The global AI in IoT market size was valued at USD 1.92 billion in 2022. It is projected to reach USD 18.37 billion by 2031, growing at a CAGR of 28.53% during the forecast period (2023-2031).
Artificial intelligence (AI) is the simulation of human intellectual functions by machines, particularly computer systems, and is frequently applied to speech recognition, machine learning, and machine vision. A system of interconnected computing devices, mechanical and digital machines, or other items having unique IDs and the capacity to communicate data across a network without requiring human-to-human or human-to-computer interaction is known as the Internet of Things (IoT). Using AI, IoT builds sophisticated machines that mimic human behavior and assist in making decisions with little to no human input. IoT technology is the foundation for different enterprises to undergo a digital transformation, enabling them to improve current operations by developing and monitoring new business models. IoT has been viewed as the primary enabler in boosting digital transformation and uncovering operational efficiencies by businesses and service providers.
The growth of big data, along with the quickly rising volume and complexity of data, is being driven by the expanding mobile traffic, cloud computing traffic, and the development and use of technologies like IoT and AI. Big data analytics is an effective method of delivering data, providing insightful and practical knowledge from massive amounts of data. Organizations can profit from sizeable predictive analytics in several ways, including operations, marketing, risk assessment, and raid detection. For example, in a study in 2020, about 90% of business professionals and enterprise analytics mentioned that data and analytics are critical to their organization's digital transformation initiatives. Data and analytics are increasingly becoming key components for enterprises.
Businesses can better understand and use trends by using data generated through IoT, which is then incorporated into the decision-making process to improve product design and development. Data management practices allow these firms to identify faults, evaluate performance, and quickly obtain measurements. All of these provide perceptions into how products are used, which help identify areas needing improvement and enhance current product versions.
Numerous IoT devices increase the surface area of a network, increasing the number of potential attack vectors. AIoT could launch an active attack on a network from a single connected, unprotected device. Attacks on vital infrastructure in industrial space might cause enormous losses. Therefore, hindering the growth of the market.
AI is much more effective than humans at identifying underlying patterns in the massive amounts of data that IoT devices process. This capability can be improved by AI with machine learning by foreseeing the operational circumstances and adjustments required for better results. As natural language processing advances, it becomes easier for humans and machines to communicate. By enabling better data processing and analytics, IoT can improve new or existing products and services. IoT would generate enormous amounts of data as a result of the quick expansion of devices and sensors. These data would be extremely beneficial for a number of different things, including predicting natural disasters, accidents, and crimes; assisting doctors in receiving real-time information from medical equipment; optimizing productivity across industries; performing predictive maintenance on equipment and machinery; building smart homes with connected appliances; and facilitating crucial communication between self-driving cars.
At AI Day in September 2022, Tesla (TSLA) unveiled a prototype of its Optimus humanoid robot. Optimus took about a dozen shaky steps onto the stage before moving slowly and swaying on the dance floor. According to Musk, the humanoid robot Optimus could be released in 2019. Musk claimed that Optimus could assist with the labor shortages in factories in January 2022.
Study Period | 2019-2031 | CAGR | 28.53% |
Historical Period | 2019-2021 | Forecast Period | 2023-2031 |
Base Year | 2022 | Base Year Market Size | USD 1.92 Billion |
Forecast Year | 2031 | Forecast Year Market Size | USD 18.37 Billion |
Largest Market | North America | Fastest Growing Market | Asia Pacific |
The global AI in IoT market is bifurcated into four regions, namely North America, Europe, Asia-Pacific, and LAMEA.
North America is the most significant shareholder in the global AI in IoT market and is expected to grow at a CAGR of 27.5% during the forecast period. North America is one of the primary markets for AI and IoT. One of the factors supporting the expansion of the market in this region is the widespread use of both technologies in various sectors, including manufacturing, retail, healthcare, automotive and transportation, and others. It is one of the top regions for research into creating IoT and AI applications for new end-use sectors. The region has been at the forefront of the transformation that has seen autos become more and more software-oriented, owing to the high-tech ecosystem the nation has established. IoT devices may evaluate data, make judgments, and take action on those conclusions without human intervention when AI is combined with IoT. One example of how AI and IoT might function together is in self-driving automobiles like those made by Tesla. Self-driving cars can now make predictions about the actions of other vehicles and people under different conditions because of AI.
