The global automotive artificial intelligence market size reached US$ 3.9 Billion in 2023. Looking forward, the publisher expects the market to reach US$ 33.9 Billion by 2032, exhibiting a growth rate (CAGR) of 27.2% during 2023-2032. The escalating consumer demand for advanced features, imposition of various government regulations, significant technological advancements, rapid cost reduction in sensor technology, growing demand for artificial intelligence (AI) in traffic management, and increasing emphasis on sustainability are some of the major factors propelling the market.
Automotive artificial intelligence (AI) refers to the integration of technology within vehicles to enhance their functionalities, safety, and user experience. It comprises various systems, such as driver assistance, in-car virtual assistants, predictive maintenance, and fully autonomous systems. Automotive AI is widely used in adaptive cruise control, collision avoidance, driver monitoring, voice-activated controls, traffic sign recognition, automated parking, and real-time traffic monitoring. It aids in enhancing safety, increasing efficiency, reducing emission levels, saving time, augmenting traffic flow, improving user experience, and promoting sustainability.
The rapid cost reduction in sensor technology and computing power, which is making AI implementation more financially viable for automotive manufacturers, is positively influencing the market growth. Besides this, the growing demand for AI in traffic management and route optimization owing to the increasing urbanization and subsequent traffic congestion are contributing to the market growth. Furthermore, the rising utilization of AI by automotive manufacturers to enable superior predictive maintenance, real-time decision-making, and personalized user experiences is supporting the market growth. In addition, the recent advancements in the Internet of Things (IoT) and vehicle-to-everything (V2X) communication that are offering new avenues for AI integration, such as advanced telematics and remote vehicle control, are fueling the market growth. Moreover, the increasing emphasis on sustainability is facilitating the demand for AI to optimize fuel efficiency and manage alternative fuel systems.
The increasing consumer demand for advanced features is a prominent factor propelling the growth of the automotive artificial intelligence (AI) market. Users are becoming increasingly tech-savvy, leading to higher expectations for advanced features in vehicles, such as adaptive cruise control, automated parking, and advanced navigation systems. Furthermore, the push for convenience, especially among younger demographics who are deeply engaged with technology in their daily lives, is fueling the market growth. Apart from this, the growing congestion in urban centers is facilitating the demand for vehicles that offer intelligent features to manage the complexities of city driving. This shift in consumer expectations puts considerable pressure on manufacturers to adopt AI technologies in automotive design, not merely as a value-add but as a core component that directly influences purchasing decisions.
The imposition of various government regulations
Government regulations are playing an increasingly critical role in driving the incorporation of AI in the automotive sector. Road safety is becoming a paramount concern across the globe, prompting authorities to impose stricter safety guidelines and requirements for vehicles. These guidelines often mandate the incorporation of advanced safety features, such as collision avoidance systems, lane-departure warnings, and emergency braking systems, which rely heavily on AI technologies. Furthermore, regulatory frameworks are not just being developed at a national level but are also increasingly harmonized across regions to promote higher safety standards globally. Moreover, the legislation serves dual purposes, as it aids in improving road safety and acts as a catalyst for technological innovation within the automotive industry. Besides this, the regulations effectively act as an external force that compels automakers to focus on research and development (R&D) in AI technologies.
The significant technological advancements
Rapid technological advancements are pivotal in propelling the automotive AI market. In line with this, the progress in machine learning (ML) algorithms has enabled vehicles to make real-time decisions, thereby drastically improving their autonomous capabilities. Furthermore, the incorporation of advanced sensor technologies in object recognition and distance measurement applications, owing to their higher accuracy and durability, is positively influencing the market growth. Moreover, the utilization of data analytics to process and interpret large data sets in real-time for predictive maintenance, route optimization, and even rider comfort is contributing to the market growth. Besides this, technological advancements have resulted in cost reduction, making it more economically viable to integrate advanced AI features into a broader range of vehicles.
Software
Services
Hardware dominates the market
The report has provided a detailed breakup and analysis of the market based on component. This includes hardware, software, and services. According to the report, hardware represented the largest segment.
Hardware is dominating the market as the foundational capabilities for AI in vehicles stem from advanced hardware components, such as sensors, cameras, light detection and ranging (LiDAR), and central processing units (CPUs). These elements are essential for the collection and initial processing of real-time data, which is then used by AI algorithms for decision-making. Furthermore, the ever-increasing complexity and capabilities of AI algorithms, which require more robust and specialized hardware for optimal performance, are positively influencing the market growth. Additionally, the hardware serves as the backbone that enables the functionalities of various AI-based technologies, such as machine vision, spatial awareness, and real-time analytics. Moreover, compared to software, which can often be updated remotely to add new features, hardware requires a physical change in the component, making it a more stable but also critical investment.
