Automotive AI Chipset Market

Automotive AI Chipset Market Outlook from (2024 to 2034)

The automotive AI chipset market is projected to be worth USD 3.5 billion in 2024. The market is anticipated to reach USD 25.9 billion by 2034. The market is further expected to surge at a CAGR of 22.1% during the forecast period 2024 to 2034.

Key Market Trends and Highlights

• The increasing interest and investment in autonomous vehicles are expected to drive the demand for AI chipsets in the automotive industry. AI plays a crucial role in enabling features such as object recognition, decision making, and navigation in autonomous vehicles.
• The automotive industry is witnessing a growing integration of AI in ADAS to enhance safety and improve driving experience. AI chipsets are essential components for processing and analyzing data from sensors, cameras, and other sources in real time.
• The trend towards connected vehicles, which communicate with each other and with infrastructure, requires robust AI capabilities. AI chipsets can support applications such as predictive maintenance, in car personalization, and real time traffic management.
• AI chipsets play a role in enhancing in car infotainment systems, providing advanced features such as voice recognition, natural language processing, and personalized content recommendations, contributing to an improved user experience.

Attributes	Key Insights
Automotive AI Chipset Market Estimated Size in 2024	USD 3.5 billion
Projected Market Value in 2034	USD 25.9 billion
Value-based CAGR from 2024 to 2034	22.1%

2019 to 2023 Historical Analysis vs. 2024 to 2034 Market Forecast Projections

The scope for automotive AI chipset rose at a 18.4% CAGR between 2019 and 2023. The global market for automotive AI chipset is anticipated to grow at a moderate CAGR of 22.1% over the forecast period 2024 to 2034.

Report Attributes	Details
Market Value in 2019	USD 1.5 billion
Market Value in 2023	USD 2.9 billion
CAGR from 2019 to 2023	18.4%

The automotive AI chipset market experienced a significant increase in the adoption of automotive AI chipsets during the historical period from 2019 to 2023. There was a significant focus on the development and testing of autonomous vehicles, driving the demand for advanced AI chipsets to enable functions such as perception, decision making, and control.

The automotive industry also witnessed a notable shift towards electric vehicles during this period. AI chipsets became crucial in managing energy efficiency, battery optimization, and enhancing the overall performance of electric vehicles.

Vehicles became more connected during this period, leading to a surge in data generation. AI chipsets played a role in processing and analyzing this data, supporting applications such as telematics, predictive maintenance, and in car infotainment.

The market is expected to witness the growth of urban air mobility during the forecast period, where AI chipsets will play a pivotal role in developing AI driven systems. The systems will focus on navigation, traffic management, and safety for autonomous flying vehicles.

The widespread deployment of 5G technology in the forecast period is poised to enhance vehicle connectivity. The improvement will facilitate more advanced AI applications in vehicles, supporting real time data processing and communication.

AI chipsets are expected to play a crucial role in advancing predictive maintenance systems. The advancement aims to reduce downtime, extend vehicle lifespan, and enhance overall maintenance efficiency.

Automotive AI Chipset Market Key Drivers

• The increasing adoption of electric vehicles provides opportunities for AI chipsets in optimizing battery management, enhancing energy efficiency, and enabling smart charging solutions.
• There is an increased focus on cybersecurity, with the growing complexity of automotive systems. AI chipsets can be employed to enhance the security of connected and autonomous vehicles, protecting them from potential cyber threats.
• Customized AI chipsets designed for specific automotive applications, such as autonomous driving or in cabin monitoring, are anticipated to become more prevalent, which allows manufacturers to tailor solutions to their specific needs, improving overall system performance.
• Vehicle to everything communication, encompassing vehicle to vehicle and vehicle to infrastructure communication, relies on AI for efficient data exchange and decision making. AI chipsets are crucial in supporting V2X communication systems for enhanced safety and traffic management.

Challenges in the Automotive AI Chipset Market

• The research, development, and implementation of advanced AI chipsets involve substantial costs. Smaller automotive companies and startups may find it challenging to invest in such technology, limiting their ability to compete with larger players.
• The increasing amount of data generated by connected vehicles raises concerns about data security and privacy. Addressing these concerns and ensuring secure data transmission and storage pose challenges for AI chip manufacturers and automotive companies.
• The absence of standardized protocols for AI integration in vehicles can lead to compatibility issues and hinder seamless communication between different systems. Standardization efforts are essential to ensure interoperability and ease of integration.
• The development of sophisticated AI chipsets requires a skilled workforce. The shortage of talent in artificial intelligence, machine learning, and semiconductor design can act as a bottleneck, slowing down innovation in the automotive AI chipset market.

Country-wise Insights

The below table showcases revenues in terms of the top 5 leading countries, spearheaded by Australia and Japan. The countries are expected to lead the market through 2034.

Forecast CAGRs from 2024 to 2034

The United States	19.9%
Germany	21.6%
Japan	23.3%
China	22.6%
Australia	26.6%

Rising Adoption of Autonomous Vehicles Driving the Market in the United States

The automotive AI chipset market in the United States expected to expand at a CAGR of 19.9% through 2034. The United States has been a significant hub for the development and testing of autonomous vehicles. The growth of AI chipsets is closely tied to the advancements in autonomous driving technologies, with various companies investing in self driving vehicle projects.

The presence of major technology companies, such as Google, Tesla, Apple, and traditional automakers like General Motors, Ford, and others, fosters a competitive environment for AI driven technologies, which contributes to the development and adoption of AI chipsets.

Adoption of Electric Vehicles to Accelerate Market Growth in Japan

The automotive AI chipset market in Japan is anticipated to expand at a CAGR of 23.3% through 2034. The automakers in Japan have a strong tradition of innovation and technological advancements. The continuous pursuit of innovation in vehicle design, performance, and features contributes to the adoption of AI chipsets for various applications.

Japan has been promoting the adoption of electric vehicles to address environmental concerns. AI chipsets play a crucial role in optimizing electric powertrains, battery management, and enhancing the intelligence of electric vehicles.

Strong Automotive Manufacturing Base Fueling the Market in Germany

The automotive AI chipset market in Germany is poised to expand at a CAGR of 21.6% through 2034. Germany is home to several major automotive manufacturers, including Volkswagen, BMW, Daimler, and Audi. The strong automotive manufacturing base in the country drives demand for advanced technologies, including AI chipsets, to enhance vehicle capabilities.

Government initiatives and policies in Germany support innovation in the automotive sector. Funding, incentives, and regulatory support encourage the development and adoption of AI driven technologies, including AI chipsets.

Rise of Mobility as a Service Spearhead the Market in China

Automotive AI chipset trends in China are taking a turn for the better. A 22.6% CAGR is forecast for the country from 2024 to 2034. The cities in China are actively exploring smart city initiatives, and intelligent transportation systems are key components. AI chipsets contribute to the development of smart traffic management, vehicle to everything communication, and other smart city solutions.

The concept of Mobility as a Service is gaining traction in China. AI chipsets play a role in the development of intelligent and connected mobility solutions, including ride sharing, autonomous taxis, and other innovative transportation services.

Connected Car Technologies Driving the Demand in Australia

The automotive AI chipset market in Australia is anticipated to expand at a CAGR of 26.6% through 2034. The growth of connected car technologies, which rely on AI for communication and data processing, is expected to contribute to the automotive AI chipset Market in Australia. Features such as in car connectivity, navigation, and real time information are becoming more prevalent.

Innovations in HMI, including AI driven interfaces, gesture controls, and augmented reality displays, may contribute to the growth of AI chipsets in the country. Improving the user experience is a key aspect of technological advancements in vehicles.

Category-wise Insights

The below table highlights how passenger vehicle segment is projected to lead the market in terms of vehicle type, and is expected to account for a share of 72.0% in 2024.

Based on application, the advanced driver assistance systems segment is expected to account for a share of 35.0% in 2024.

Category	Shares in 2024
Passenger Vehicle	72.0%
Advanced Driver Assistance Systems	35.0%

Passenger Vehicle Segment Claims High Demand for Automotive AI Chipset

Based on vehicle type, the passenger vehicle segment is expected to continue dominating the automotive AI chipset market. The segment is expected to account for a share of 72.0% in 2024.

The development and integration of autonomous driving technologies in passenger vehicles rely heavily on AI chipsets. The chipsets process data from various sensors, cameras, and radars to enable features such as lane keeping, adaptive cruise control, and fully autonomous driving.

Passenger vehicles are incorporating AI driven applications within the cabin to enhance the in car experience, which includes AI powered infotainment systems, voice recognition, personalized settings, and features like natural language processing for human machine interaction.

AI chipsets support real time data processing for effective traffic management and navigation in passenger vehicles, which includes dynamic route planning, traffic prediction, and intelligent navigation systems, contributing to a smoother driving experience.

Advanced Driver Assistance Systems to Hold High Demand for Automotive AI Chipset

In terms of application, the ADAS segment is expected to continue dominating the automotive AI chipset market. The segment is expected to account for a share of 35.0% in 2024.

Many regions have implemented or are considering regulations mandating the inclusion of certain ADAS features in vehicles. For instance, requirements for autonomous emergency braking systems. Compliance with these regulations drives the integration of AI chipsets in vehicles.

Ongoing technological advancements in ADAS, enabled by AI chipsets, contribute to the development of more sophisticated and effective safety features, which includes improved object recognition, adaptive cruise control, and advanced sensor fusion techniques.

AI chipsets play a crucial role in the development of collision avoidance systems. The systems use sensors and AI algorithms to detect potential collisions and take preventive actions, such as alerting the driver or applying brakes autonomously.

Competitive Landscape

The key strategies chosen by large companies include several growth strategies such as technology development, expansion as well and mergers and acquisitions to surge market share, reach and revenue.

