Artificial Intelligence (AI) in IoT

Artificial Intelligence (AI) in IoT

Global Artificial Intelligence (AI) in IoT Market to Reach US$89.1 Billion by 2030

The global market for Artificial Intelligence (AI) in IoT estimated at US$21.2 Billion in the year 2023, is expected to reach US$89.1 Billion by 2030, growing at a CAGR of 22.7% over the analysis period 2023-2030. Platforms Component, one of the segments analyzed in the report, is expected to record a 20.6% CAGR and reach US$32.1 Billion by the end of the analysis period. Growth in the Software Solutions Component segment is estimated at 25.2% CAGR over the analysis period.

The U.S. Market is Estimated at US$6.0 Billion While China is Forecast to Grow at 22.2% CAGR

The Artificial Intelligence (AI) in IoT market in the U.S. is estimated at US$6.0 Billion in the year 2023. China, the world`s second largest economy, is forecast to reach a projected market size of US$13.8 Billion by the year 2030 trailing a CAGR of 22.2% over the analysis period 2023-2030. Among the other noteworthy geographic markets are Japan and Canada, each forecast to grow at a CAGR of 19.9% and 19.3% respectively over the analysis period. Within Europe, Germany is forecast to grow at approximately 15.9% CAGR.

Global Artificial Intelligence (AI) in IoT Market - Key Trends and Drivers Summarized

How Is AI Transforming Data Processing and Decision-Making in IoT?

Artificial Intelligence (AI) is revolutionizing the Internet of Things (IoT) by enabling faster, smarter data processing and real-time decision-making at unprecedented scales. Traditionally, IoT devices would collect data and transmit it to centralized servers for analysis, often causing delays in processing and response. Now, with AI embedded at the edge, IoT devices can process data locally, making instantaneous decisions without needing to rely on cloud connectivity. Edge AI allows connected devices to detect patterns, identify anomalies, and take corrective actions in real time, essential for time-sensitive applications like autonomous vehicles, industrial machinery, and smart medical devices. For example, in smart manufacturing, AI-powered IoT sensors monitor equipment for unusual vibrations or temperature spikes, triggering alerts or adjustments to prevent breakdowns and reduce downtime. AI’s role in analyzing data directly within IoT systems streamlines operations and improves reliability, reducing latency and bandwidth use while empowering devices to function autonomously.

Can AI Enhance Security and Predictive Maintenance in IoT Ecosystems?

AI is proving indispensable for enhancing the security and longevity of IoT networks by enabling predictive maintenance and bolstering cybersecurity measures. With the vast number of connected devices, IoT networks are particularly vulnerable to cyber threats, as each device potentially introduces new security risks. AI-driven cybersecurity solutions continuously monitor network traffic and device behavior, identifying anomalies that may indicate potential attacks, such as unauthorized access or malware, and responding proactively to mitigate threats. Companies like Darktrace and Cisco use AI to provide real-time threat detection and response, safeguarding IoT networks against ever-evolving cyber risks. Additionally, AI-powered predictive maintenance in IoT systems analyzes data from connected devices to forecast when equipment might fail, allowing for timely repairs before issues disrupt operations. In sectors like manufacturing, transportation, and energy, predictive maintenance minimizes costly downtime and extends equipment lifespan by identifying maintenance needs early. By enhancing security and enabling proactive maintenance, AI strengthens IoT infrastructure, ensuring operational continuity and protection against potential threats.

How Is AI Driving Efficiency in Smart Cities and Industrial IoT?

AI is a critical component in maximizing the efficiency of IoT-driven smart cities and industrial applications. In smart cities, AI enables intelligent systems that manage traffic, energy consumption, waste management, and public safety more effectively. For instance, AI in IoT-powered traffic management systems can analyze data from sensors, cameras, and GPS to predict congestion patterns and optimize traffic flow in real time, reducing commute times and minimizing emissions. Similarly, AI-driven energy management solutions in smart grids can predict energy demand based on usage patterns, adjust power distribution, and incorporate renewable energy sources, creating a more sustainable urban infrastructure. In industrial IoT, AI-powered solutions enable real-time monitoring and optimization of factory operations, supply chains, and logistics. Companies such as Siemens and GE employ AI in industrial IoT systems to enhance productivity by analyzing sensor data from machinery, predicting maintenance needs, and optimizing workflows. Through these applications, AI maximizes IoT’s potential to create smarter, more efficient environments in both urban and industrial contexts.

What Factors Are Driving the Growth of AI in the IoT Market?

The growth in the AI in IoT market is driven by several key factors, including advancements in AI technology, increased adoption of IoT devices, and rising demand for automation and predictive capabilities. As the number of connected devices expands across industries, there is an urgent need for advanced AI-driven analytics that can process and interpret massive datasets in real time, enabling devices to make autonomous decisions and improve operational efficiency. The rise of edge computing has been instrumental, allowing AI algorithms to run directly on IoT devices, reducing dependency on cloud processing and enabling faster responses. Increasing cybersecurity concerns are also fueling AI adoption in IoT, as AI’s ability to detect and mitigate threats proactively makes it an essential tool for securing connected networks. Furthermore, the demand for predictive maintenance and operational optimization is growing as industries seek to reduce costs and improve uptime; AI-driven IoT solutions are critical to achieving these goals, especially in sectors like manufacturing, healthcare, and transportation. Strategic partnerships between tech companies and IoT providers are accelerating the development of AI-IoT applications, driving innovation and expanding market reach. Together, these factors are positioning AI as an indispensable component of IoT, ensuring scalability, efficiency, and security across increasingly connected environments.

SCOPE OF STUDY:

The report analyzes the Artificial Intelligence (AI) in IoT market in terms of US$ Million by the following Component; Technology, and Geographic Regions/Countries:

Segments:
Component (Platforms, Software Solutions, Services); Technology (Machine Learning & Deep Learning, Natural Language Processing)

Geographic Regions/Countries:
World; United States; Canada; Japan; China; Europe (France; Germany; Italy; United Kingdom; and Rest of Europe); Asia-Pacific; Rest of World.

Select Competitors (Total 234 Featured) -

• Anagog
• Arundo
• Autoplant Systems India Pvt. Ltd.
• AWS
• C3 IoT
• GE
• Google
• Hitachi
• IBM
• Imagimob
• Kairos
• Microsoft
• Oracle
• PTC
• Salesforce
• SAP
• SAS
• Softweb Solutions
• Thingstel
• Uptake

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