Computer Vision
Natural Language Processing
A detailed breakup and analysis of the market based on the technology has also been provided in the report. This includes machine learning and deep learning, computer vision, and natural language processing.
Machine learning (ML) and deep learning are dominating the market due to their capability to facilitate real-time decision-making and predictive analysis, which are essential in modern vehicular applications. Furthermore, they can process vast quantities of data and learn from it, enabling features, such as adaptive cruise control, collision avoidance, and predictive maintenance. In addition, they can operate in sync with sensor technologies, such as LiDAR, radio detecting and ranging (RADAR), and cameras, thereby providing a comprehensive and integrated approach to vehicle automation.
Computer vision is witnessing significant growth due to its indispensable role in enabling real-time perception and decision-making capabilities, which is essential for various critical applications in automotive AI, including object detection, lane departure warning, and collision avoidance systems. Furthermore, the escalating adoption of computer vision to meet regulatory requirements regarding the safety of vehicles and pedestrians is favoring the market growth. Additionally, computer vision offers seamless integration with sensor fusion technologies, which combine data from different sensors like radars and LiDAR, to offer a more comprehensive understanding of the vehicle's surroundings.
Image Recognition
Signal Recognition
Data mining hold the largest share in the market
A detailed breakup and analysis of the market based on the process has also been provided in the report. This includes data mining, image recognition, and signal recognition. According to the report, data mining accounted for the largest market share.
Data mining is dominating the market due to its critical role in extracting valuable insights from vast amounts of data generated by modern vehicles. These insights serve as the foundation for many AI-based features, such as predictive maintenance and real-time decision-making. Furthermore, data mining techniques help to identify vehicle performance data, driver behavior, environmental conditions, and patterns and correlations that can be translated into actionable insights or improvements in AI algorithms. Besides this, it can analyze both structured and unstructured data, offering a comprehensive understanding of vehicle operations and user experiences. Moreover, data mining enables predictive analytics, which is one of the most promising applications in automotive AI. In addition, it is also essential for optimizing routing algorithms, improving fuel efficiency, and minimizing emissions, which are key objectives for modern vehicles.
Autonomous
Semi-autonomous hold the largest share in the market
A detailed breakup and analysis of the market based on the application has also been provided in the report. This includes semi-autonomous and autonomous. According to the report, semi-autonomous accounted for the largest market share.
The semi-autonomous is dominating the market as it offers enhanced safety features, such as lane departure warnings, adaptive cruise control, and emergency braking, that are easier to integrate into vehicles and have gained regulatory approval in many jurisdictions. Furthermore, several consumers are still skeptical about relinquishing full control to a machine. In line with this, semi-autonomous features allow drivers to experience the benefits of AI while retaining control over the vehicle. Moreover, semi-autonomous features can be integrated into vehicles at a fraction of the cost, making them more economically viable for both manufacturers and consumers. Additionally, the rapid rate of technological advancements in AI and machine learning (ML) algorithms, which allow for continuous upgrades in semi-autonomous systems, is supporting the market growth.
United States
Canada
Asia-Pacific
China
Japan
India
South Korea
Australia
Indonesia
Others
Europe
Germany
France
United Kingdom
Italy
Spain
Russia
Others
Latin America
Brazil
Mexico
Others
Middle East and Africa
North America hosts a large number of technology companies that are at the forefront of AI and automotive innovation. In addition, regional consumers are known for their early adoption of new technologies due to high average income levels. Furthermore, the imposition of various regulations by the regional governments that are conducive to the development and integration of AI technologies in the automotive sector is positively influencing the market growth. Besides this, the region is witnessing high levels of investment in research and innovation activities from government bodies and private organizations to accelerate the pace of innovation and implementation of AI features in vehicles. Moreover, the presence of world-class universities and research institutions in North America, which contributes to a highly skilled workforce that is adept at advanced technologies, including AI, is boosting the market growth.
Daimler AG
Ford Motor Company
Hyundai Motor Company
Intel Corporation
International Business Machines Corporation
Micron Technology Inc.
Microsoft Corporation
NVIDIA Corporation
Qualcomm Incorporated
Tesla Inc.
Toyota Motor Corporation
Uber Technologies Inc.
In March 2023, Ford Motor Company established Latitude AI, a subsidiary, to develop new automated driving technologies.
