PUBLISHER: The Business Research Company | PRODUCT CODE: 1999553
PUBLISHER: The Business Research Company | PRODUCT CODE: 1999553
AI in automotive and transportation involves integrating artificial intelligence technologies into vehicles and transportation systems to enhance safety, efficiency, and user satisfaction. This integration empowers vehicles with intelligence, enabling functionalities such as self-driving capabilities, predictive maintenance, and personalized user experiences.
The primary offerings in AI for automotive and transportation comprise hardware and software components. Hardware encompasses the physical elements of vehicles and infrastructure, including sensors, processors, and computing units, utilized for data collection and processing in AI applications. This hardware incorporates various technologies such as machine learning, natural language processing, computer vision, context-aware computing, among others. Its applications span human-machine interfaces, driver monitoring, driver or identity authentication, autonomous driving processing chips, and intelligent traffic management systems.
Note that the outlook for this market is being affected by rapid changes in trade relations and tariffs globally. The report will be updated prior to delivery to reflect the latest status, including revised forecasts and quantified impact analysis. The report's Recommendations and Conclusions sections will be updated to give strategies for entities dealing with the fast-moving international environment.
Tariffs are affecting the AI in automotive and transportation market by increasing the cost of imported sensors, AI processors, LiDAR systems, connectivity modules, and embedded computing hardware. Automotive manufacturers in North America and Europe are particularly impacted due to reliance on imported semiconductor components, while Asia-Pacific suppliers face export pricing pressure. These tariffs are raising system integration costs and slowing AI feature deployment. However, they are also accelerating localization of chip manufacturing, regional software development, and innovation in cost-optimized AI mobility platforms.
The ai in automotive and transportation market research report is one of a series of new reports from The Business Research Company that provides ai in automotive and transportation market statistics, including ai in automotive and transportation industry global market size, regional shares, competitors with a ai in automotive and transportation market share, detailed ai in automotive and transportation market segments, market trends and opportunities, and any further data you may need to thrive in the ai in automotive and transportation industry. This ai in automotive and transportation market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenario of the industry.
The ai in automotive and transportation market size has grown rapidly in recent years. It will grow from $14.17 billion in 2025 to $16.96 billion in 2026 at a compound annual growth rate (CAGR) of 19.7%. The growth in the historic period can be attributed to advanced driver assistance systems adoption, sensor integration in vehicles, automotive digitization, growth of embedded computing, safety feature demand.
The ai in automotive and transportation market size is expected to see rapid growth in the next few years. It will grow to $31.31 billion in 2030 at a compound annual growth rate (CAGR) of 16.6%. The growth in the forecast period can be attributed to full autonomous vehicle development, smart mobility ecosystems, real-time traffic optimization, vehicle-to-everything integration, AI-driven personalization. Major trends in the forecast period include adoption of autonomous driving algorithms, growth of driver monitoring systems, integration of ai chips in vehicles, expansion of smart traffic solutions, rise of connected vehicles.
The rising demand for autonomous vehicles is expected to drive the growth of the AI in automotive and transportation market in the coming years. Autonomous vehicles are equipped with sensors, cameras, and artificial intelligence technologies that allow them to navigate and operate without human intervention. Demand for these vehicles is increasing due to their potential to enhance safety, improve convenience, and boost efficiency in transportation. AI in autonomous vehicles enables real-time perception of the surroundings through sensor data analysis and decision-making, allowing vehicles to operate safely and efficiently without human input. For example, in December 2024, according to the National Association of Insurance Commissioners, the Insurance Institute for Highway Safety anticipates that 4.5 million self-driving vehicles will be on U.S. roads by 2030. Therefore, the growing demand for autonomous vehicles is fueling the AI in automotive and transportation market.
Key players in the AI in automotive and transportation sector are innovating technologically advanced products, such as vehicle search tools, to gain a competitive edge. Vehicle search tools, comprising electronic devices or software, diagnose, reprogram, and interface with vehicle control modules in the automotive and transportation industries. For example, in February 2024, Rodo, a US-based automotive technology company, introduced an AI-powered vehicle search tool. This groundbreaking solution transforms vehicle searches, offering unmatched convenience and simplicity by providing customers with precise insights into competitively priced vehicles online. It delivers instant, personalized results and competitive pricing, replicating the in-store interaction between customers and salespersons. Leveraging its AI technology, the platform addresses specific customer queries, ensuring immediate results and offering a smarter, faster vehicle discovery experience.
In January 2024, Stellantis N.V., a Netherlands-based automobile corporation, acquired artificial intelligence and machine learning technology, along with intellectual property rights and patents, from CloudMade for an undisclosed sum. Through this acquisition, Stellantis aims to reinforce its software strategy and expedite the development of its STLA smart cockpit, striving to create intelligent mobility solutions swiftly and flexibly to digitally integrate vehicles and drivers. CloudMade, a UK-based provider of AI in automotive and transportation, adds strategic value to Stellantis' objectives.
Major companies operating in the ai in automotive and transportation market report include Alphabet Inc., Toyota Motor Corporation, Microsoft Corporation, Bayerische Motoren Werke AG, Robert Bosch GmbH, Tesla Inc., Siemens AG, Intel Corporation, International Business Machines Corporation (IBM), AUDI AG, Denso Corporation, Qualcomm Technologies Inc., Continental AG, Uber Technologies Inc., Micron Technology Inc., Volvo Cars, NVIDIA Corporation, Valeo SA, Harman International, Scania AB, Argo AI LLC, CarVi Inc., Arbe Robotics Ltd., Visteon Corporation
North America was the largest region in the AI in automotive and transportation market in 2025. The regions covered in the ai in automotive and transportation market report include Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.
The countries covered in the ai in automotive and transportation market report include Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Taiwan, Russia, South Korea, UK, USA, Canada, Italy, Spain
The AI in automotive and transportation market consists revenues earned by entities by providing services such as smart navigation, traffic management, fleet management, and vehicle diagnostics. The market value includes the value of related goods sold by the service provider or included within the service offering. The AI in automotive and transportation market also includes of sales of advanced driver assistance systems, in-vehicle infotainment systems, predictive maintenance solutions, traffic management systems, and energy management systems. Values in this market are 'factory gate' values, that is the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.
The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD unless otherwise specified).
The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.
AI In Automotive And Transportation Market Global Report 2026 from The Business Research Company provides strategists, marketers and senior management with the critical information they need to assess the market.
This report focuses ai in automotive and transportation market which is experiencing strong growth. The report gives a guide to the trends which will be shaping the market over the next ten years and beyond.
Where is the largest and fastest growing market for ai in automotive and transportation ? How does the market relate to the overall economy, demography and other similar markets? What forces will shape the market going forward, including technological disruption, regulatory shifts, and changing consumer preferences? The ai in automotive and transportation market global report from the Business Research Company answers all these questions and many more.
The report covers market characteristics, size and growth, segmentation, regional and country breakdowns, total addressable market (TAM), market attractiveness score (MAS), competitive landscape, market shares, company scoring matrix, trends and strategies for this market. It traces the market's historic and forecast market growth by geography.
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