Neuromorphic Chips for Autonomous Vehicles Market Size - By Chip Architecture, By Deployment, Vehicle Category, End Use Analysis, Share, Growth Forecast, 2025 - 2034

Neuromorphic Chips for Autonomous Vehicle Market Size

The global neuromorphic chips for autonomous vehicle market were valued at USD 9.11 billion in 2024. The market is expected to grow from USD 10.91 billion in 2025 to USD 27.43 billion in 2030 and USD 59.16 billion in 2034, growing at a CAGR of 20.7% during the forecast period of 2025-2034, according to Global Market Insights Inc.

• The growing demand for self-driving vehicles has captured the focus for advanced computing solutions capable of processing significant amounts of sensory information instantaneously. Computing devices designed to replicate the brain structure, known as neuromorphic chips, type text faster decisions with lower energy expenditures than conventional processors. Vehicles are now incorporating multiple cameras, LiDAR, and radar sensors for enhanced safety and reliability as the ability to perceive and act with minimal latency on complex information becomes more critical.
   
• The more autonomous and electric vehicles become, the more the concern of efficient energy use and thermal regulation increases. Both GPUs and CPUs thermal throttle themselves to optimized performance and sustain great power and heat expenditure during continuous AI workloads, thus, restraining the vehicle system’s scalability. Conversely designed, morphic chips process pertinent and appropriate data and hence, parallel event-driven computing with lower power expenditure becomes more appropriate for systems designed to enhance the battery’s operational efficiency of electric vehicles.
   
• Adopting neuromorphic are accelerated due to advances in sensor technologies. Other bio-spired sensors and event cameras produce sparse rich in information data streams which are not suited for standard computing systems. These 'quad' sensors are positioned in a neuromorphic chip which manages asynchronous, spike-based signals. This makes them useful for advanced next generation perception systems. In neuromorphic systems, real-time data from a wide range of inputs is seamlessly integrated and processed. This makes them useful in the automotive industry, which is currently moving towards sensor fusion models that integrate data from a wide range of sources.
   

Neuromorphic Chips for Autonomous Vehicle Market Trends

• The transition of neuromorphic computing from the research phase to practical application in self-driving cars is in the process of being operationalized. Advanced spiking neural networks and mixed-signal chip designs facilitate the easier and quicker processing of complicated sensor information. As a result, neuromorphic chips can perform real-time perception, localization, and decision-making rudimentary for reliable and safe self-driving cars. As the chips progress, they are bound to serve a critical role in the AI systems of the vehicles in the near future, augmenting the conventional processors or taking over from them on some functions.
   
• The adoption of advanced sensors, such as LiDAR, event-based cameras, and radar that produce asynchronous, complex, and rich information streams, boosts the growth of conventional computing systems that neuromorphic chips are built to support. Spiking data stream processors can perform real-time sensor data fusion and interpretation, enhancing situational awareness in dynamic decision-making environments. This sophisticated decision-making is crucial in dynamic driving systems, enhancing the overall driving experience.
   
• Neuromorphic technology is evoking changes in deployment strategies to maximally benefit from it. Edge computing, where chips are physically mounted in the vehicle, is fast becoming commonplace because of the urgent need for ultra-low-latency data processing and responses. Also, multi-modal paradigms, where on-vehicle processing is supplemented with learning and system updates from the cloud, are also on the rise. These paradigms enable vehicles to consistently augment their AI capabilities and operate safely in real time.
   
• The automotive ecosystem is facilitating the swift commercialization of neuromorphic chips. Automakers, Tier-1 suppliers, and tech developers are engaging more in collaborative R&D, pilot projects, and co-development activities. Such cooperation helps to integrate neuromorphic chips into vehicle platforms and provides the requisite knowledge to comply with the stringent safety, performance, and reliability. The resulting ecosystem ensures effective technology scaling across diverse vehicle types and applications.
   
• Adoption remains focused on maintaining energy efficiency. Other leading edge computing devices, neuromorphic chips, perform computations while energy is being used compared to other GPUs and CPUs. This capability is crucial for use in electric and autonomous vehicles. This performance translates to longer battery life as well as lower thermal load. With advanced disproportionate computing deployed onboard, autonomous mobility can now perform intricate sets of advanced AI functionalities actively while still maintaining efficiency. This performance energy savings balance is what is giving neuromorphic chips preference and positioned as a solution for tomorrow's autonomous mobility.
   

