Automotive Artificial Intelligence Market Size, Trends, Share, Growth | Report 2022-2030
The global automotive artificial intelligence market size will witness a notable gain on the backdrop of the trend for adaptive cruise control (ACC), advanced driver assistance system (ADAS) and blind-spot alert. Automakers are expected to harness advanced technologies to bring safe and innovative vehicles into the market. OEMs are expected to emphasize the production of autonomous vehicles and the integration of AI in cars for driver monitoring, risk assessment, and personalization.
AI has witnessed significant traction across the automotive value chain, including manufacturing, production, supply, design, and post-production. Prominently, aftermarket services, such as insurance and predictive maintenance, have also witnessed a paradigm shift due to the trend for AI. The personalization trend has leveraged connected vehicles as the automotive industry pushes into a period of digital transformation. Furthermore, OEMs and automakers are prioritizing AI-enabled technologies, including gesture-control features, natural language processing, and deep learning neural networks, thereby boosting industry growth for AI.
Tier−1 suppliers and car developers are expected to emphasize expanding natural language processing (NLP) technologies. The automotive sector could cash in on the rising prominence of NLP to enhance the driving and passenger experience. For instance, an AI-powered vehicle with an interactive experience can enable passengers to request the desired entertainment (movie or local weather) and can provide passengers through online gaming.
In terms of offering, the hardware segment could account for a considerable share of the global market on the back of the rising prominence of application-specific chips. An uptick in demand for autonomous driving functions and ADAS will solidify the need for chip hardware. Industry players expect hardware to serve as a major differentiator in AI as memory, networks, and processors will continue to witness technological innovations over the next few years.
Based on technology, the deep learning segment is likely to expand at a robust CAGR in the wake of the rising footfall of self-driving vehicles. The technology has gained impetus for data analysis, speech & audio recognition, object detection, face recognition, and image processing. To illustrate, deep learning has gained momentum in ADAS for pedestrian detection and traffic sign recognition. Advanced technology has also become sought-after for identifying drivers in a fleet of cars.
With respect to application, the autonomous driving segment will contribute notably to the automotive artificial intelligence market share. Stakeholders anticipate computer vision and deep learning to play an invaluable role in boosting autonomous driving across emerging and advanced economies. Leading companies are expected to emphasize self-driving cars in the ensuing period. To illustrate, in May 2022, Tesla asserted it would have self-driving cars without the need for human drivers in May 2023.
North America’s automotive artificial intelligence market forecast will be strong in light of the trend for deep learning, machine learning, and autonomous driving. The U.S. and Canada have witnessed increased traction for self-driving cars to minimize traffic congestion and human errors. Moreover, the presence of leading companies, such as Alphabet, GM, IBM Corporation, Microsoft, and Tesla, has boded well for regional growth. For instance, in September 2021, General Motors (GM) announced an infusion of funds into a U.S. startup Oculii. GM contemplates using the latter’s low-cost software to bolster radars’ resolution to ramp up self-driving cars and partially automated vehicles.
The competitive scenario suggests prominent companies will invest in organic and inorganic strategies to tap into the global market. Specifically, in July 2022, Aurora Labs reportedly raised USD 63 million in Series C financing to bring AI to the software-defined vehicle. The Israel-based company expects the solution will keep software secure and safe from cybersecurity attacks and faults.
In March 2022, Waymo, Google’s sibling company, announced it would offer self-driving ride-hailing services in San Francisco and expand autonomous rides to downtown Phoenix. Meanwhile, in June 2021, Waymo suggested it would be pouring USD 2.5 billion to bolster its autonomous driving technology.
Market Segmentation
Chapter 1. Introduction
1.1. Research Objective
1.2. Scope of the Study
1.3. Definition
Chapter 2. Research Methodology
2.1. Research Approach
2.2. Data Sources
2.3. Assumptions & Limitations
Chapter 3. Executive Summary
3.1. Market Snapshot
Chapter 4. Market Variables and Scope
4.1. Introduction
4.2. Market Classification and Scope
4.3. Industry Value Chain Analysis
4.3.1. Raw Material Procurement Analysis
4.3.2. Sales and Distribution Channel Analysis
4.3.3. Downstream Buyer Analysis
Chapter 5. COVID 19 Impact on Automotive Artificial Intelligence Market
5.1. COVID-19 Landscape: Automotive Artificial Intelligence Industry Impact
5.2. COVID 19 - Impact Assessment for the Industry
5.3. COVID 19 Impact: Global Major Government Policy
5.4. Market Trends and Opportunities in the COVID-19 Landscape
Chapter 6. Market Dynamics Analysis and Trends
6.1. Market Dynamics
6.1.1. Market Drivers
6.1.2. Market Restraints
6.1.3. Market Opportunities
6.2. Porter’s Five Forces Analysis
6.2.1. Bargaining power of suppliers
6.2.2. Bargaining power of buyers
6.2.3. Threat of substitute
6.2.4. Threat of new entrants
6.2.5. Degree of competition
Chapter 7. Competitive Landscape
7.1.1. Company Market Share/Positioning Analysis
7.1.2. Key Strategies Adopted by Players
7.1.3. Vendor Landscape
7.1.3.1. List of Suppliers
7.1.3.2. List of Buyers
Chapter 8. Global Automotive Artificial Intelligence Market, By Offering
8.1. Automotive Artificial Intelligence Market, by Offering, 2022-2030
8.1.1 Hardware
8.1.1.1. Market Revenue and Forecast (2017-2030)
8.1.2. Software
8.1.2.1. Market Revenue and Forecast (2017-2030)
8.1.3. Service
8.1.3.1. Market Revenue and Forecast (2017-2030)
Chapter 9. Global Automotive Artificial Intelligence Market, By Technology
9.1. Automotive Artificial Intelligence Market, by Technology, 2022-2030
9.1.1. Machine Learning
9.1.1.1. Market Revenue and Forecast (2017-2030)
9.1.2. Deep Learning
9.1.2.1. Market Revenue and Forecast (2017-2030)
9.1.3. Context Awareness
9.1.3.1. