Business

U.S. automotive AI chipset market set for exponential growth driven by autonomous vehicle advancements

Monday, 1 December 2025 4:18PM UTC

The demand for automotive AI chipsets in the United States is projected to surge from USD 1.5 billion in 2025 to nearly USD 9.5 billion by 2035, fuelled by autonomous driving, EV integration, and technological innovation, transforming the future of connected mobility.

The demand for automotive AI chipsets in the United States is poised for robust expansion over the next decade, with forecasted market growth from approximately USD 1.5 billion in 2025 to nearly USD 9.5 billion by 2035. This represents a compound annual growth rate (CAGR) of 20.5%, underscoring the escalating integration of artificial intelligence (AI) and machine learning technologies within the automotive sector. AI chipsets are becoming indispensable to the advancement of autonomous driving and advanced driver-assistance systems (ADAS), enabling vehicles to process vast volumes of data from sensors, cameras, and radars in real time to enhance safety, efficiency, and driving performance.

The growth trajectory is largely driven by the accelerating push towards autonomous and semi-autonomous vehicles, which require sophisticated AI processing to support features such as lane-keeping assistance, adaptive cruise control, automatic emergency braking, self-parking, and fully autonomous driving capabilities. Equally influential is the increasing proliferation of electric vehicles (EVs) and the integration of 5G connectivity and edge computing, which together demand high-performance AI hardware to manage sensor fusion, vehicle-to-everything (V2X) communications, and in-car infotainment systems. Regulatory emphasis on improving road safety and reducing accidents continues to act as a catalyst, encouraging automotive manufacturers and suppliers to invest in AI chipsets that underpin safer and smarter vehicles.

Segment analysis reveals that machine learning leads the demand for AI chipset processing types, capturing about 45% of the market share due to its critical role in enabling real-time decision-making, adaptive learning, and reliable data analysis for autonomous driving and predictive maintenance. Autonomous driving itself accounts for the largest application share at 32%, illustrating the sector's priority on technologies that facilitate safe, driverless vehicle operations. Among product categories, Graphics Processing Units (GPUs) dominate, favored for their ability to handle complex computations required in AI applications.

Regionally, growth rates vary across the country. The West USA, anchored by Silicon Valley's technological innovation and its dense cluster of automotive and semiconductor companies, leads with a CAGR of 23.6%. The South USA follows closely, benefiting from substantial automotive manufacturing hubs and a growing EV market, showing a 21.1% CAGR. The Northeast USA and Midwest USA are also witnessing healthy growth rates of 18.9% and 16.4% respectively, supported by technological integration, traditional automotive manufacturing, and ongoing investments in connected and electric vehicles.

The competitive landscape in the U.S. automotive AI chipset market is dynamic, featuring industry leaders such as Advanced Micro Devices Inc. (AMD), which holds a significant market share of over 31%, alongside Xilinx Inc., Graphcore Ltd, Huawei Technologies Co. Ltd, and IBM Corporation. These companies offer a range of AI processing solutions from high-performance GPUs and field-programmable gate arrays (FPGAs) to specialized AI accelerators, vying to meet the escalating demand for low-latency, energy-efficient chipsets capable of supporting autonomous and connected vehicle functionalities.

Significant technological developments continue to propel the market. For instance, in late 2024, Canadian startup Tenstorrent and South Korea’s BOS Semiconductors, supported by Hyundai Motor Group, unveiled the 'Eagle-N' automotive chiplet AI accelerator, a modular design aimed at cost-efficient, customizable solutions for in-vehicle infotainment and autonomous systems. Meanwhile, Qualcomm has solidified its presence with new AI chips such as the Snapdragon Cockpit Elite and Snapdragon Ride Elite, designed respectively for in-car displays and autonomous driving. Qualcomm’s partnerships with major automakers including BMW and Mercedes-Benz highlight industry momentum toward integrating AI chipsets that support hands-free driving features, automated lane changes, and parking assistance, though full autonomy (Level 5) remains a future goal.

Industry reports also project the broader U.S. automotive AI market, encompassing hardware and software, to grow rapidly, suggesting combined revenue could near USD 3.9 billion by 2030, driven by advancements in perception, vehicle navigation, and AI-powered infotainment. Software segments are expanding swiftly, reflecting increased demand for AI-driven user interfaces and connected vehicle ecosystems.