Neuromorphic Chips for Autonomous Vehicle Market Analysis

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Based on chip architecture, the market is divided into analog, digital and mixed-signal.
 

• In 2024, digital chips hold the largest share of 43.2% of the global neuromorphic chips for autonomous vehicles market. Digital neuromorphic chips dominate the market as they integrate seamlessly with existing automotive AI architectures and support high computational precision. Their compatibility with current vehicle electronic control units (ECUs) and AI software frameworks allows automakers to adopt them without extensive redesigns, making them a preferred choice for mass production. Additionally, the strong backing from leading chip manufacturers ensures availability, scalability, and ongoing technological improvements.
   
• The mixed-signal chips segment will witness a sharp increase in the CAGR and be estimated at 21.7% from 2025 to 2034. Mixed-signal neuromorphic chips are gaining attention due to their ability to combine the efficiency of analog computation with the precision and flexibility of digital processing. They are particularly suitable for edge processing in autonomous vehicles, enabling low-latency decision-making while reducing power consumption. As the demand for energy-efficient, real-time computing grows, mixed-signal chips are emerging as a critical growth area.

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Based on deployment, the neuromorphic chips for autonomous vehicle market is segmented into on-board (edge) processing, cloud-assisted processing and hybrid processing.
 

• The on-board (edge) processing sector recorded revenues of USD 3.95 billion in 2024. On-board deployment of neuromorphic chips is the dominant model due to the critical need for real-time processing. Edge computing allows vehicles to process sensor data locally, minimizing latency and ensuring rapid reaction to driving conditions. This deployment model is indispensable for safety-critical applications such as collision avoidance and emergency braking.
   
• The hybrid processing sector is expected to witness a CAGR of 21.4% during the period 2025 to 2034. Hybrid processing models, combining on-board edge computation with cloud-assisted learning, are expanding quickly. They allow vehicles to continuously update AI models, optimize performance, and share insights across fleets while maintaining immediate responsiveness on-board. This approach is particularly valuable for connected autonomous mobility solutions and fleet management.
   

Based on vehicle category, the market is segmented into passenger cars, commercial vehicles, autonomous shuttles & robo-taxis, off-road & specialized vehicles and others.
 

• The passenger cars segment dominated the neuromorphic chips for autonomous vehicle market, accounting for USD 2.99 billion in 2024. Passenger cars, including semi-autonomous and fully autonomous vehicles, constitute the largest market for neuromorphic chips. High production volumes, early adoption of ADAS features, and the need for regulatory compliance drive strong demand. Passenger vehicles also offer OEMs a platform to validate and refine AI-driven mobility technologies before expanding into commercial applications.
   
• The autonomous shuttles & robo-taxis segment is projected to grow at a strong CAGR of 22.1% during the forecast period. Autonomous shuttles and robo-taxis are rapidly expanding, especially in urban environments. These applications require continuous, reliable processing of sensor data to navigate crowded streets and respond safely to dynamic traffic conditions. Growth is fueled by urban mobility initiatives, pilot programs, and demand for shared autonomous transportation.

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The North America neuromorphic chips for autonomous vehicle market accounted for USD 3.13 billion in 2024. The North American market is driven by the strong presence of both established automotive manufacturers and cutting-edge technology firms, creating an ecosystem conducive to the rapid adoption of neuromorphic chips. Increasing integration of artificial intelligence in autonomous vehicles, combined with the demand for higher safety standards and improved energy efficiency, is propelling interest in neuromorphic computing.
 

• In 2024, the U.S. neuromorphic chips for autonomous vehicle market reached a valuation of USD 2.5 billion. The U.S. market benefits from strong government and private sector support for AI and autonomous vehicle technologies. A culture of innovation and the presence of leading tech companies accelerate research in neuromorphic computing, particularly for applications requiring real-time data processing and decision-making. The U.S. automotive industry’s shift towards highly automated and autonomous vehicles further fuels the adoption of neuromorphic chips, as these components are essential for safe, energy-efficient, and intelligent vehicle operation.
   
• The U.S. market benefits from strong government and private sector support for AI and autonomous vehicle technologies. A culture of innovation and the presence of leading tech companies accelerate research in neuromorphic computing, particularly for applications requiring real-time data processing and decision-making. The U.S. automotive industry’s shift towards highly automated and autonomous vehicles further fuels the adoption of neuromorphic chips, as these components are essential for safe, energy-efficient, and intelligent vehicle operation.
   