In August 2023, Hyundai Motor Company and Kia announced an investment of US$ 50 million in a Canadian AI semiconductor company to integrate AI into their future vehicle models.
2. What is the expected growth rate of the global automotive artificial intelligence market during 2024-2032?
3. What are the key factors driving the global automotive artificial intelligence market?
4. What has been the impact of COVID-19 on the global automotive artificial intelligence market?
5. What is the breakup of the global automotive artificial intelligence market based on the component?
6. What is the breakup of the global automotive artificial intelligence market based on the process?
7. What is the breakup of the global automotive artificial intelligence market based on the application?
8. What are the key regions in the global automotive artificial intelligence market?
9. Who are the key players/companies in the global automotive artificial intelligence market?
Automotive artificial intelligence (AI) refers to the integration of technology within vehicles to enhance their functionalities, safety, and user experience. It comprises various systems, such as driver assistance, in-car virtual assistants, predictive maintenance, and fully autonomous systems. Automotive AI is widely used in adaptive cruise control, collision avoidance, driver monitoring, voice-activated controls, traffic sign recognition, automated parking, and real-time traffic monitoring. It aids in enhancing safety, increasing efficiency, reducing emission levels, saving time, augmenting traffic flow, improving user experience, and promoting sustainability.
The rapid cost reduction in sensor technology and computing power, which is making AI implementation more financially viable for automotive manufacturers, is positively influencing the market growth. Besides this, the growing demand for AI in traffic management and route optimization owing to the increasing urbanization and subsequent traffic congestion are contributing to the market growth. Furthermore, the rising utilization of AI by automotive manufacturers to enable superior predictive maintenance, real-time decision-making, and personalized user experiences is supporting the market growth. In addition, the recent advancements in the Internet of Things (IoT) and vehicle-to-everything (V2X) communication that are offering new avenues for AI integration, such as advanced telematics and remote vehicle control, are fueling the market growth. Moreover, the increasing emphasis on sustainability is facilitating the demand for AI to optimize fuel efficiency and manage alternative fuel systems.
Automotive Artificial Intelligence Market Trends/Drivers:
The escalating demand for advanced featuresThe increasing consumer demand for advanced features is a prominent factor propelling the growth of the automotive artificial intelligence (AI) market. Users are becoming increasingly tech-savvy, leading to higher expectations for advanced features in vehicles, such as adaptive cruise control, automated parking, and advanced navigation systems. Furthermore, the push for convenience, especially among younger demographics who are deeply engaged with technology in their daily lives, is fueling the market growth. Apart from this, the growing congestion in urban centers is facilitating the demand for vehicles that offer intelligent features to manage the complexities of city driving. This shift in consumer expectations puts considerable pressure on manufacturers to adopt AI technologies in automotive design, not merely as a value-add but as a core component that directly influences purchasing decisions.
The imposition of various government regulations
Government regulations are playing an increasingly critical role in driving the incorporation of AI in the automotive sector. Road safety is becoming a paramount concern across the globe, prompting authorities to impose stricter safety guidelines and requirements for vehicles. These guidelines often mandate the incorporation of advanced safety features, such as collision avoidance systems, lane-departure warnings, and emergency braking systems, which rely heavily on AI technologies. Furthermore, regulatory frameworks are not just being developed at a national level but are also increasingly harmonized across regions to promote higher safety standards globally. Moreover, the legislation serves dual purposes, as it aids in improving road safety and acts as a catalyst for technological innovation within the automotive industry. Besides this, the regulations effectively act as an external force that compels automakers to focus on research and development (R&D) in AI technologies.
The significant technological advancements
Rapid technological advancements are pivotal in propelling the automotive AI market. In line with this, the progress in machine learning (ML) algorithms has enabled vehicles to make real-time decisions, thereby drastically improving their autonomous capabilities. Furthermore, the incorporation of advanced sensor technologies in object recognition and distance measurement applications, owing to their higher accuracy and durability, is positively influencing the market growth. Moreover, the utilization of data analytics to process and interpret large data sets in real-time for predictive maintenance, route optimization, and even rider comfort is contributing to the market growth. Besides this, technological advancements have resulted in cost reduction, making it more economically viable to integrate advanced AI features into a broader range of vehicles.
Automotive Artificial Intelligence Industry Segmentation:
The report provides an analysis of the key trends in each segment of the global automotive artificial intelligence market report, along with forecasts at the global, regional and country levels from 2024-2032. Our report has categorized the market based on component, technology, process, and application.Breakup by Component:
HardwareSoftware
Services
Hardware dominates the market
The report has provided a detailed breakup and analysis of the market based on component. This includes hardware, software, and services. According to the report, hardware represented the largest segment.
