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As per Intent Market Research, the Automotive IoT Market was valued at USD 65.0 billion in 2023 and will surpass USD 231.7 billion by 2030; growing at a CAGR of 19.9% during 2024 - 2030.
The automotive Internet of Things (IoT) market is rapidly evolving, driven by advancements in connectivity, automation, and data analytics. IoT technology in the automotive sector enables real-time communication between vehicles, infrastructure, and users, enhancing safety, efficiency, and convenience. The increasing integration of IoT in vehicles is transforming how automakers design and manufacture vehicles, offering consumers a smarter, more connected driving experience. IoT also facilitates advanced vehicle diagnostics, predictive maintenance, and enhanced navigation systems. As the industry moves towards autonomous driving, IoT plays a central role in enabling vehicle communication and processing the data required for safe and efficient operations.
Moreover, the growth of electric vehicles (EVs) and connected services has accelerated the demand for IoT solutions in the automotive market. The ability to integrate IoT into various vehicle functions, including fleet management, infotainment, and autonomous driving, is driving the market's expansion. As connectivity and data exchange between vehicles and smart cities evolve, the automotive IoT market is poised for rapid growth, with both OEMs and aftermarket suppliers capitalizing on these emerging opportunities.
Connectivity remains the largest technology segment in the automotive IoT market. This subsegment enables real-time data exchange between vehicles, the cloud, and various infrastructure elements, such as traffic lights and road sensors. By allowing vehicles to communicate with each other (V2V) and with infrastructure (V2I), connectivity enhances safety, traffic flow, and fuel efficiency. It also forms the backbone for applications like navigation systems, remote diagnostics, and vehicle tracking. As consumer demand for smart features increases, automakers are adopting more advanced connectivity technologies to improve user experiences, including seamless integration with smartphones, wearable devices, and home automation systems.
The continuous development of 5G technology is further propelling the growth of the connectivity segment. With 5G offering faster and more reliable communication, vehicles can exchange data in real time, enabling features such as autonomous driving, advanced driver-assistance systems (ADAS), and in-vehicle entertainment. The expansion of connected vehicles worldwide ensures that connectivity remains the dominant technology in the automotive IoT market.
Artificial Intelligence (AI) is the fastest-growing technology in the automotive IoT market, largely due to its crucial role in the development of autonomous vehicles. AI enables vehicles to process vast amounts of data from sensors, cameras, and radars, making decisions in real time. AI algorithms help in object detection, path planning, and decision-making, all of which are essential for the safe and efficient operation of autonomous vehicles. As the automotive industry moves towards fully autonomous cars, AI is becoming an indispensable component for advanced driver assistance systems (ADAS) and self-driving technology.
AI is also being increasingly integrated into other aspects of automotive IoT, such as predictive maintenance, where machine learning models analyze data to predict vehicle issues before they become critical. As advancements in AI continue, the technology is expected to further disrupt the automotive industry, enabling more sophisticated, intelligent vehicles that can learn from their environment and improve performance over time.
The vehicle tracking and fleet management application is the largest in the automotive IoT market. As businesses and logistics companies increasingly rely on fleets of vehicles to deliver goods and services, the need for real-time tracking, monitoring, and management has grown significantly. IoT-enabled solutions allow fleet managers to track vehicle locations, monitor driver behavior, and optimize routes, improving operational efficiency and reducing fuel consumption. Additionally, vehicle tracking provides valuable data for maintenance scheduling, improving fleet uptime and reducing costs.
The demand for efficient fleet management is not limited to logistics alone. Commercial fleets in industries like agriculture, construction, and public transportation are adopting IoT solutions to improve their operations. As the IoT infrastructure for vehicle tracking and fleet management becomes more advanced, this application is expected to continue dominating the automotive IoT market.
Passenger vehicles represent the largest vehicle type in the automotive IoT market. The increasing demand for connected and smart features in consumer vehicles, such as in-car entertainment, navigation systems, and advanced driver assistance systems (ADAS), is driving the growth of IoT in passenger cars. Consumers expect a seamless, personalized driving experience, which is facilitated by IoT technologies that integrate vehicle systems with smartphones and home automation devices. Furthermore, as vehicle safety and convenience become paramount, IoT-enabled technologies such as real-time traffic updates, collision warning systems, and remote diagnostics are becoming standard in passenger vehicles.
The widespread adoption of electric vehicles (EVs) is also boosting the demand for IoT solutions, as EVs require enhanced connectivity for functions like battery monitoring and charging station navigation. As the automotive market continues to shift towards more connected and automated passenger vehicles, the demand for IoT technology is expected to remain strong in this segment.
