Automotive Artificial Intelligence Market is segmented by Component Type (Microprocessors, Graphics Processing Unit (GPU), Field Programmable Gate Array (FPGA), Memory and Storage Systems, Image Sensors, Biometric Scanners), Offering Type (Hardware, Software), Technology Type (Deep Learning, Machine Learning, Computer Vision, Context-Aware Computing, Natural Language Processing), Process Type (Signal Recognition, Image Recognition, Data Mining), Application Type (Human–Machine Interface (HMI), Semi-Autonomous Driving, Autonomous Driving, Identity Authentication, Driver Monitoring, Autonomous Driving Processor Chips), and Region (North America, Europe, Asia-Pacific, and the Rest of the World).
Automotive Artificial Intelligence Market is segmented by Component Type (Microprocessors, Graphics Processing Unit (GPU), Field Programmable Gate Array (FPGA), Memory and Storage Systems, Image Sensors, Biometric Scanners), Offering Type...
“TheAutomotive Artificial Intelligence Market was estimated atUS$ 2.15 billion in 2022and is expected to grow at a healthyCAGR of 23.6%during 2023-2029 to reachUS$ 9.47 billion by 2029.”
Automotive Artificial Intelligence (AI) refers to the integration of advanced machine learning and computational algorithms within vehicles to enhance their functionality, safety, and autonomous capabilities. AI in the automotive industry enables vehicles to process and interpret real-time data from various sensors, cameras, and radar systems, empowering them to make intelligent decisions and adapt to changing driving conditions. This technology plays a crucial role in autonomous vehicles, allowing them to navigate, recognize obstacles, and make split-second decisions to ensure safe and efficient transportation.
Automotive AI also contributes to features like voice recognition, natural language processing, and predictive maintenance, enhancing the overall driving experience and paving the way for the future of smart, self-driving automobiles.
Driver: Increasing demand for enhanced user experience
Human-machine interface (HMI) solutions for the automotive industry have made it easier for users to control and operate, leading to an improved user experience. These solutions offer control over various applications such as music systems, vehicle lights, and infotainment systems.
In the past, the cost of electronics systems in a vehicle only accounted for 1-2% of the total vehicle cost. However, due to the increasing demand for enhanced user experience and convenience features, this share has risen to 8-12%.
Modern vehicles often incorporate driver assistance technology that heavily relies on AI. This technology accurately detects driver fatigue or drowsiness by monitoring their eyes. To enhance the driving experience and reduce fatigue, the car's AI system learns about the driver's preferences, such as preferred temperature settings, songs, and destinations. Automotive companies collaborate with software providers to ensure that AI creates the best interior atmosphere for the driver, resulting in a personalized and engaging user experience.
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Restraint: High cost of vehicle
The high cost of introducing new commercialized technological systems is expected to make autonomous vehicles expensive, particularly since most advanced technologies are incorporated into luxury and premium cars with a limited customer base due to their high price.
As a result, the inflated cost of autonomous vehicles is expected to have a dampening effect on market growth. The demand for expensive autonomous vehicles is likely to be lower than that for semi-autonomous vehicles. For autonomous cars to be effective, the supporting infrastructure must also accommodate the technology. For instance, lane assist technology requires lane lines on the road for the system to detect and adjust vehicle position, which could increase infrastructure development costs.
The installation of advanced features such as blind spot detection (BSD), lane departure warning (LDW), adaptive cruise control (ACC), and forward collision warning system (FCWS) can increase the overall cost of a vehicle. While cost is not a significant concern for premium cars, the demand for small and medium-segment cars is affected by the vehicle cost. Every automaker strives to provide efficient safety features at an affordable price. The increasing cost of vehicles due to enhanced safety features could hinder the growth of the automotive AI market.
The human-machine interface (HMI) application segment accounts for the largest share of the market during the forecast period.
Technology Type
Deep Learning, Machine Learning, Computer Vision, Context-Aware Computing, Natural Language Processing
The machine learning segment dominates the market during the forecast period.
Region Analysis
North America, Europe, Asia-Pacific, and the Rest of the World
North America is projected to hold the largest portion of the market during the forecast period.
By Application Type
“The human-machine interface (HMI) application segment accounts for the largest share of the automotive artificial intelligence market during the forecast period.”
HMI allows drivers and passengers to interact with the vehicle by delivering convenience, information, and entertainment seamlessly. Key components of HMI include electromechanical devices such as keypads, pointing devices, indicators, and alarms.
The infotainment category comprises advanced features such as speech recognition, eye tracking, monitoring driving behavior, gesture recognition, and a database of natural languages. OEMs are integrating advanced HMI solutions to provide a unique and innovative user experience and differentiate their brand image. The intelligent car concept is evolving rapidly, with features such as self-braking, advanced cruise control, and self-parking becoming increasingly common. These developments will create numerous opportunities for automotive HMI systems.
Developed countries where people prefer to travel long distances in their vehicles and where infrastructure is improving are also driving the demand for advanced HMI systems.
By Technology Type
“Machine learning accounts for the second largest share of the automotive artificial intelligence market during the forecast period.”
By using machine learning, vehicles are equipped with the capability to examine and understand diverse driving scenarios, resulting in fewer accidents and enhanced safety and efficiency. Through this technology, precise models can be created to provide direction for future actions, while also quickly detecting patterns at a previously unprecedented scale.
The machine learning field encompasses several different technologies, such as supervised learning, unsupervised learning, deep learning, and reinforcement learning. Within the automotive industry, where datasets are extensive, varied, and often evolving, machine-learning approaches are especially effective in powering systems with novel insights.
Regional Analysis
“North America is projected to hold the largest portion of the automotive artificial intelligence market during the forecast period.”
The moderate expansion of automotive artificial intelligence in this region is attributed to the swift advancement of autonomous vehicle technology, coupled with stringent government regulations on road safety. Additionally, the presence of numerous major technological firms within the region helps the early introduction and widespread adoption of technologies, including automotive artificial intelligence.
Government incentives and funding serve as crucial drivers in the development of this technology. The automotive industry in the US is highly advanced, with industry leaders such as Ford Motor Company, General Motors, and Fiat-Chrysler Automotive continually updating their product portfolios. Vehicles in the US come equipped with sophisticated features such as adaptive cruise control, lane departure warning systems, voice recognition, gesture recognition, and blind spot detection.
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Key Players
The market is highly populated with the presence of several local, regional, and global players. Most of the major players compete in some of the governing factors including price, product offerings, regional presence, etc.
The following are the key players in the automotive artificial intelligence market (arranged alphabetically).
Note:The above list does not necessarily include all the top players in the market.
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In-depth Analysis of the Automotive Artificial Intelligence Market
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Global, regional, and country-level historical data and forecasts
Which are the most attractive market segments?
Market Segment Analysis and Forecast
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Porter’s five forces analysis, PEST analysis, Life cycle analysis
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Drivers & challenges
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This report offers high-quality insights and is the outcome of a detailed research methodology comprising extensive secondary research, rigorous primary interviews with industry stakeholders, and validation and triangulation with Stratview Research’s internal database and statistical tools.
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Recent Market News
In February 2023, Mercedes-Benz and NVIDIA entered a partnership to take vehicle product lifecycle digital with NVIDIA’s AI and omniverse.
In February 2023, Mercedes-Benz and Google partnered to create next-generation navigation experience. Mercedes-Benz aims to build its own branded navigation using new in-car geospatial data and Google Maps’ navigation capabilities.
In April 2022, Stellantis N.V. and Qualcomm Technologies, Inc. entered a multi-year technology collaboration to use the latest Snapdragon Digital Chassis advanced features to deliver intelligent, customizable, and immersive in-vehicle experiences to millions of vehicles across Stellantis’ 14 automotive brands beginning in 2024.
In April 2022, Qualcomm completed acquisition of Arriver Business from SSW Partners. Through this acquisition, Qualcomm Technologies incorporated Arriver’s Computer Vision, Drive Policy, and Driver Assistance assets into its Snapdragon Ride Platform portfolio.
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Automotive Artificial Intelligence (AI) refers to the integration of advanced machine learning and computational algorithms within vehicles to enhance their functionality, safety, and autonomous capabilities. AI in the automotive industry enables vehicles to process and interpret real-time data from various sensors, cameras, and radar systems, empowering them to make intelligent decisions and adapt to changing driving conditions. This technology plays a crucial role in autonomous vehicles, allowing them to navigate, recognize obstacles, and make split-second decisions to ensure safe and efficient transportation.
Automotive AI also contributes to features like voice recognition, natural language processing, and predictive maintenance, enhancing the overall driving experience and paving the way for the future of smart, self-driving automobiles.
The major players operating in the global Automotive Artificial Intelligence market are Alphabet Inc., Microsoft Corporation, NVIDIA Corporation, Intel Corporation, International Business Machines Corporation, Qualcomm Inc., Tesla, Inc., Bayerische Motoren Werke AG, Xilinx, Inc., Micron Technology, Harman International Industries, Inc., Volvo Cars, Audi AG, General Motors Company, Ford Motor Company, Honda Motor Coltd., Toyota Motor Corporation, Hyundai Motor Co., Ltd, Uber Technologies, Inc, Daimler AG, Didi Chuxing.
North America is projected to hold the largest portion of the automotive artificial intelligence market during the forecast period, and this growth trend is anticipated to persist.
The human-machine interface (HMI) application segment to account for the largest share of the automotive artificial intelligence market during the forecast period.