• The Canada neuromorphic chips for autonomous vehicle market are projected to grow at a CAGR of 20.2% during the forecast period. Canada’s growing focus on artificial intelligence, supported by research institutions and government initiatives, is a key driver for neuromorphic chip adoption in autonomous vehicles. There is also increasing interest in sustainable and energy-efficient technologies, which makes neuromorphic computing a favorable option. Canadian companies and tech startups are actively exploring autonomous vehicle applications, creating a receptive environment for these advanced chips.
   

Europe neuromorphic chips for autonomous vehicle market is projected to grow at a CAGR of 20.2% during 2025–2034. Europe is experiencing strong demand for advanced autonomous vehicle solutions, supported by progressive regulations and increasing consumer interest in AI-driven technologies. Environmental considerations, including energy efficiency and reduced carbon footprint, are further driving the adoption of neuromorphic chips. European automotive manufacturers are actively incorporating AI into vehicle systems, creating a growing need for specialized, high-performance computing components.
 

• The UK neuromorphic chips for autonomous vehicle market is projected to reach USD 2.66 billion by 2034. The UK’s strong AI research ecosystem, combined with active collaboration between startups and automotive companies, is driving the adoption of neuromorphic chips. Initiatives focused on autonomous vehicle testing and smart city projects provide a conducive environment for deploying advanced computing systems. There is also growing interest in energy-efficient and low-latency technologies that can enhance vehicle safety and intelligence.
   
• Manufacturers actively collaborate with UK-based research institutions, startups, and automotive companies to co-develop chips tailored for local market needs. Participation in government-led innovation programs can provide access to resources and accelerate market penetration. Offering adaptable, high-efficiency chips that integrate seamlessly with autonomous systems will position manufacturers as trusted partners in the UK market.
   
• The Germany neuromorphic chips for autonomous vehicle market accounted for USD 420.83 million in 2024, Germany’s leadership in automotive manufacturing and technological innovation is a key factor in driving the adoption of neuromorphic chips. There is strong interest in AI-powered autonomous vehicle solutions that improve safety, performance, and energy efficiency. Collaborative innovation between technology firms and automotive OEMs is fostering the development of specialized chips optimized for high-performance applications.
   

Asia Pacific accounted for 28.3% of neuromorphic chips for autonomous vehicle market in 2024, APAC is experiencing rapid technological advancement, with increasing adoption of AI and autonomous driving technologies. Growing urbanization and investments in smart transportation infrastructure are creating a favorable environment for neuromorphic chips. Countries in the region are also focusing on energy-efficient solutions and low-latency computing, which align well with the capabilities of neuromorphic systems.
 

• The China neuromorphic chips for autonomous vehicle market is expected to grow at a CAGR of 23.8% during the forecast period 2025–2034. China is rapidly advancing in autonomous vehicle technologies, with a strong focus on AI, electric vehicles, and digital cockpits. The government and industry initiatives emphasize innovation in semiconductor design and energy-efficient solutions, creating a fertile environment for neuromorphic chip adoption. Increasing urbanization and smart mobility projects further drive demand for advanced computing solutions.
   
• Manufacturers in China aligns their product development strategies with focus on AI and semiconductor innovation. Establishing partnerships with local technology firms and automotive companies will be key for market access. Emphasizing energy efficiency, real-time processing capabilities, and integration with advanced vehicle platforms will increase the competitiveness of neuromorphic chips in China.
   
• Japan neuromorphic chips for autonomous vehicle market is expected to reach USD 1.96 billion by 2034. Key growth drivers include the adoption of advanced driver-assistance systems (ADAS), increasing integration of AI in vehicle platforms, and strong government support for automotive innovation. Manufacturers are aiming to maintain and expand their market share in Japan focuses on developing energy-efficient, low-latency neuromorphic chips tailored to local automotive standards. Strategic partnerships with Japanese OEMs and technology firms will facilitate product integration and adoption
   

The Latin America neuromorphic chips for autonomous vehicle market were valued at USD 631.79 million in 2024. Latin America is gradually adopting autonomous vehicle technologies, creating opportunities for neuromorphic computing. Increasing urbanization, focusing on intelligent mobility solutions, and the rising interest in energy-efficient AI systems are key drivers. Additionally, the region’s emerging tech ecosystem supports innovation and adaptation of advanced computing solutions.
 

