The global demand for Automotive AI Chipset Market is presumed to reach the market size of nearly USD 25.97 BN by 2030 from USD 3.56 BN in 2022 with a CAGR of 28.2% under the study period 2023 - 2030.
An automotive AI (Artificial Intelligence) chipset, also known as an automotive AI processor or automotive AI SoC (System-on-Chip), is a specialized integrated circuit designed to enable advanced artificial intelligence and machine learning capabilities in vehicles. These chipsets are specifically tailored to meet the computational demands of AI algorithms and applications used in the automotive industry. These play a critical role in enabling autonomous driving, advanced driver assistance systems (ADAS), in-vehicle infotainment, and various other AI-related functionalities in modern vehicles.
The automotive AI chipset market is witnessing remarkable growth, fueled by factors that underscore the increasing role of AI in the automotive sector. One of the primary drivers is the development of autonomous vehicles, where AI chipsets are pivotal in processing extensive sensor data and making real-time decisions, a fundamental requirement for self-driving cars. Additionally, the adoption of Advanced Driver Assistance Systems (ADAS) is on the rise, enhancing vehicle safety and convenience and heavily reliant on AI chipsets. In-vehicle infotainment systems are becoming increasingly sophisticated, incorporating AI-driven features for voice recognition, user-specific settings, and entertainment, improving the in-car experience. Regulatory requirements and emissions standards worldwide are pushing automakers to embrace AI-driven technologies for compliance and enhanced control. Connected vehicles and the growth of EVs also contribute to the demand for AI chipsets. These chipsets optimize power management, extend battery life, and facilitate vehicle-to-vehicle and vehicle-to-infrastructure communication, all critical elements for safety and efficiency in the evolving automotive landscape. Furthermore, the pursuit of energy efficiency, improved user experiences, and the growing emphasis on safety features continue to propel the market, with automakers and tech companies vying for a competitive edge through AI integration. As AI continues to revolutionize the automotive industry, the demand for powerful and efficient AI chipsets is set to remain robust.
The research report covers Porter’s Five Forces Model, Market Attractiveness Analysis, and Value Chain analysis. These tools help to get a clear picture of the industry’s structure and evaluate the competition attractiveness at a global level. Additionally, these tools also give an inclusive assessment of each segment in the global market of automotive ai chipset. The growth and trends of automotive ai chipset industry provide a holistic approach to this study.
This section of the automotive ai chipset market report provides detailed data on the segments at country and regional level, thereby assisting the strategist in identifying the target demographics for the respective product or services with the upcoming opportunities.
By Product
By Application
By Processing Type
By Vehicle Type
This section covers the regional outlook, which accentuates current and future demand for the Automotive AI Chipset market across North America, Europe, Asia-Pacific, Latin America, and Middle East & Africa. Further, the report focuses on demand, estimation, and forecast for individual application segments across all the prominent regions.
The research report also covers the comprehensive profiles of the key players in the market and an in-depth view of the competitive landscape worldwide. The major players in the Automotive AI Chipset market include Nvidia, Qualcomm, Intel, Renesas Technologies, and others. This section consists of a holistic view of the competitive landscape that includes various strategic developments such as key mergers & acquisitions, future capacities, partnerships, financial overviews, collaborations, new product developments, new product launches, and other developments.
1 . PREFACE
1.1. Report Description
1.1.1. Objective
1.1.2. Target Audience
1.1.3. Unique Selling Proposition (USP) & offerings
1.2. Research Scope
1.3. Research Methodology
1.3.1. Market Research Process
1.3.2. Market Research Methodology
2 . EXECUTIVE SUMMARY
2.1. Highlights of Market
2.2. Global Market Snapshot
3 . AUTOMOTIVE AI CHIPSET – INDUSTRY ANALYSIS
3.1. Introduction - Market Dynamics
3.2. Market Drivers
3.3. Market Restraints
3.4. Opportunities
3.5. Industry Trends
3.6. Porter’s Five Force Analysis
3.7. Market Attractiveness Analysis
3.7.1 Market Attractiveness Analysis By Product
3.7.2 Market Attractiveness Analysis By Application
3.7.3 Market Attractiveness Analysis By Processing Type
3.7.4 Market Attractiveness Analysis By Vehicle Type
3.7.5 Market Attractiveness Analysis By Region
4 . VALUE CHAIN ANALYSIS
4.1. Value Chain Analysis
4.2. Raw Material Analysis
4.2.1. List of Raw Materials
4.2.2. Raw Material Manufactures List
4.2.3. Price Trend of Key Raw Materials
4.3. List of Potential Buyers
4.4. Marketing Channel
4.4.1. Direct Marketing
4.4.2. Indirect Marketing
4.4.3. Marketing Channel Development Trend
5 . GLOBAL AUTOMOTIVE AI CHIPSET MARKET ANALYSIS BY PRODUCT
5.1 Overview by Product
5.2 Historical and Forecast Data
5.3 Analysis by Product
5.4 GPU Historic and Forecast Sales by Regions
5.5 ASIC Historic and Forecast Sales by Regions
5.6 FGPA Historic and Forecast Sales by Regions
5.7 CPU Historic and Forecast Sales by Regions
6 . GLOBAL AUTOMOTIVE AI CHIPSET MARKET ANALYSIS BY APPLICATION
6.1 Overview by Application
6.2 Historical and Forecast Data
6.3 Analysis by Application
6.4 Advanced Driver Assistance Systems (ADAS) Historic and Forecast Sales by Regions
6 ...