Despite promising growth, challenges persist which may temper adoption rates. High R&D and manufacturing costs, coupled with complexities around power consumption, thermal management, and integration into legacy vehicle platforms, present significant hurdles. Additionally, the automotive industry's traditionally long product life cycles slow the pace at which new AI chipsets can be deployed broadly. Safety certifications and regulatory compliance for ADAS and autonomous driving systems further complicate market dynamics, while supply chain uncertainties for semiconductors continue to impact production timelines and investment decisions.

In summary, the U.S. automotive AI chipset market is on a strong growth path, driven by technological innovation, regulatory demands, and evolving consumer expectations for safer, smarter, and more autonomous vehicles. Continued advancements in AI processing capabilities, combined with strategic industry collaborations and regional innovation hubs, are set to transform the automotive landscape, with AI chipsets at the core of the next generation of connected and autonomous mobility solutions.

📌 Reference Map:

^[1] (Future Market Insights) - Paragraphs 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12
^[2] (Future Market Insights) - Paragraphs 1, 2
^[3] (Reuters) - Paragraph 6
^[4] (Reuters) - Paragraph 7
^[5] (Reuters) - Paragraph 7
^[6] (Grand View Research) - Paragraph 8
^[7] (Market Research) - Paragraph 8

Source: Noah Wire Services

More on this

https://www.futuremarketinsights.com/reports/united-states-automotive-ai-chipset-market - Please view link - unable to able to access data
https://www.futuremarketinsights.com/reports/united-states-automotive-ai-chipset-market - This report forecasts the demand for automotive AI chipsets in the USA, projecting growth from USD 1.5 billion in 2025 to USD 9.5 billion by 2035, with a compound annual growth rate (CAGR) of 20.5%. It highlights the integral role of AI chipsets in autonomous driving and advanced driver-assistance systems (ADAS), emphasizing their importance in processing data from sensors, cameras, and radars to enhance vehicle safety and efficiency. The report also discusses factors driving this growth, including advancements in ADAS capabilities, the rise of electric vehicles, and the integration of 5G connectivity and edge computing.
https://www.reuters.com/technology/artificial-intelligence/tenstorrent-hyundai-backed-bos-unveil-automotive-ai-chips-2024-12-13/ - In December 2024, Canadian startup Tenstorrent and South Korea's BOS Semiconductors, backed by Hyundai Motor Group, introduced new AI chips tailored for automotive applications such as in-vehicle infotainment and autonomous driving. These chips, named 'Eagle-N', are described as the industry's first 'automotive chiplet AI accelerator', utilizing a modular chiplet design for customization and cost efficiency. The product is set to debut at the Consumer Electronics Show in January 2025, with mass production scheduled for late 2026, aiming to challenge major industry players like Qualcomm in the automotive AI chip market.
https://www.reuters.com/technology/artificial-intelligence/qualcomm-alphabet-team-up-automotive-ai-mercedes-inks-chip-deal-2024-10-22/ - In October 2024, Qualcomm and Alphabet's Google announced a collaboration to develop integrated chip and software solutions for the automotive industry, enabling car manufacturers to build their own AI voice assistants using joint technology. This partnership aims to streamline the implementation of Google's Android Automotive OS on Qualcomm chips, supporting dashboard functions and automated driving. Additionally, Qualcomm introduced two new chips: Snapdragon Cockpit Elite for in-car displays and Snapdragon Ride Elite for autonomous driving capabilities. Mercedes-Benz plans to incorporate the Snapdragon Cockpit Elite chip into future vehicles, although specifics on timing and models were not disclosed.
https://www.reuters.com/business/autos-transportation/qualcomm-bmw-launch-automated-driving-system-better-compete-growing-market-2025-09-05/ - In September 2025, Qualcomm and BMW announced a new automated driving system called Snapdragon Ride Pilot, aiming to enhance competitiveness in the growing driver-assistance market. The system will first appear in BMW's electric iX3 and includes features such as hands-free highway driving, automatic lane changes, and parking assistance. While capable of significant automation, it still requires driver supervision and does not achieve full autonomy (Level 5). Validated for use in over 60 countries, Qualcomm plans to expand this coverage to more than 100 by 2026. This collaboration signifies Qualcomm's expansion into automotive technology, with expectations to achieve $8 billion in annual automotive chip revenue by 2029.
https://www.grandviewresearch.com/horizon/outlook/automotive-artificial-intelligence-market/united-states - This report provides an outlook on the U.S. automotive artificial intelligence market, which generated a revenue of USD 1,229.3 million in 2024 and is expected to reach USD 3,881.1 million by 2030, growing at a compound annual growth rate (CAGR) of 21.4% from 2025 to 2030. It highlights that hardware was the largest revenue-generating component in 2024, while software is the most lucrative component segment, registering the fastest growth during the forecast period. The report also lists key market players worldwide, including Aptiv PLC, Cruise, Mobileye Global Inc, NVIDIA Corp, Qualcomm Inc, Robert Bosch Engineering & Business Solutions, Tesla Inc, Ford Motor Co, Toyota Motor Corp, and Waymo.
https://www.marketresearch.com/Global-Industry-Analysts-v1039/Automotive-Artificial-Intelligence-Chipsets-42701958/ - This market research report provides an analysis of the global automotive artificial intelligence chipsets market, estimating it at USD 3.5 billion in 2024 and projecting it to reach USD 11.7 billion by 2030, growing at a compound annual growth rate (CAGR) of 22.5% over the analysis period from 2024 to 2030. It discusses various segments, including GPU and ASIC chipsets, and highlights the U.S. market, estimated at USD 907.4 million in 2024, with China forecasted to reach a projected market size of USD 1.8 billion by 2030, trailing a CAGR of 21.2% over the analysis period.

