Industry fueled by advancements in autonomous vehicles and AI-driven analytics. With a projected CAGR of 15.3%, demand for intelligent systems is rising along with in-vehicle data needs.
Automotive Artificial Intelligence (AI) Market
Dublin, Sept. 01, 2025 (GLOBE NEWSWIRE) -- The "Automotive AI Market by Offerings (Compute, Memory, Software), Level of Autonomy (L1, L2, L3, L4, L5), Technology (Deep Learning, ML, Computer Vision, Context-aware Computing, NLP), Application (ADAS, Infotainment, Telematics) - Global Forecast to 2030" has been added to ResearchAndMarkets.com's offering.
The report segments the automotive AI market based on offerings (hardware, software), architecture types, autonomy levels, technologies, and applications like ADAS and infotainment systems. It covers market drivers, restraints, opportunities, and challenges, offering a thorough view across North America, Europe, Asia-Pacific, and RoW. The study also provides an ecosystem analysis of key players.
The market is composed of leading players such as Tesla, NVIDIA Corporation, Mobileye, Qualcomm Technologies, Advanced Micro Devices, and more. Comprehensive competitive analysis includes profiles, recent developments, and market strategies of these companies.
The automotive AI market is anticipated to grow significantly, expanding from USD 18.83 billion in 2025 to USD 38.45 billion by 2030, at a CAGR of 15.3%. This growth is largely driven by the advent of autonomous vehicles that leverage AI for key functionalities such as perception, navigation, and decision-making in real time. The increasing levels of autonomy in the automotive industry are augmenting the demand for intelligent systems. Moreover, as in-vehicle data proliferates through sensors, cameras, and connected systems, there is an escalating need for AI-driven analytics to boost safety, efficiency, and personalization.
Hardware Segment on a High Growth Trajectory
The hardware segment is expected to experience the highest growth rate within the automotive AI market. This surge is attributed to the integration of advanced sensors, AI accelerators, and high-performance computing chips essential for autonomous driving systems and intelligent features in vehicles. As cars transform into data-heavy platforms, there is an escalating demand for robust hardware infrastructure, including GPUs, ASICs, FPGAs, and edge AI chips, designed to process real-time data from diverse sensors. Furthermore, the shift towards software-defined vehicles is propelling automakers to implement powerful domain controllers and centralized computing systems.