The Middle East & Africa (MEA) neuromorphic chips for autonomous vehicle market is anticipated to reach USD 4.73 billion by 2034. The MEA region is witnessing growing interest in smart transportation and autonomous mobility, particularly in urban centers. Initiatives to deploy intelligent infrastructure and AI-driven vehicle systems are creating demand for neuromorphic chips. The focus on low-power, high-performance computing solutions is aligned with regional needs for energy-efficient technology.
 

• The UAE neuromorphic chips for autonomous vehicle market is projected to grow at a CAGR of 18.6% during the forecast period. The UAE commitment to smart city initiatives and autonomous mobility solutions is boosting demand for advanced AI technologies, including neuromorphic chips. Government support for innovation and investment in AI research encourages deployment of cutting-edge vehicle systems that rely on intelligent, energy-efficient computing.
   
• The Saudi Arabia neuromorphic chips for autonomous vehicle market accounted for USD 312.62 million in 2024. Saudi Arabia Vision 2030 plan emphasizes smart transportation and autonomous vehicle deployment, creating a strong market for neuromorphic computing. Investments in AI research and infrastructure development are enabling the adoption of intelligent, energy-efficient vehicle systems across the country.
   

Neuromorphic Chips for Autonomous Vehicle Market Share

• The top five players in the neuromorphic chips market for autonomous vehicles Intel, IBM, NVIDIA, Qualcomm, and Samsung collectively dominate the landscape due to their technological leadership, extensive R&D capabilities, and strategic collaborations with automotive OEMs and tech firms with 79.6% share in 2024. Their growth is driven by increasing demand for energy-efficient, low-latency AI processing in autonomous vehicles, coupled with the need for real-time decision-making and advanced perception systems. Each of these companies leverages its unique strengths ranging from scalable neuromorphic architectures and high-performance computing platforms to memory-based innovations to capture market share and strengthen their foothold in this emerging sector.
   
• Intel leads the neuromorphic chips market with a 25% share in 2024, driven by its Loihi neuromorphic architecture and strong collaborations with automotive manufacturers and research institutions. The company’s emphasis on scalable, low-power, and high-performance neuromorphic solutions has positioned it as the industry benchmark, enabling Intel to provide reliable AI processing for a wide range of autonomous vehicle applications.
   
• IBM holds a 18% share in 2024, leveraging its TrueNorth architecture to deliver energy-efficient, brain-inspired computing systems. The company’s focus on research and enterprise-scale applications supports its strong presence in autonomous vehicle AI, allowing IBM to provide sophisticated neuromorphic solutions capable of handling complex decision-making tasks and real-time data processing.
   
• NVIDIA commands an 15% share in 2024, largely due to its integration of GPU and neuromorphic computing within the DRIVE platform for autonomous vehicles. The company’s strength lies in high-performance AI processing, enabling real-time perception, prediction, and planning. NVIDIA’s leadership is reinforced by strategic partnerships with automotive OEMs and software developers to deploy efficient, scalable neuromorphic solutions.
   
• Qualcomm has a 12.3% share in 2024, driven by its focus on low-power, edge-optimized neuromorphic processors. The company’s ability to provide energy-efficient AI computation for autonomous vehicles positions it as a key player in edge computing applications, particularly for real-time decision-making and sensor fusion in compact, performance-constrained environments.
   
• Samsung Electronics holds a 9.3% share in 2024, capitalizing on its expertise in memory-driven neuromorphic computing and semiconductor manufacturing. The company focuses on integrating memory-based neuromorphic chips into AI-driven automotive systems, enabling energy-efficient and high-throughput processing that supports autonomous vehicle perception and control applications.
   

Neuromorphic Chips for Autonomous Vehicle Market Companies

The major companies operating in the neuromorphic chips for autonomous vehicle industry are:
 

• Accenture
• Applied Brain Research Inc.
• Aspinity Inc.
• BorgWarner Inc. (USA)
• BrainChip Holdings Ltd.
• Cadence Design Systems, Inc.
• Figaro Engineering Inc. (Japan)
• General Vision Inc.
• Grayscale AI
• Gyrfalcon Technology Inc.
• Hewlett Packard Enterprise Development LP
• IBM Corporation
• Intel Corporation
• MemryX Inc.
• Micron Technology, Inc.
• Mythic Inc.
• NVIDIA Corporation
• Polyn Technology
• Prophesee SA
• Qualcomm Technologies, Inc.
• Samsung Electronics Co., Ltd.
• Sony Corporation
   

• The leaders of the market in neuromorphic chips are Intel, IBM, NVIDIA, Qualcomm, and Samsung. Their ability to neuromorphic the chips for self-driving cars come from heavy investments in R&D, global reach, and strong financial backing. It comes from years of research and development at the firm. It undergoes rigorous tests to be able to qualify for reliability, being scalable, and to make sure it is able to be incorporated AI and automotive platforms. The joint efforts from multiple automotive OEMs, automotive technology firms, and various research institutes enables them to gain market-leader status by being proficient at chip scaling. It is rather normal for the market leaders to be the ones creating a market's norms, creating the blueprints for competitor’s neuromorphic chips, and prolonging market shifts.
   
