Automotive Artificial Intelligence (AI) Market Size, Share & Trends Analysis Report By Component, By Level Of Autonomy, By Technology (Machine Learning, Natural Language Processing), By Vehicle Type, By Region, And Segment Forecasts, 2023 - 2030

Automotive AI Market Size & Trends

The global automotive AI market size was valued at USD 2.99 billion in 2022 and is expected to grow at a compound annual growth rate (CAGR) of 22.7% from 2023 to 2030. Introducing artificial intelligence (AI) in the automotive industry ushers in a new era, allowing businesses to track operations, improve business plans, develop autonomous and semi-autonomous vehicles, and enhance digital outcomes. The global automotive AI market is driven by rising demand for autonomous vehicles, adoption of artificial intelligence for traffic management, advanced automotive solutions, and government initiatives.

Nevertheless, absence of infrastructure and expensive procurement and operational expenses are obstacles to market growth. For instance, in November 2022, Stellantis NV, a multinational automotive manufacturing corporation, announced the acquisition of aiMotive Ltd., an autonomous vehicle technology company. The acquisition intends to expand Stellantis’ global talent pool, enhance AI and autonomous driving core technology, and boost development of STLA AutoDrive platform. Automotive AI is rapidly replacing human drivers by enabling self-driving cars that utilize sensors to collect data about their surroundings.

Artificial intelligence (AI) is projected to disrupt automobile sector by streamlining production capacities and increasing corporate growth. Developing and deploying novel technologies such as autonomous mobility, rapid prototyping, vehicle simulations, and AI-enabled automotive factories are boosting market for autonomous technology. Automakers are rapidly modernizing their existing production systems by incorporating AI platforms. Companies are also increasingly focusing on developing self-driving vehicles to increase passenger mobility. For instance, in January 2022, Baidu, Inc., a Chinese multinational technology company, announced the launch of a car model with Level-2 self-driving technology in near future. By introducing car models with Level-2 self-driving technology, the company aims to offer consumers an advanced and convenient driving experience.

AI in automotive has been gaining traction in recent years. AI improves customer experience through conversational interfaces and personalized recommendations based on preferences. Additionally, it is used to expand capabilities of existing technologies, such as voice assistants, by allowing them to understand what you need and provide you with relevant information. For instance, in June 2022, Hailo, an AI chipmaker, partnered with Renesas to seamlessly enable automotive customers to transition from ADAS to automated driving. With collaboration between Hailo and Renesas, sophisticated ADAS technology will be more accessible to vehicles of all types.

COVID-19 has accelerated implementation of artificial intelligence in critical industries, particularly automotive industry. AI is applied efficiently throughout automotive value chain, including post-production, manufacturing, supply chain, design, production, driver assistance, and risk assessment systems. Although market players have witnessed less sales volume during first year of pandemic, the market is gradually gaining traction. The COVID-19 pandemic has compelled automakers to reconsider their short-term strategy for redefining automation.

Market Dynamics

Increasing government regulations plays a crucial role in driving growth of automotive AI market. Governments worldwide are becoming increasingly concerned about road safety and enacting strict safety measures. Automotive AI technology, such as Advanced Driver Assistance Systems (ADAS) and self-driving systems, is viewed as a viable solution to minimize fatalities and accidents. Governments frequently compel automakers to include AI-powered safety systems, such as pedestrian identification, collision avoidance, and lane-keeping assist.

Governments are also focusing on reducing car emissions to battle climate change and pollution. Electric vehicles (EVs) are becoming more popular, and AI technologies are being used to optimize battery utilization, range prediction, and charging infrastructure management. Governments frequently subsidize EV adoption while imposing higher emission limits for conventional vehicles, creating a need for automotive AI solutions. Before deploying AI-powered systems on public roadways, governments frequently require technology providers and vehicle manufacturers to undergo rigorous testing and certification processes to ensure that AI systems are reliable and safe in real-world circumstances, thereby driving market growth.

AI algorithms enable vehicles to acquire and interpret massive volumes of data from cameras and sensors in real time, assisting drivers in identifying possible hazards and preventing accidents. Governments drive use of AI in automotive systems by legislating specific safety measures, resulting in safer automobiles on road. Businesses operating in this industry must adapt to and comply with these regulations to capitalize on growth prospects and secure market position. Overall, government regulations influence safety standards, data protection, emission restrictions, international collaboration, and testing methods, pushing market forward.

