Automotive Artificial Intelligence Market Report

Market Insights

The global automotive artificial intelligence market is expected to grow from USD 2.15 billion in 2022 to USD 9.47 billion by 2029 at a CAGR of 23.6% during the forecast period.

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What is Automotive Artificial Intelligence?

Automotive Artificial Intelligence (AI) refers to the integration of AI technology in automobiles. This includes features such as advanced driver assistance systems (ADAS), self-driving capabilities, and intelligent infotainment systems. ADAS uses AI to assist drivers with tasks such as lane departure warnings, collision avoidance, and adaptive cruise control.

Self-driving cars rely on AI to analyze data from sensors, cameras, and other inputs to make decisions and navigate roads. Intelligent infotainment systems use AI to personalize the driving experience, providing recommendations based on user preferences and driving patterns. AI is transforming the automotive industry, making driving safer, more efficient, and enjoyable.

The market is expected to experience growth during the forecast period due to factors such as an increase in demand for improved user experience and convenient features, as well as the growing adoption of ADAS technology by OEMs.

Key Players

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

Market Dynamics

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 frequently 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 an optimal interior atmosphere for the driver, resulting in a personalized and engaging user experience.

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 high 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.

Segment Analysis

By Application Type

The human-machine interface (HMI) application segment to account 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 in a seamless manner. Key components of HMI include electromechanical devices such as keypads, pointing devices, indicators, and alarms.

The infotainment category comprises of 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 own vehicles and where infrastructure is improving are also driving the demand for advanced HMI systems.

By Technology Type

Machine learning to account for the second largest share of the automotive artificial intelligence market during the forecast period. By utilizing 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 frequently evolving, machine learning approaches are especially effective in powering systems with novel insights.

Regional Analysis

By 2029, 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 moderate expansion of automotive artificial intelligence in this region is attributed to the swift advancement of autonomous vehicle technology, coupled with stringent government regulations pertaining to road safety.

Additionally, the presence of numerous major technological firms within the region facilitates 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.

Research Methodology

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.

More than 1,000 authenticated secondary sources, such as company annual reports, fact books, press releases, journals, investor presentations, white papers, patents, and articles, have been leveraged to gather the data.

We conducted more than 15 detailed primary interviews with the market players across the value chain in all four regions and industry experts to obtain both qualitative and quantitative insights.

Report Features

This report provides market intelligence in the most comprehensive way. The report structure has been kept such that it offers maximum business value. It provides critical insights into the market dynamics and will enable strategic decision making for the existing market players as well as those willing to enter the market. The following are the key features of the report:

• Market structure: Overview, industry life cycle analysis, supply chain analysis.
• Market Environment analysis: Growth drivers and constraints, Porter’s five forces analysis, SWOT analysis.
• Market trend and forecast analysis.
• Market segment trend and forecast.
• Competitive landscape and dynamics: Market share, Product Portfolio, New Product Launches, etc.
• Attractive market segments and associated growth opportunities.
• Emerging trends.
• Strategic growth opportunities for the existing and new players.
• Key success factors.

Customization Options

With this detailed report, Stratview Research offers one of the following free customization options to our respectable clients:

Company Profiling

• Detailed profiling of additional market players (up to three players)
• SWOT analysis of key players (up to three players)

Competitive Benchmarking

• Benchmarking of key players on the following parameters: product portfolio, geographical reach, regional presence, and strategic alliances

Custom Research: Stratview research offers custom research services across the sectors. In case of any custom research requirement related to market assessment, competitive benchmarking, sourcing and procurement, target screening, and others, please send your inquiry to sales@Stratviewresearch.com

Recent Developments

• In February 2023, Mercedes-Benz and NVIDIA entered into 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 into a multi-year technology collaboration to utilize 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.