to Siemens, in August 2025, the company announced its approach to predictive maintenance with embedded edge AI, which can automatically adjust machine parameters in real time to prevent disruptions, thereby enhancing operational continuity and efficiency. This approach also mitigates data transfer bottlenecks, reinforces data privacy by localizing sensitive information, and ensures robust system functionality even with intermittent network connectivity.

Generative AI Integration into IoT Devices is transforming the market by empowering devices to move beyond basic data analysis. This advanced capability enables IoT systems to create new content, simulate complex scenarios, and autonomously adapt their functions, leading to more sophisticated intelligence. In smart factory settings, for example, generative AI can design optimal production workflows or generate synthetic data to train other AI models, accelerating product development and innovation cycles. According to the Manufacturers Alliance Foundation, between August 2023 and August 2024, 93% of American manufacturers initiated AI projects, with an additional 6% in the planning stages, demonstrating the rapid integration of advanced AI capabilities into industrial operations. This integration fosters more adaptive IoT ecosystems, capable of addressing intricate operational challenges without constant human intervention.

Segmental Insights

The Manufacturing sector is rapidly emerging as the fastest-growing segment within the Global AI in IoT Market. This accelerated expansion is primarily driven by the imperative for operational efficiency and enhanced productivity across industrial processes. The integration of artificial intelligence with IoT enables critical applications such as predictive maintenance, where AI analyzes real-time sensor data from machinery to anticipate and prevent potential failures, thereby minimizing downtime and maintenance costs. Furthermore, AI in IoT significantly improves quality control through automated inspection systems that detect defects with precision, leading to higher product standards and reduced waste. Manufacturers are also leveraging these combined technologies for advanced automation and optimizing production schedules and resource allocation, fostering the development of intelligent, adaptive factories.

Regional Insights

North America stands as the leading region in the Global AI in IoT Market, primarily driven by its highly developed technological infrastructure and extensive investments in research and development. The region benefits significantly from a vibrant ecosystem comprising global technology leaders and an active startup community, which together consistently foster innovation in artificial intelligence and IoT solutions. This strong foundation enables the widespread and early adoption of advanced technologies across crucial sectors such as manufacturing, healthcare, and smart cities. The increasing demand for real-time data analytics and enhanced operational efficiency further propels market expansion, with supportive governmental initiatives also playing a vital role in accelerating AI and IoT integration across industries.

Recent Developments

• In October 2025, Synaptics Incorporated launched its new Astra SL2600 Series of multimodal Edge AI processors, designed to enhance the capabilities of intelligent devices within the cognitive Internet of Things (IoT). These processors aim to power next-generation smart appliances, factory automation equipment, healthcare devices, and autonomous robotics. The series integrates advanced NPU architectures and open-source compilers to establish a new benchmark in IoT AI application development. The SL2610 product line, featuring Google’s RISC-V-based Coral NPU, emphasizes power efficiency and robust security, supporting a wide array of IoT solutions.

• In October 2025, Oracle announced a collaboration with Microsoft aimed at improving supply chain efficiency and responsiveness for manufacturers. This partnership focuses on developing an integration blueprint that enables organizations utilizing Oracle Fusion Cloud Supply Chain & Manufacturing (SCM) to leverage real-time insights from factory equipment and sensors. By integrating data captured through Azure IoT Operations and processed by Microsoft Fabric, companies can enhance data-driven decision-making and automate critical supply chain processes, directly impacting the global AI in IoT market through industrial application.

• In October 2025, Arm and Meta deepened their strategic partnership to advance AI efficiency across various compute layers, ranging from milliwatt-scale on-device intelligence to megawatt-scale training systems for advanced AI models. This multi-year collaboration builds on existing hardware and software co-design efforts, combining Arm’s expertise in power-efficient AI compute with Meta’s innovations in AI-driven products and infrastructure. The partnership seeks to improve efficiency for billions of devices by optimizing AI software across platforms like PyTorch and ExecuTorch, thereby enhancing AI in IoT applications.

• In October 2025, Nokia continued its efforts in driving global smart transportation initiatives through its 5G and IoT partnerships with entities such as AT&T, T-Mobile, and NTT Data. These collaborations are enabling substantial upgrades to transportation infrastructure powered by artificial intelligence. Nokia’s solutions contribute to enhancing logistics efficiency and reducing energy consumption within smart cities and industrial settings, demonstrating the direct impact of AI and IoT integration on critical urban and industrial operational improvements.

Key Market Players

• Microsoft Corporation
• Amazon.com, Inc.
• Alphabet Inc.
• Apple Inc.
• IBM Corporation
• Siemens AG
• Samsung Electronics Co., Ltd.
• Huawei Technologies Co., Ltd.
• Intel Corporation
• SAP SE

Report Scope:

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:

• AI in IoT Market, By Technology:

o   Machine Learning

o   Deep Learning

o   Natural Language Processing

• AI in IoT Market, By Industry Vertical:

o   BFSI

o   IT and Telecom

o   Retail and E-commerce

o   Manufacturing

o   Healthcare

o   Energy and Utilities

o   Transportation and Mobility

o   Others

• AI in IoT Market, By Region:

o   North America

§  United States

§  Canada

§  Mexico

o   Europe

§  France

§  United Kingdom

§  Italy

§  Germany

§  Spain

o   Asia Pacific

§  China

§  India

§  Japan

§  Australia

§  South Korea

o   South America

§  Brazil

§  Argentina

§  Colombia

o   Middle East & Africa

§  South Africa

§  Saudi Arabia

§  UAE

Competitive Landscape

Company Profiles: Detailed analysis of the major companies presents in the Global AI in IoT Market.

Available Customizations:

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:

Company Information

• Detailed analysis and profiling of additional market players (up to five).

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