North America is the largest region in the automotive IoT market, driven by the region’s advanced automotive industry and rapid adoption of new technologies. The United States, in particular, is a leader in automotive manufacturing, with a strong presence of both OEMs and technology companies that are advancing IoT integration in vehicles. The region’s infrastructure is also well-suited to support connected vehicle technologies, including the development of 5G networks, which are essential for the growth of IoT-enabled applications like autonomous driving and real-time vehicle communication.
Moreover, North America has witnessed strong consumer demand for smart vehicles equipped with IoT-enabled features, such as telematics, in-vehicle communication systems, and advanced safety features. As the market for connected and autonomous vehicles grows, North America’s automotive IoT market will continue to thrive, supported by both regulatory frameworks and high consumer expectations.
The automotive IoT market is highly competitive, with major players across both technology and automotive industries leading the charge. Leading companies include Bosch, Continental AG, Harman International, Qualcomm, and Ericsson, all of which are investing heavily in IoT innovations for the automotive sector. These companies provide a broad range of IoT solutions, from connectivity platforms to AI-driven autonomous vehicle systems.
As the market evolves, competition is intensifying around the integration of advanced technologies like 5G, AI, and edge computing into vehicle systems. Companies are also forming partnerships with automotive manufacturers to develop IoT solutions tailored to the needs of modern vehicles. In addition to established players, new startups and tech firms are entering the space, providing innovative solutions that push the boundaries of what IoT can achieve in the automotive industry. As a result, companies are focusing on R&D, strategic alliances, and acquisitions to strengthen their positions in this rapidly expanding market.
Report Features |
Description |
Market Size (2023) |
USD 65.0 Billion |
Forecasted Value (2030) |
USD 231.7 Billion |
CAGR (2024 – 2030) |
19.9% |
Base Year for Estimation |
2023 |
Historic Year |
2022 |
Forecast Period |
2024 – 2030 |
Report Coverage |
Market Forecast, Market Dynamics, Competitive Landscape, Recent Developments |
Segments Covered |
Automotive IoT Market by Technology (Connectivity, Edge Computing, Cloud Computing, Artificial Intelligence (AI)), Application (Vehicle Tracking and Fleet Management, In-Vehicle Communication Systems, Autonomous Vehicles, Telematics and Diagnostics, Infotainment Systems), Vehicle Type (Passenger Vehicles, Commercial Vehicles), End-User (Original Equipment Manufacturers (OEM), Aftermarket) |
Regional Analysis |
North America (US, Canada, Mexico), Europe (Germany, France, UK, Italy, Spain, and Rest of Europe), Asia-Pacific (China, Japan, South Korea, Australia, India, and Rest of Asia-Pacific), Latin America (Brazil, Argentina, and Rest of Latin America), Middle East & Africa (Saudi Arabia, UAE, Rest of Middle East & Africa) |
Major Companies |
Aptiv PLC, Autotalks Ltd., Cisco Systems, Inc., Continental AG, Daimler AG, Ford Motor Company, Huawei Technologies Co., Ltd., Intel Corporation, NXP Semiconductors, Qualcomm Technologies, Inc., Robert Bosch GmbH, Samsara Inc., Valeo S.A. |
Customization Scope |
Customization for segments, region/country-level will be provided. Moreover, additional customization can be done based on the requirements |
1. Introduction |
1.1. Market Definition |
1.2. Scope of the Study |
1.3. Research Assumptions |
1.4. Study Limitations |
2. Research Methodology |
2.1. Research Approach |
2.1.1. Top-Down Method |
2.1.2. Bottom-Up Method |
2.1.3. Factor Impact Analysis |
2.2. Insights & Data Collection Process |
2.2.1. Secondary Research |
2.2.2. Primary Research |
2.3. Data Mining Process |
2.3.1. Data Analysis |
2.3.2. Data Validation and Revalidation |
2.3.3. Data Triangulation |
3. Executive Summary |
3.1. Major Markets & Segments |
3.2. Highest Growing Regions and Respective Countries |
3.3. Impact of Growth Drivers & Inhibitors |
3.4. Regulatory Overview by Country |
4. Automotive IoT Market, by Technology (Market Size & Forecast: USD Million, 2022 – 2030) |
4.1. Connectivity |
4.2. Edge Computing |
4.3. Cloud Computing |
4.4. Artificial Intelligence (AI) |
