AI in IoT Market By Component (Software, Hardware, Services), By Technology (Machine Learning, Deep Learning, Edge Computing), By Application (Smart Homes, Industrial Automation, Healthcare, Automotive, Agriculture, Energy Management), By End User (Enterprises, Consumers, Governments), and By Region; Global Insights & Forecast (2024 – 2030)

As per Intent Market Research, the AI in IoT Market was valued at USD 9.7 billion in 2023 and will surpass USD 26.3 billion by 2030; growing at a CAGR of 15.4% during 2024 - 2030.

The AI in IoT (Internet of Things) market is witnessing a surge in growth as the convergence of artificial intelligence and connected devices continues to revolutionize various industries. AI-powered IoT solutions enable smarter decision-making, real-time data processing, and autonomous operations, making them critical for enhancing operational efficiency, reducing costs, and improving user experiences. This fusion of AI and IoT allows businesses to leverage vast amounts of data collected from connected devices to optimize processes, predict outcomes, and automate decision-making, leading to smarter, more responsive systems across sectors like healthcare, automotive, agriculture, and energy.

As the number of connected devices grows globally, the demand for AI-driven IoT solutions is expected to skyrocket, creating new business opportunities and transforming industries. The use of AI technologies such as machine learning, edge computing, and deep learning is enhancing IoT's potential, enabling faster data processing, real-time analytics, and better decision-making at the edge. These advancements are paving the way for next-generation IoT solutions that will redefine how we interact with technology, providing real-time insights and driving innovation across industries.

Machine Learning Drives Growth in Smart Homes Application

Machine learning is the key technology driving the growth of AI in the smart homes application within the IoT market. Machine learning algorithms allow smart home devices to learn from user behaviors and adapt to preferences, improving the overall user experience. From smart thermostats that learn and adjust to the user's temperature preferences to AI-powered security systems that detect unusual activity, machine learning is enhancing the intelligence of home automation devices. The technology's ability to predict and anticipate needs—such as automatically adjusting lighting, temperature, or appliance settings—has made smart homes more intuitive and user-friendly.

In addition, machine learning enables the integration of various smart home devices, allowing them to work together seamlessly. As consumers demand more convenience and control over their homes, machine learning continues to play a vital role in delivering personalized experiences. The widespread adoption of smart home devices, including voice assistants, smart lighting, and security cameras, is driving significant growth in this segment of the AI in IoT market. As machine learning continues to evolve, its impact on the smart homes sector is expected to expand, further enhancing the functionality and intelligence of home automation systems.

Edge Computing Powers Industrial Automation in AI in IoT

Edge computing is the fastest-growing technology driving AI in IoT, particularly in the industrial automation application. By enabling data processing at or near the source of data generation—such as IoT sensors and devices—edge computing significantly reduces latency and bandwidth requirements compared to cloud-based processing. This allows industrial operations to process and analyze data in real time, improving efficiency, safety, and overall productivity. Edge computing is particularly important in sectors like manufacturing, energy management, and supply chain logistics, where time-sensitive data needs to be processed quickly to make immediate operational decisions.

In industrial automation, edge computing enables predictive maintenance, real-time monitoring, and more responsive systems. By analyzing data locally, edge computing can detect equipment failures before they occur, preventing costly downtime and improving the longevity of assets. Additionally, edge computing supports the scaling of IoT solutions by reducing the reliance on centralized cloud infrastructure and enabling local control of operations. The growth of edge computing in industrial applications is set to continue, driven by increasing automation and the need for faster, more reliable data processing across industries.

Enterprises Lead the Way as End Users of AI in IoT

Enterprises represent the largest end users of AI in the IoT market, with businesses across various sectors leveraging connected devices and AI-powered solutions to optimize operations and enhance customer experiences. From smart manufacturing solutions in the industrial sector to data-driven decision-making in retail and logistics, enterprises are adopting IoT technologies to improve operational efficiency, reduce costs, and drive innovation. The integration of AI with IoT allows businesses to automate processes, analyze vast amounts of data in real-time, and create more responsive, flexible systems that can adapt to changing market conditions.

In particular, enterprises in sectors like manufacturing, logistics, and retail are increasingly turning to AI-driven IoT solutions to streamline supply chains, optimize inventory management, and improve customer engagement. As more businesses adopt these technologies to gain a competitive edge, the demand for AI in IoT solutions is expected to continue growing. Enterprises are also investing in IoT infrastructure to enable smarter decision-making, and with the increasing connectivity of devices, the potential for AI in IoT to transform enterprise operations is immense.

North America Dominates the AI in IoT Market

North America is the largest region in the AI in IoT market, driven by its advanced technological infrastructure, high adoption rate of AI solutions, and significant investments in IoT innovations. The United States, in particular, is a global leader in AI research and development, with a strong presence of technology giants, startups, and research institutions pushing the boundaries of AI in IoT applications. North America’s early adoption of IoT technologies across industries like automotive, healthcare, and industrial automation has positioned the region as a key player in the market.

Moreover, government initiatives and funding for smart city projects, connected infrastructure, and industrial IoT further support the growth of AI in IoT technologies in the region. The robust ecosystem of technology companies and the increasing use of AI in sectors such as energy management, agriculture, and healthcare contribute to North America's dominance. As the region continues to innovate and expand its IoT capabilities, North America is expected to maintain its leadership position in the global AI in IoT market.

Leading Companies and Competitive Landscape

The AI in IoT market is competitive, with a range of technology providers and solution developers focusing on advancing IoT infrastructure and AI integration. Key players include Intel Corporation, NVIDIA Corporation, Microsoft Corporation, Google LLC, and IBM Corporation, all of which are investing heavily in AI and IoT technologies to deliver innovative solutions. These companies are developing hardware, software, and services to support AI in IoT, ranging from machine learning algorithms to IoT sensors and edge computing infrastructure.

As the market grows, the competitive landscape is expected to become more dynamic, with companies focusing on expanding their IoT portfolios, improving AI algorithms, and exploring new applications across industries. Strategic partnerships and acquisitions are common as companies seek to strengthen their AI and IoT capabilities. The AI in IoT market is poised for continued innovation, and players that can offer scalable, secure, and efficient solutions will be well-positioned for long-term success in this rapidly evolving space.

Recent Developments:

• In October 2024, IBM launched a new AI-powered IoT platform designed to optimize industrial automation and predictive maintenance.
• In September 2024, Microsoft expanded its Azure IoT suite with advanced AI and machine learning tools to enhance smart city applications.
• In August 2024, Amazon Web Services (AWS) introduced new AI-based IoT solutions for energy management in smart buildings.
• In July 2024, Intel unveiled a new edge AI solution to improve real-time data processing for IoT devices in the automotive industry.
• In June 2024, Qualcomm Technologies announced an AI-enhanced IoT chipset designed for low-power, high-performance devices in healthcare and consumer applications.

List of Leading Companies:

• IBM Corporation
• Microsoft Corporation
• Intel Corporation
• Cisco Systems
• Google LLC
• Amazon Web Services (AWS)
• Qualcomm Technologies
• Huawei Technologies
• SAP SE
• PTC Inc.

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