Asia-Pacific is the second-largest region in the market and is estimated to grow at a CAGR of 29.25%. Technological innovations like AI and IoT have been widely adopted throughout Asia-Pacific. Due to the difficulty in rebuilding existing automation systems and machine investments, the market in the region's developing nations has a significant advantage in implementing industrial automation. IoT spending is heavily concentrated in Asia-Pacific, with South Korea and Singapore predicted to be among the top countries worldwide. The Organization for Economic Cooperation and Development reports that South Korea has the most internet-connected items per habitat internationally. Asia-Pacific has a significant manufacturing sector. As a substantial contributor to the global economy, China's economy is rapidly changing due to rising labor prices and the unsustainable nature of the traditional migrant worker model. These trends have forced the economy to incorporate automation into its industrial procedures.
The industries anticipated to adopt IoT in Europe include transportation, healthcare, housing and hospitality, manufacturing, and retail. As IoT adds value to these industries, demand for the invention of IoT chips and the modernization of already-existing chip-based technologies would rise. The adoption of IoT in the European automotive industry is fueled by substantial financial investments made by well-known vendors and a growing interest in solutions for improving fuel economy and traffic safety. IoT penetration is generally relatively high in Sweden, France, Italy, Germany, and Luxembourg. These nations' automobile industries are embracing IoT technology quickly as well.
The LAMEA region is anticipated to grow at a moderate rate, owing to the technological advancements in UAE and Saudi Arabia. The economic growth in countries of South America such as Brazil, Argentina, and Chile is also contributing to the growth of AI in IoT in the region. The UAE has adopted digital technologies to diversify its economy toward a knowledge-based one, demonstrate the country's capacity for innovation, and demonstrate its viability as a major global economic force. The UAE Government launched its National Strategy for Artificial Intelligence in 2017 as part of the next stage of its national development with the goal of making the UAE a global leader in AI through investments in the people and sectors that are essential to its prosperity. Resources and energy, logistics and transportation, cybersecurity, tourism and hospitality, and healthcare are prioritized sectors for AI in the UAE with the goal of boosting industrial productivity by 30% by 2031.
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The global AI in IoT market is segmented by component and end-user.
Based on components, the global market is bifurcated into Platforms, Services, and Software.
The software segment is the highest contributor to the market and is expected to grow at a CAGR of 27.89% during the forecast. It is further sub-segmented into Data Management, Network Bandwidth Management, Real-time Streaming Analytics, Remote Monitoring, Security, and Edge Solutions. Among these segments, data management acquires a significant share of the market. IoT data management is frequently used to forecast wear and tear on connected assets and infrastructure.
The Platform segment is sub-segmented into application management, connectivity Management, and Device Management. Application management occupies a significant share and includes application functionality, upgrades, and version control. It improves organizations to make better decisions efficiently and effectively
Based on end-user, the global market is bifurcated into banking, financial services, & insurance, it & telecom, energy & utilities, healthcare, and manufacturing.
The manufacturing segment is the highest contributor to the market and is expected to grow at a CAGR of 28.43% during the forecast period. Manufacturers are working harder than ever to develop fully automated data management solutions. Manufacturing IoT systems with AI capabilities can effectively handle production quality control, monitoring and optimizing equipment performance, and human-to-machine communication. Significantly shorter product cycles are possible because of more rapid and effective supply chain and production processes. The objective is to address common industrial difficulties while greatly accelerating future Industrial IoT advancements, reducing time to value, and driving production efficiencies. The underlying platform will continue to develop to embrace new technologies, such as those in analytics, artificial intelligence, and digital feedback loops, by production requirements.
The banking, financial services, and insurance segment is expected to grow at a significant rate. The banking, financial services, & insurance industries use AI-based IoT solutions primarily for fraud detection, product development, insurance processing, and operations. Technologies based on artificial intelligence (AI) have the potential to change the BFSI sector significantly. These businesses' implementation of AIoT can help them achieve goals like increasing customer experience, cost and efficiency optimization, providing personalized service, and accelerating the time to market for new products. AIoT is typically utilized in the banking industry for ATM fraud detection and other unlawful actions. To identify fraudulent ATM activity and report them right away to the bank's security staff or even law enforcement agencies, companies like IGZY built their IoT sensors or cameras.