5. Automotive IoT Market, by Application (Market Size & Forecast: USD Million, 2022 – 2030) |
5.1. Vehicle Tracking and Fleet Management |
5.2. In-Vehicle Communication Systems |
5.3. Autonomous Vehicles |
5.4. Telematics and Diagnostics |
5.5. Infotainment Systems |
6. Automotive IoT Market, by Vehicle Type (Market Size & Forecast: USD Million, 2022 – 2030) |
6.1. Passenger Vehicles |
6.2. Commercial Vehicles |
7. Automotive IoT Market, by End-User (Market Size & Forecast: USD Million, 2022 – 2030) |
7.1. Original Equipment Manufacturers (OEM) |
7.2. Aftermarket |
8. Regional Analysis (Market Size & Forecast: USD Million, 2022 – 2030) |
8.1. Regional Overview |
8.2. North America |
8.2.1. Regional Trends & Growth Drivers |
8.2.2. Barriers & Challenges |
8.2.3. Opportunities |
8.2.4. Factor Impact Analysis |
8.2.5. Technology Trends |
8.2.6. North America Automotive IoT Market, by Technology |
8.2.7. North America Automotive IoT Market, by Application |
8.2.8. North America Automotive IoT Market, by Vehicle Type |
8.2.9. North America Automotive IoT Market, by End-User |
8.2.10. By Country |
8.2.10.1. US |
8.2.10.1.1. US Automotive IoT Market, by Technology |
8.2.10.1.2. US Automotive IoT Market, by Application |
8.2.10.1.3. US Automotive IoT Market, by Vehicle Type |
8.2.10.1.4. US Automotive IoT Market, by End-User |
8.2.10.2. Canada |
8.2.10.3. Mexico |
*Similar segmentation will be provided for each region and country |
8.3. Europe |
8.4. Asia-Pacific |
8.5. Latin America |
8.6. Middle East & Africa |
9. Competitive Landscape |
9.1. Overview of the Key Players |
9.2. Competitive Ecosystem |
9.2.1. Level of Fragmentation |
9.2.2. Market Consolidation |
9.2.3. Product Innovation |
9.3. Company Share Analysis |
9.4. Company Benchmarking Matrix |
9.4.1. Strategic Overview |
9.4.2. Product Innovations |
9.5. Start-up Ecosystem |
9.6. Strategic Competitive Insights/ Customer Imperatives |
9.7. ESG Matrix/ Sustainability Matrix |
9.8. Manufacturing Network |
9.8.1. Locations |
9.8.2. Supply Chain and Logistics |
9.8.3. Product Flexibility/Customization |
9.8.4. Digital Transformation and Connectivity |
9.8.5. Environmental and Regulatory Compliance |
9.9. Technology Readiness Level Matrix |
9.10. Technology Maturity Curve |
9.11. Buying Criteria |
10. Company Profiles |
10.1. Aptiv PLC |
10.1.1. Company Overview |
10.1.2. Company Financials |
10.1.3. Product/Service Portfolio |
10.1.4. Recent Developments |
10.1.5. IMR Analysis |
*Similar information will be provided for other companies |
10.2. Autotalks Ltd. |
10.3. Cisco Systems, Inc. |
10.4. Continental AG |
10.5. Daimler AG |
10.6. Ford Motor Company |
10.7. General Motors |
10.8. Huawei Technologies Co., Ltd. |
10.9. Intel Corporation |
10.10. NXP Semiconductors |
10.11. Qualcomm Technologies, Inc. |
10.12. Robert Bosch GmbH |
10.13. Samsara Inc. |
10.14. TomTom International BV |
10.15. Valeo S.A. |
11. Appendix |
A comprehensive market research approach was employed to gather and analyze data on the Automotive IoT Market. In the process, the analysis was also done to analyze the parent market and relevant adjacencies to measure the impact of them on the Automotive IoT Market. The research methodology encompassed both secondary and primary research techniques, ensuring the accuracy and credibility of the findings.
Secondary research involved a thorough review of pertinent industry reports, journals, articles, and publications. Additionally, annual reports, press releases, and investor presentations of industry players were scrutinized to gain insights into their market positioning and strategies.
Primary research involved conducting in-depth interviews with industry experts, stakeholders, and market participants across the E-Waste Management ecosystem. The primary research objectives included:
A combination of top-down and bottom-up approaches was utilized to analyze the overall size of the Automotive IoT Market. These methods were also employed to assess the size of various subsegments within the market. The market size assessment methodology encompassed the following steps:
To ensure the accuracy and reliability of the market size, data triangulation was implemented. This involved cross-referencing data from various sources, including demand and supply side factors, market trends, and expert opinions. Additionally, top-down and bottom-up approaches were employed to validate the market size assessment.