• In 2022, Qualcomm unveiled the Snapdragon Ride Vision System, a significant addition to its product lineup. The expansion features a cutting edge, open, scalable, and modular vision software stack, leveraging a state of the art 4 nanometer processing node. The Vision System on Chip is seamlessly integrated with the established Vision Stack, offering a finely tuned implementation of front and surround view cameras.
• In the same year, NVIDIA officially commenced production of the NVIDIA DRIVE Orin™ autonomous vehicle computer. The company also highlighted the adoption of the NVIDIA DRIVE™ platform by new automakers and introduced the next generation of its NVIDIA DRIVE Hyperion™ architecture.
• In 2021, NXP® Semiconductors expanded the S32G Vehicle Network Processors family by introducing the S32G3 Series, featuring four initial devices. The new devices, which are software and pin compatible with the widely adopted S32G2 series launched in Q2 2021, provide up to 2.5 times more applications processing performance, on chip system memory, and networking capabilities compared to the highest performance device in the current S32G2 series.

Report Scope

Attribute	Details
Estimated Market Size in 2024	USD 3.5 billion
Projected Market Valuation in 2034	USD 25.9 billion
Value-based CAGR 2024 to 2034	22.1%
Forecast Period	2024 to 2034
Historical Data Available for	2019 to 2023
Market Analysis	Value in USD billion
Key Regions Covered	North America; Latin America; Western Europe; Eastern Europe; South Asia and Pacific; East Asia; The Middle East & Africa
Key Market Segments Covered	Product, Application, Processing Type, Vehicle Type, Region
Key Countries Profiled	The United States, Canada, Brazil, Mexico, Germany, France, France, Spain, Italy, Russia, Poland, Czech Republic, Romania, India, Bangladesh, Australia, New Zealand, China, Japan, South Korea, GCC countries, South Africa, Israel
Key Companies Profiled	Advanced Micro Devices Inc.; Xilinx Inc.; Graphcore Ltd; Huawei Technologies Co. Ltd; IBM Corporation; Intel Corporation; NVIDIA Corporation; Micron Technology Inc.; Samsung Semiconductor (Samsung Electronics Co. Ltd); Qualcomm; NVIDIA; NXP Semiconductors; Mobileye

Table of Content

• 1. Executive Summary
• 2. Market Overview
• 3. Market Background
• 4. Global Market Analysis 2019 to 2023 and Forecast, 2024 to 2034
• 5. Global Market Analysis 2019 to 2023 and Forecast 2024 to 2034, By Product
  • 5.1. GPU
  • 5.2. ASIC
  • 5.3. FGPA
  • 5.4. CPU
• 6. Global Market Analysis 2019 to 2023 and Forecast 2024 to 2034, By Application
  • 6.1. Advanced Driver Assistance Systems (ADAS)
  • 6.2. Voice & Gesture Recognition
  • 6.3. Infotainment System
  • 6.4. Predictive Maintenance
  • 6.5. Autonomous Driving
  • 6.6. Others
• 7. Global Market Analysis 2019 to 2023 and Forecast 2024 to 2034, By Processing Type
  • 7.1. Computer Vision
  • 7.2. Machine Learning
  • 7.3. Natural Language Processing
• 8. Global Market Analysis 2019 to 2023 and Forecast 2024 to 2034, By Region
  • 8.1. North America
  • 8.2. Latin America
  • 8.3. Western Europe
  • 8.4. Eastern Europe
  • 8.5. South Asia and Pacific
  • 8.6. East Asia
  • 8.7. Middle East and Africa
• 9. North America Market Analysis 2019 to 2023 and Forecast 2024 to 2034, By Country
• 10. Latin America Market Analysis 2019 to 2023 and Forecast 2024 to 2034, By Country
• 11. Western Europe Market Analysis 2019 to 2023 and Forecast 2024 to 2034, By Country
• 12. Eastern Europe Market Analysis 2019 to 2023 and Forecast 2024 to 2034, By Country
• 13. South Asia and Pacific Market Analysis 2019 to 2023 and Forecast 2024 to 2034, By Country
• 14. East Asia Market Analysis 2019 to 2023 and Forecast 2024 to 2034, By Country
• 15. Middle East and Africa Market Analysis 2019 to 2023 and Forecast 2024 to 2034, By Country
• 16. Key Countries Market Analysis
• 17. Market Structure Analysis
• 18. Competition Analysis
  • 18.1. Advanced Micro Devices Inc. (AMD)
  • 18.2. Xilinx Inc.
  • 18.3. Graphcore Ltd
  • 18.4. Huawei Technologies Co. Ltd
  • 18.5. IBM Corporation
  • 18.6. Intel Corporation
  • 18.7. NVIDIA Corporation
  • 18.8. Micron Technology Inc.
  • 18.9. Samsung Semiconductor (Samsung Electronics Co. Ltd)
• 19. Assumptions & Acronyms Used
• 20. Research Methodology