Component Insights

Hardware segment dominated the market in 2022 and accounted for a revenue share of over 75%. Automotive AI hardware is considered a crucial component of modern vehicles as it enables advanced features and capabilities. Hardware in automotive AI includes sensors such as cameras, radar, ultrasonic sensors, and Inertial Measurement Units (IMUs), which are employed to collect data related to vehicles’ surroundings and internal state. These sensors provide crucial inputs for AI algorithms to make informed decisions. In addition, it includes processing units such as CPUs (Central Processing Units), GPUs (Graphics Processing Units), and specialized AI chips that perform complex computations required for AI algorithms and actuators that convert electrical signals into physical actions, enabling AI-controlled functions. For instance, in March 2023, RoboSense announced the launch of RS-Fusion-P6 (P6) automotive-grade solid-state LiDAR perception solution. The P6 LiDAR system is designed explicitly for level 4 autonomous driving and integrates cutting-edge software and hardware support, ensuring efficient and reliable perception capabilities for autonomous vehicles.

Software segment is anticipated to grow significantly in the coming years. Automotive AI software plays a significant role in improving vehicle performance, safety, and user experience. AI and machine learning work together in automotive sector to develop algorithms that analyze traffic situations, make quick decisions, and learn from other participants. Adapting technology to quickly changing conditions and reducing human factors in auto accidents are challenging for automotive software developers. Top car firms compete based on ML and AI software for autonomous vehicles. For instance, in April 2023, SoundHound AI Inc. launched SoundHound Chat AI for automotive industry. It represents a significant development in integrating voice AI technology into vehicles. Availability of powerful voice assistants can significantly enhance the in-vehicle experience for both automakers and customers. With SoundHound Chat AI, drivers and passengers can access various voice-controlled features and functionalities, such as controlling various vehicle settings, accessing navigation systems, making hands-free calls, and managing entertainment options.

Level of Autonomy Insights

Level 2 segment led market in 2022, accounting for over 62% share of global revenue. Advanced driving assistance systems (ADAS) in level 2 vehicles can take over acceleration, steering, and braking under specific circumstances. Several automated systems cooperate during more complex driving tasks, but human drivers must always intervene if a car encounters a problem it cannot resolve. Semi-autonomous vehicles provide pragmatic, rapid solutions to requirements for on-demand mobility. In addition to being sustainable, autonomous, and convenient, semi-autonomous cars are safer and easier to manage than completely automated vehicles. Therefore, safety concerns are driving market growth of this segment.

Level 3 segment is predicted to foresee significant growth in forecast years. Level 3 autonomous driving systems are predicted to become more sophisticated and capable as technology advances. This provides increased autonomy under specific scenarios while assuring driver safety and readiness. Level 3 autonomous automobiles perceive and analyze their surroundings using AI systems. AI systems can recognize and comprehend road signs, traffic lights, lane markings, and other pertinent information to make informed vehicle control and navigation decisions.

Vehicle Type Insights

Passenger vehicles led the market in 2022, accounting for over 85% share of global revenue. Passenger vehicles such as cars as well as motorcycles have implemented AI integration. AI can play a decisive role in improving convenience and safety of passengers traveling in any particular vehicle. AI is widely used in ADAS to analyze data from various sensors, including cameras, radars, and LiDARs. For instance, in December 2020, Kawasaki began developing motorcycles with hybrid and AI assistant technology. Such significant developments are likely to fuel market growth.

Commercial vehicles segment is predicted to foresee significant growth in forecast years. AI is increasingly being integrated into commercial vehicles to facilitate intelligent routing and logistics, predictive maintenance, fleet management, and autonomous capabilities. These applications have made development of self-driving commercial vehicles more feasible by augmenting safety, enhancing vehicle efficiency and performance, and improving logistics. As such, AI is poised to make significant strides in commercial vehicles as it develops and advances further, thereby boosting overall productivity.

Technology Insights

Machine learning segment led market in 2022, accounting for over 36% share of global revenue. Machine learning has played a potent role in latest advances, such as self-driving cars, lane-change assistance, park assist, and intelligent energy systems associated with automotive industry. Machine learning algorithms can deliver vehicle maintenance recommendations to drivers. Taking references from previous occurrences, they can forecast when an event or issue will occur again, thereby enhancing vehicle safety, effectiveness, and performance. As such, machine learning algorithms are often integrated into advanced driving assistance systems (ADAS) to alert drivers about potential road hazards and into scheduling and routing systems to reduce fuel consumption. Machine learning can also help in identifying car issues before they become serious, thereby reducing maintenance costs and averting any major downtime. By adjusting vehicular settings to preferences of drivers, machine learning can also enhance driving experience.

Computer vision segment is anticipated to grow significantly in coming years. Computer vision, often known as machine vision, is AI-based technology. This technique collects valuable data from photos using machine learning algorithms and acts as a vehicle's eye. Vision systems were initially introduced in automotive industry to automate assembling vehicles. However, advent of automotive driver assistance and traffic management systems has widened the scope of computer vision systems in industry. For instance, in July 2022, Michelin, a tire manufacturing company, acquired RoadBotics, Inc., a startup based in the U.S. known for transforming virtual infrastructure data with help of computer vision technology. Acquisition allowed Michelin DDI, a Michelin company, to gain access to RoadBotics, Inc.'s computer vision expertise. Acquisition was aimed at gaining unique insights into factors contributing to driving behavior to facilitate simpler, quicker, and more relevant decisions and more effective road safety management.

Regional Insights

North America dominated the market in 2022, accounting for over 38% share of global revenue. Growth is attributed to early adoption of technology such as artificial intelligence and analytics. The region will continue to witness growth owing to increased hiring in AI roles in automotive industry. Furthermore, North America has long been a leader in automated vehicle sector, and West Coast U.S tech centers have been a significant source of its contributions to self-driving technology. The U.S. is leading race to make autonomous vehicles safe, with companies such as Uber and Tesla generating news about their successes and failures. 2020 American Automotive Policy Council (AAPC) Economic Contribution report states that leading automakers such as Ford, FCA US, and General Motors are driving rapid change in the North American automotive industry by investing in future technologies such as artificial intelligence and cloud computing.

Asia Pacific is likely to possess lucrative market opportunities in the coming years. Region's rapid rise can be attributed to growing sales of premium passenger automobiles, increasing disposable income, and positive consumer opinion of AI. Region's increasing sales of premium passenger automobiles equipped with advanced AI features have attracted consumers seeking enhanced driving experiences. Consumers' rise in disposable incomes to purchase technologically advanced vehicles is fueling demand for AI-driven automotive solutions. Additionally, favorable customer perceptions of AI in automotive sector, which provides convenience, safety, and customized experiences, have further spurred market expansion. Moreover, government assistance, technology developments, and business partnerships have also contributed to the Asia Pacific region's rapidly expanding automotive AI sector.

Key Companies & Market Share Insights

Automotive AI competitors focus on innovation and product portfolio upgrades to achieve competitive advantage. Acquiring new companies and integrating them backward is a strategy companies use to cut costs and increase performance. For instance, in May 2023, Qualcomm Inc. acquired Autotalks, Ltd., a semiconductor company. Acquisition was aimed at expanding Qualcomm Inc.’s snapdragon digital chassis product portfolio, company’s portfolio of cloud-connected automotive platforms. Besides, in April 2023, SoundHound AI Inc. launched SoundHound Chat AI for automotive industry. It represents a significant development in integrating voice AI technology into vehicles. Availability of powerful voice assistants can significantly enhance the in-vehicle experience for both automakers and customers. With SoundHound Chat AI, drivers and passengers can access various voice-controlled features and functionalities, such as controlling various vehicle settings, accessing navigation systems, making hands-free calls, and managing entertainment options. Some of the prominent players in the global automotive artificial intelligence market include:

• Alphabet Inc.

• Intel Corporation

• Microsoft

• NVIDIA Corporation

• IBM Corporation

• Qualcomm Technologies, Inc.

• Tesla

• AB Volvo

• BMW AG

• AUDI AG.

Automotive Artificial Intelligence Market Report Scope

Global Automotive Artificial Intelligence Market Report Segmentation

This report forecasts revenue growth at global, regional, and country levels and provides an analysis of the latest industry trends in each of the sub-segments from 2017 - 2030. For the purpose of this study, Grand View Research has segmented the global automotive artificial intelligence market report based on component, level of autonomy, technology, vehicle type, and region.

• Component Outlook (Revenue, USD Million, 2017 - 2030)

  • Hardware

  • Software

• Level of Autonomy Outlook (Revenue, USD Million, 2017 - 2030)

  • Level 1

  • Level 2

  • Level 3

  • Level 4

• Technology Outlook (Revenue, USD Million, 2017 - 2030)

  • Machine Learning

  • Natural Language Processing

  • Computer Vision

  • Context-aware Computing

  • Others

• Vehicle Type Outlook (Revenue, USD Million, 2017 - 2030)

  • Passenger Vehicles

  • Commercial Vehicles.

• Regional Outlook (Revenue, USD Million, 2017 - 2030)

  • North America

    • U.S.

    • Canada

    • Mexico

  • Europe

    • Germany

    • UK

    • France

  • Asia Pacific

    • China

    • Japan

    • India

  • Central & South America

    • Brazil

  • Middle East and Africa (MEA)