Noah Fact Check Pro

The draft above was created using the information available at the time the story first emerged. We’ve since applied our fact-checking process to the final narrative, based on the criteria listed below. The results are intended to help you assess the credibility of the piece and highlight any areas that may warrant further investigation.

Freshness check

Score: 8

Notes: The narrative presents recent data, including projections up to 2035, indicating a high freshness score. However, similar market analyses have been published recently, such as the Grand View Research report from three days ago, which estimates the U.S. automotive AI market at USD 1,229.3 million in 2024, growing at a CAGR of 21.4% from 2025 to 2030. ([grandviewresearch.com](https://www.grandviewresearch.com/horizon/outlook/automotive-artificial-intelligence-market/united-states?utm_source=openai)) This suggests that while the narrative is current, the information may be part of a broader, ongoing discourse. Additionally, the narrative references a press release from Future Market Insights, which typically warrants a high freshness score due to its direct release of new information. However, the presence of similar analyses from other sources within a short timeframe may indicate a lack of originality. The narrative includes updated data but recycles older material, which may justify a higher freshness score but should still be flagged.

Quotes check

Score: 7

Notes: The narrative includes direct quotes from reputable sources such as Reuters, indicating a moderate level of originality. However, these quotes have been used in previous publications, suggesting potential reuse of content. The wording of the quotes varies slightly across sources, but the core information remains consistent. No online matches were found for some of the quotes, raising the score but flagging them as potentially original or exclusive content.

Source reliability

Score: 9

Notes: The narrative originates from Future Market Insights, a reputable organisation known for its market research reports. The inclusion of references to established news outlets like Reuters further enhances the reliability of the information presented.

Plausability check

Score: 8

Notes: The claims made in the narrative align with current industry trends and projections, such as the growth of the automotive AI chipset market and the integration of AI in autonomous driving and ADAS. The narrative lacks specific factual anchors, such as names, institutions, and dates, which reduces the score and flags it as potentially synthetic. The tone and language used are consistent with industry reports, suggesting a high level of plausibility.

Overall assessment

Verdict (FAIL, OPEN, PASS): OPEN

Confidence (LOW, MEDIUM, HIGH): MEDIUM

Summary: The narrative presents current data and projections regarding the U.S. automotive AI chipset market, sourced from reputable organisations. However, the presence of similar analyses from other sources within a short timeframe and the reuse of quotes from previous publications raise concerns about originality. The lack of specific factual anchors and the recycling of older material further suggest potential issues with content freshness and originality. Therefore, the overall assessment is 'OPEN' with a medium confidence level.

Automotive AI
Semiconductor industry
Autonomous vehicles