Hardware is dominating the market as the foundational capabilities for AI in vehicles stem from advanced hardware components, such as sensors, cameras, light detection and ranging (LiDAR), and central processing units (CPUs). These elements are essential for the collection and initial processing of real-time data, which is then used by AI algorithms for decision-making. Furthermore, the ever-increasing complexity and capabilities of AI algorithms, which require more robust and specialized hardware for optimal performance, are positively influencing the market growth. Additionally, the hardware serves as the backbone that enables the functionalities of various AI-based technologies, such as machine vision, spatial awareness, and real-time analytics. Moreover, compared to software, which can often be updated remotely to add new features, hardware requires a physical change in the component, making it a more stable but also critical investment.
Breakup by Technology:
Machine Learning and Deep LearningComputer Vision
Natural Language Processing
A detailed breakup and analysis of the market based on the technology has also been provided in the report. This includes machine learning and deep learning, computer vision, and natural language processing.
Machine learning (ML) and deep learning are dominating the market due to their capability to facilitate real-time decision-making and predictive analysis, which are essential in modern vehicular applications. Furthermore, they can process vast quantities of data and learn from it, enabling features, such as adaptive cruise control, collision avoidance, and predictive maintenance. In addition, they can operate in sync with sensor technologies, such as LiDAR, radio detecting and ranging (RADAR), and cameras, thereby providing a comprehensive and integrated approach to vehicle automation.
Computer vision is witnessing significant growth due to its indispensable role in enabling real-time perception and decision-making capabilities, which is essential for various critical applications in automotive AI, including object detection, lane departure warning, and collision avoidance systems. Furthermore, the escalating adoption of computer vision to meet regulatory requirements regarding the safety of vehicles and pedestrians is favoring the market growth. Additionally, computer vision offers seamless integration with sensor fusion technologies, which combine data from different sensors like radars and LiDAR, to offer a more comprehensive understanding of the vehicle's surroundings.
Breakup by Process:
Data MiningImage Recognition
Signal Recognition
Data mining hold the largest share in the market
A detailed breakup and analysis of the market based on the process has also been provided in the report. This includes data mining, image recognition, and signal recognition. According to the report, data mining accounted for the largest market share.
Data mining is dominating the market due to its critical role in extracting valuable insights from vast amounts of data generated by modern vehicles. These insights serve as the foundation for many AI-based features, such as predictive maintenance and real-time decision-making. Furthermore, data mining techniques help to identify vehicle performance data, driver behavior, environmental conditions, and patterns and correlations that can be translated into actionable insights or improvements in AI algorithms. Besides this, it can analyze both structured and unstructured data, offering a comprehensive understanding of vehicle operations and user experiences. Moreover, data mining enables predictive analytics, which is one of the most promising applications in automotive AI. In addition, it is also essential for optimizing routing algorithms, improving fuel efficiency, and minimizing emissions, which are key objectives for modern vehicles.
Breakup by Application:
Semi-AutonomousAutonomous
Semi-autonomous hold the largest share in the market
A detailed breakup and analysis of the market based on the application has also been provided in the report. This includes semi-autonomous and autonomous. According to the report, semi-autonomous accounted for the largest market share.
The semi-autonomous is dominating the market as it offers enhanced safety features, such as lane departure warnings, adaptive cruise control, and emergency braking, that are easier to integrate into vehicles and have gained regulatory approval in many jurisdictions. Furthermore, several consumers are still skeptical about relinquishing full control to a machine. In line with this, semi-autonomous features allow drivers to experience the benefits of AI while retaining control over the vehicle. Moreover, semi-autonomous features can be integrated into vehicles at a fraction of the cost, making them more economically viable for both manufacturers and consumers. Additionally, the rapid rate of technological advancements in AI and machine learning (ML) algorithms, which allow for continuous upgrades in semi-autonomous systems, is supporting the market growth.
Breakup by Region:
North AmericaUnited States
Canada
Asia-Pacific
China
Japan
India
South Korea
Australia
Indonesia
Others
Europe
Germany
France
United Kingdom
Italy
Spain
Russia
Others
Latin America
Brazil
Mexico
Others
Middle East and Africa
North America exhibits a clear dominance, accounting for the largest automotive artificial intelligence market share
The market research report has also provided a comprehensive analysis of all the major regional markets, which include North America (the United States and Canada); Asia Pacific (China, Japan, India, South Korea, Australia, Indonesia, and others); Europe (Germany, France, the United Kingdom, Italy, Spain, Russia, and others); Latin America (Brazil, Mexico, and others); and the Middle East and Africa. According to the report, North America accounted for the largest market share.North America hosts a large number of technology companies that are at the forefront of AI and automotive innovation. In addition, regional consumers are known for their early adoption of new technologies due to high average income levels. Furthermore, the imposition of various regulations by the regional governments that are conducive to the development and integration of AI technologies in the automotive sector is positively influencing the market growth. Besides this, the region is witnessing high levels of investment in research and innovation activities from government bodies and private organizations to accelerate the pace of innovation and implementation of AI features in vehicles. Moreover, the presence of world-class universities and research institutions in North America, which contributes to a highly skilled workforce that is adept at advanced technologies, including AI, is boosting the market growth.
Competitive Landscape:
Leading companies are developing more sophisticated AI algorithms to enhance autonomous driving capabilities and optimize vehicle operations. Furthermore, they are collaborating with other industry stakeholders to bring together expertise in hardware and software, creating synergies that drive the rapid development of automotive AI technologies. Besides this, top players are extensively utilizing data analytics to improve their products and refine their AI algorithms. Moreover, key players are engaging with consumers to understand what features are most desired and aim to incorporate these in their offerings. They are also adapting their technologies for different markets and driving conditions around the world, which assists them in addressing a broad spectrum of consumer needs and regulatory requirements. Moreover, companies are aligning their AI technologies with sustainability goals, developing solutions that contribute to fuel efficiency and reduced carbon emissions.The report has provided a comprehensive analysis of the competitive landscape in the market. Detailed profiles of all major companies have also been provided. Some of the key players in the market include:
Bayerische Motoren Werke AGDaimler AG
Ford Motor Company
Hyundai Motor Company
Intel Corporation
International Business Machines Corporation
Micron Technology Inc.
Microsoft Corporation
NVIDIA Corporation
Qualcomm Incorporated
Tesla Inc.
Toyota Motor Corporation
Uber Technologies Inc.
Recent Developments:
In March 2023, Daimler AG announced that it had signed an agreement to acquire Algolux, an AI company known for its expertise in machine learning (ML) and computer vision.In March 2023, Ford Motor Company established Latitude AI, a subsidiary, to develop new automated driving technologies.
In August 2023, Hyundai Motor Company and Kia announced an investment of US$ 50 million in a Canadian AI semiconductor company to integrate AI into their future vehicle models.
Key Questions Answered in This Report
1. How big is the global automotive artificial intelligence market?2. What is the expected growth rate of the global automotive artificial intelligence market during 2024-2032?
3. What are the key factors driving the global automotive artificial intelligence market?
4. What has been the impact of COVID-19 on the global automotive artificial intelligence market?
5. What is the breakup of the global automotive artificial intelligence market based on the component?
6. What is the breakup of the global automotive artificial intelligence market based on the process?
7. What is the breakup of the global automotive artificial intelligence market based on the application?
8. What are the key regions in the global automotive artificial intelligence market?
9. Who are the key players/companies in the global automotive artificial intelligence market?
Table of Contents
1 Preface3 Executive Summary12 Value Chain Analysis14 Price Analysis
2 Scope and Methodology
4 Introduction
5 Global Automotive Artificial Intelligence Market
6 Market Breakup by Component
7 Market Breakup by Technology
8 Market Breakup by Process
9 Market Breakup by Application
10 Market Breakup by Region
11 SWOT Analysis
13 Porters Five Forces Analysis
15 Competitive Landscape
List of Figures
List of Tables
Companies Mentioned
- Bayerische Motoren Werke AG
- Daimler AG
- Ford Motor Company
- Hyundai Motor Company
- Intel Corporation
- International Business Machines Corporation
- Micron Technology Inc.
- Microsoft Corporation
- NVIDIA Corporation
- Qualcomm Incorporated
- Tesla Inc.
- Toyota Motor Corporation
- Uber Technologies Inc.
Methodology
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Table Information
| Report Attribute | Details |
|---|---|
| No. of Pages | 149 |
| Published | July 2024 |
| Forecast Period | 2023 - 2032 |
| Estimated Market Value ( USD | $ 3.9 Billion |
| Forecasted Market Value ( USD | $ 33.9 Billion |
| Compound Annual Growth Rate | 27.2% |
| Regions Covered | Global |
| No. of Companies Mentioned | 13 |