• Some of the companies that fall under “Challengers” in this example are Sony, Micron, Hewlett Packard Enterprise, Cadence, and BrainChip. The companies are known for their advanced innovative products and powerful technology, even if they lack reach or market availability set by the market leaders. Companies known for their advanced neuromorphic chips are touted for their technological breakthroughs. In the case of challengers, they tend to stick towards specific silos in the neuromorphic chip market, such as memory-centric computing or event-based vision systems. With enough partnerships and strides in production, these companies are capable of advancing towards the market leaders.
   
• The companies SynSense, Prophesee, Innatera, MemryX, Mythic, and Syntiant are classified under followers. Much like the rest of the competition, these companies are either start-ups or highly specialized autonomous vehicle tech companies. Their innovative technology and products, however, are overshadowed by the competition’s massive market scale and recognition. Followers are passive and reactive to the market trends the leaders and challengers create. The loose ends and gaps of the market are the products they focus on and sell. Followers focus on edge computing and more specialized products they smoother market demand for. Their systematic and niche strategy helps them grow gradually.
   
• Gyrfalcon, Applied Brain Research, General Vision, Vicarious, Aspinity, Polyn Technology, Grayscale AI, and Vivum Computing, on the other hand, belong in the niche or potential pitfall category. These companies focus in depth on specialized technologies, or in small scales of deployment, which cannot easily be adopted for use in autonomous vehicles. Their innovations, such as analog computing or brain-inspired AI, are remarkable, however, they ache in funding, and are torn between small players or highly established competition. Strong IP protection, market validation, and strategic partnerships are key to avoid losing the niche position and progression stagnation.
   

Neuromorphic Chips for Autonomous Vehicle Industry News

• In June 2023, Honeywell announced the DG Neuromorphic Chips for Autonomous Vehicle as a solution designed to enhance the efficiency and reliability of monitoring and controlling low-pressure combustion air and fuel gases. The product provided precise monitoring capabilities and aligned with digitalization trends under Industry 4.0, offering opportunities to improve combustion system performance and transform operational dynamics for OEMs, end users, and system integrators.
   
• In January 2025, At CES in Las Vegas, Bosch Sensortec showcased its AI-enabled sensors that combine MEMS, embedded microcontrollers, and AI to deliver smarter functionality. CEO Stefan Finkbeiner noted that these solutions supported applications in consumer health, smart homes, and smart cities, with AI and intelligent software as the core enablers.
   
• In October 2021, ABB launched its FusionAir Neuromorphic Chips for Autonomous Vehicle, a touch-free room sensor equipped with optional controls to monitor temperature, humidity, CO2, and VOCs, aimed at enhancing indoor air quality and reducing viral exposure risks.
   

This Neuromorphic Chips for Autonomous Vehicle market research report includes in-depth coverage of the industry with estimates & forecasts in terms of revenue (USD Billion) from 2021 to 2034, for the following segments:

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Market, By Chip Architecture

• Analog
• Digital
• Mixed-Signal

Market, By Deployment

• On-Board (Edge) Processing
• Cloud-Assisted Processing
• Hybrid Processing

Market, By Vehicle Category

• Passenger Cars
• Commercial Vehicles
  • Trucks
  • Buses 
• Autonomous Shuttles & Robo-Taxis
• Off-Road & Specialized Vehicles
  • Agriculture
  • Mining
  • Construction
• Others

Market, By End Use

• Automotive OEMs
• Tier-1 Suppliers
• Aftermarket Solution Providers
• Research & Development Entities
• Others

The above information is provided for the following regions and countries:

• North America
  • U.S.
  • Canada
• Europe
  • UK
  • Germany
  • France
  • Italy
  • Spain
  • Netherlands
• Asia Pacific
  • China
  • India
  • Japan
  • South Korea
  • ANZ 
• Latin America
  • Brazil
  • Mexico
  • Argentina 
• MEA
  • UAE
  • Saudi Arabia
  • South Africa