Global AI in Automotive Market by Component (Hardware, Software) by Autonomy (Semi-Autonomous Vehicles, Fully-Autonomous Vehicles) by Technology (Machine Learning & Deep Learning, Natural Language Processing, Computer Vision, Context-aware Computing, Others) Region and Companies – Industry Segment Outlook, Market Assessment, Competition Scenario, Trends and Forecast 2024-2033

Report Overview

The global AI in automotive market size is estimated to reach USD 134.5 billion in the year 2033 with a CAGR of 37.4% during the forecast period and was valued at USD 5.6 billion in the year 2023.

Artificial Intelligence (AI) is efficiently used throughout the automotive value chain, including manufacturing, design, supply chain, manufacturing, post-production, driving assistance, and driving risk assessment systems. Auto manufacturing services include designing, producing parts, and collaborating with teams to create vehicles. AI mimics human decision-making by using human-generated data and algorithms.

Automakers can ensure a superior customer experience by streamlining their decision-making process with the use of AI. Modern cars have distinct AI-enabled features like adaptive cruise control and anti-lock braking systems (ABS). The upcoming development in the auto industry is automated driving technology, which heavily relies on AI.

A significant transformation can be achieved with the introduction of AI in the automotive industry, which enables businesses to track operations, enhance business planning, create autonomous vehicles, and improve outcomes. The increasing demand for self-driving cars, the use of AI in traffic management, cutting-edge automotive technologies, and government initiatives are propelling global AI in the automotive market.

The integration of artificial intelligence (AI) in the automotive industry is rapidly accelerating, reshaping how vehicles are designed, manufactured, and operated. This growth is driven by increasing demand for autonomous vehicles, advanced driver-assistance systems (ADAS), and predictive maintenance technologies, all of which rely heavily on AI capabilities.

Autonomous vehicles represent one of the largest areas of AI adoption in the automotive sector. By 2025, nearly 15% of all new vehicles are expected to incorporate some form of AI-based autonomous driving features, enabling functions like lane-keeping, automatic parking, and traffic navigation. This growing trend is largely due to advancements in machine learning, computer vision, and sensor fusion, which are essential for real-time decision-making in self-driving cars.

AI is also making a significant impact on manufacturing and vehicle maintenance. Automakers using AI for predictive maintenance and quality control are reducing downtime by up to 30%, resulting in cost savings and improved vehicle reliability. AI-driven robots and automated systems are being used in assembly lines, enabling faster production and better quality control, particularly in electric vehicle (EV) manufacturing.

In the customer experience segment, AI-powered virtual assistants and in-car infotainment systems are now present in more than 40% of new vehicles, offering features like voice recognition, navigation assistance, and personalized recommendations. This level of connectivity enhances user interaction and engagement, providing a seamless, intuitive driving experience.

Despite its rapid growth, the AI in automotive market faces challenges, including high development costs and concerns over data privacy and security. However, the expanding use of AI in EVs, combined with advancements in autonomous driving and connected car technologies, presents significant opportunities for growth. As the automotive industry continues to embrace AI, the market is expected to reach $15.9 billion by 2028, revolutionizing transportation and redefining the future of mobility.

Key Takeaways:

• The global AI in automotive market size was valued at USD 5.6 billion in the year 2023 and is estimated to reach USD 134.5 billion in the year 2033 with a CAGR of 37.4% during the forecast period.
• Based on the components, the hardware segment has dominated the market with a share of 47% in the year 2023.
• Based on autonomy, the fully autonomous vehicle is leading the market with a share of 59% in the year 2023.
• Based on the technology, the machine learning and deep learning segment has dominated the market with a share of 24% in the year 2023.

Component Analysis

Based on the component, the market is segmented into hardware and software segments. Among these, the hardware segment has dominated the market with a share of 47% in the year 2023.

To handle massive amounts of data from sensors, cameras, and other sources in real-time, automotive AI systems need a lot of processing power. This requires high-performance hardware pieces like GPUs, TPUs, and specialized processors intended for AI tasks. Automotive AI ensures high priority to safety and dependability, necessitating the need for specific hardware that can satisfy the car’s quality requirements. This specific hardware guarantees that AI systems perform consistently in a range of harsh environments and urgent circumstances.

Additionally, specialized hardware accelerators are needed for the efficient execution of the complicated AI algorithms employed in advanced driver assistance systems (ADAS) and automated driving. These accelerators maximize performance and power usage, enabling quicker reaction and decision times.

Additionally, due to increasing issues about data security, privacy, and liability, the regulatory framework promotes the adoption of hardware solutions for AI in automotive market applications. Regulatory compliance requires more visible and auditable processes; which are offered by hardware solutions.

Autonomy Analysis

Based on autonomy, the market is segmented into fully autonomous vehicles and semi-autonomous vehicles, where the fully autonomous vehicle is leading the market with a share of 59% in the year 2023. The potential of fully autonomous vehicles to transform transportation is a major factor propelling the dominance of AI in the automotive business.

These cars offer higher safety, efficiency, and convenience. Fully autonomous cars could drastically lower the number of accidents brought on by human mistakes, which is a big risk while driving a standard car. These vehicles can navigate difficult areas with increased awareness and precision as they utilize AI algorithms for real-time decision-making and sensor fusion. The development and use of autonomous vehicles have accelerated due to the growing demand for efficient and sustainable mobility solutions.

Concerning the international initiatives to solve environmental concerns, these vehicles present a huge opportunity for better energy efficiency, less traffic congestion, and enhanced route planning. Furthermore, the auto industry’s strategic response to shifting consumer preferences and competitive challenges is leading to the encouragement of AI for autonomous vehicles. By investing in self-driving technology, businesses aim to bring innovations and satisfy the increasing consumer demand for autonomous features in automobiles.

Technology Analysis

Based on the technology used AI in Automotive Market is segmented into Machine Learning & Deep Learning, Natural Language Processing, Computer Vision, Context-aware Computing, and Other segments. Among these, the machine learning and deep learning segment has dominated the market with a share of 24% in the year 2023. The capacity of machine learning (ML) and deep learning technology to manage intricate data processing tasks essential to advanced driver assistance systems (ADAS) is a major factor contributing to this dominance.

Machine learning and deep learning are highly effective in deriving significant insights from vast datasets produced by sensors, cameras, and other automotive systems. These algorithms’ ability to identify patterns, and objects, and decode environmental information is crucial for real-time decision-making, obstacle identification, and navigation. The performance and safety of autonomous vehicles are enhanced by the iterative nature of machine learning (ML) and deep learning, which allows for constant improvement and adaptation to various driving situations.

By employing methods like reinforcement learning, algorithms vehicles can adjust their behavior in response to feedback from the driving experience, resulting in the development of more durable and dependable self-driving systems. Additionally, the adoption of deep learning and machine learning in automotive applications has accelerated due to the availability of powerful computing resources like GPUs and TPUs. These advancements in hardware make it possible to train and deploy sophisticated neural networks efficiently, which facilitates the creation of complicated AI models that are appropriate for automotive applications.

Key Market Segments

By Component

• Hardware
• Software

By Autonomy

• Semi-autonomous Vehicles
• Fully-autonomous Vehicles

By Technology

• Machine Learning & Deep Learning
• Natural Language Processing
• Computer Vision
• Context-aware Computing
• Others

Driving Factors

Rising investment in R&D development

The growing R&D development in the automotive industry throughout the forecast period is one of the major factors propelling the growth of global AI in the automotive market. Streamlining all the aspects of an automobile organization’s operations, from design and research to manufacturing and marketing, data science and machine learning helps the firm remain competitive.

In addition to this, the primary objective of investing in fuel research and development is to lessen reliance on fossil fuels by converting to ecologically beneficial, abundant, safe, and renewable energy sources. Moreover, the market is being driven by the increasing awareness of the self-driving business. There has been a major spike in customer demand for autonomous vehicles and self-driving features.

For instance, according to Cox Automotive Mobility Solutions Group, 54% of consumers desire semi-autonomous capabilities for safer and better driving. Road accidents can be decreased and safety can be increased with the support of expanding government initiatives in the areas of automotive technology, telematics, artificial intelligence, and road safety.

Restraining Factors

Higher cost of the vehicle

One of the biggest barriers to AI adoption in the automotive sector is the growing cost of advanced vehicles. Advanced driver assistance features and automated driving systems are two examples of AI technologies that raise the cost of a car since they have a lot of processing power and complex sensors. The rate at which these cutting-edge technologies are adopted may be slowed down if automobile prices increase and people are less inclined toward purchasing AI-equipped vehicles. Furthermore, increased car prices might compel automakers to put cost-cutting measures ahead of incorporating AI technologies.

This may result in delays in the creation and application of AI solutions in the automobile industry. Rising auto expenses may also affect the aftermarket for AI solutions and services, which would make it more expensive for customers to upgrade and maintain AI systems.

Moreover, growing car expenses can affect the competitiveness of AI-based cars in the market, particularly in price-sensitive markets. This might prevent AI technologies from being widely adopted and incorporated into the automotive sector, restricting their ability to fully enhance driving safety, efficiency, and satisfaction. Thus, resolving the issue of growing car expenses is essential to ensure AI’s effective integration and uptake in the automotive industry.

Growth Opportunities

Government support

The integration of artificial intelligence (AI) in the Automotive sector has significant opportunities due to the support of the government. The application of AI technology in the automotive industry adheres to the regulations that prioritize efficiency, safety, and sustainability. For instance, AI-powered autonomous cars have lower carbon emissions, optimized driving, and enhanced safety through advanced driver assistance systems (ADAS).

Furthermore, AI’s capacity to increase battery efficiency and forecast range contributes to the government’s practices to promote electric and hybrid vehicles. Furthermore, fleet management, a crucial component in in carriage sector, can be optimized, minimizing downtime, and increasing vehicle reliability using AI-based predictive maintenance.

Additionally, AI skills to create intelligent traffic management systems, lessen traffic congestion and enhance mobility catalyze the government’s desire for connectivity and smart infrastructure. Furthermore, attempts to finance the research and development of cutting-edge technology frequently accompany concerned legislation, encouraging innovation in AI applications for the automobile industry. Government laws and AI innovation are thus coming together to create opportunities for the automobile sector to innovate, advance sustainability, and raise social welfare standards.

Challenging Factors

Lack of skilled and expert workforce

A lack of professional and qualified experts hampers the integration of AI in the automotive sector. A thorough understanding of both AI and automotive engineering is necessary to develop AI-based vehicles. However, there is a shortage of individuals with the deep experience needed for these professions.

An in-depth knowledge of complex systems, such as vehicle dynamics, safety procedures, and regulations is required to build AI-based automotive solutions. Software engineering, data science, and machine learning abilities are needed to construct AI algorithms. This market is also hampered by the need for ongoing learning and development to stay up to date with the latest advancements.

The industry’s capacity to innovate and successfully implement AI solutions is being hampered by a lack of experience and competent workers, which is delaying advancements in fields like autonomous driving, maintenance prediction, and personalized driving experiences. To overcome this problem, a focused effort must be made to fund educational initiatives, training courses, and cross-industry cooperation to develop more AI specialists in the automotive industry.

Latest Trends

Increasing demand for autonomous vehicles

One significant trend in the AI automotive sector is the rising demand for autonomous cars. Numerous factors, including improvements in AI technology, shifting customer preferences, and the need for increased efficiency and safety, are contributing to this rising demand. Automated driving systems have numerous capabilities due to advances in artificial intelligence, particularly in machine learning and computer vision. These developments provide cars the ability to check the environment, reason complex situations, and move with higher accuracy.

Furthermore, as convenience, safety, and sustainability become more important to consumers, the market for self-driving cars is growing. Self-driving cars have the potential to completely transform transportation by offering comfortable transportation, reducing accidents with the use of cutting-edge safety technologies, and optimizing traffic flow to cut down on emissions and jamming.

Companies are also recognizing the potential of autonomous cars to completely transform delivery, logistics, and ridesharing. Fleets of autonomous vehicles are being adopted by several industries due to their potential for cost savings, increased productivity, and instant operations. The automotive industry is changing as a result of the growing desire for autonomous vehicles, which is drawing large investments from established automakers, tech giants, and start-ups.

Regional Analysis

North America region is leading the market

The North American region has dominated the market with a share of 39.5% in the year 2023 with a growth by USD 2.2 Billion. The early use of technology like analytics and artificial intelligence is the main factor contributing to the dominance of this region. As the automotive industry is hiring more people for AI positions, this sector will continue to grow. Furthermore, US West Coast technological hubs constitute a significant source of North America’s contributions to automated driving technology.

With businesses like Uber and Tesla disclosing details about their accomplishments and setbacks, the US is leading the global effort to make autonomous cars safer. According to the American Automotive Policy Council’s (AAPC) 2020 Economic Contribution Report, major automakers like Ford, FCA US, and General Motors are investing in cutting-edge technologies like cloud computing and artificial intelligence, which are changing the market scenario in the region.

Key Regions and Countries

North America

• US
• Canada

Europe

• Germany
• France
• The UK
• Spain
• Italy
• Rest of Europe

Asia Pacific

• China
• Japan
• South Korea
• India
• Australia
• Singapore
• Rest of APAC

Latin America

• Brazil
• Mexico
• Rest of Latin America

Middle East & Africa

• South Africa
• Saudi Arabia
• UAE
• Rest of MEA

Market Share and Key Players Analysis

To obtain a competitive advantage, key players in the automotive AI space are concentrating on innovation and expanding their product lines. Companies employ early integration and acquisition of new enterprises as a cost-cutting and performance-boosting tactic. This may include significant advancement in the integration of voice AI technologies into automobiles. Key players in the AI automotive market include Tesla, which leads in autonomous driving technology with its advanced AI-based Autopilot system, and Waymo, a subsidiary of Alphabet, known for its cutting-edge self-driving car technology.

NVIDIA plays a crucial role by providing AI-powered hardware and software platforms for autonomous vehicles, while Intel’s Mobileye is a major player in ADAS and autonomous vehicle technologies. Additionally, BMW and Mercedes-Benz are integrating AI into their production processes and in-car systems, focusing on enhancing the driving experience through AI-powered infotainment, navigation, and safety features. These companies are driving AI innovation and adoption in the automotive sector.

Top Key Players in the Market

• BMW AG
• AUDI AG
• Intel Corporation
• Tesla Inc
• Uber Technologies
• Volvo Car Corporation
• Honda Motors
• Ford Motor Company
• NVIDIA Corporation
• Tencent
• Microsoft
• Other Key Players

Recent Developments

• In March 2024, MediaTek announced the launch of four new SoCs (Systems on chip) within its Dimensity Auto Cockpit portfolio, which offers AI in-cabin experiences for AI-based vehicles.
• In Jan 2024, Intel acquired Silicon Mobility SAS for advanced EV energy management and the new AI-enhanced software-defined vehicle SoCs.
• In December 2023, Renesas launched a Cloud-based environment to accelerate automotive AI software development and evaluation.

Report Scope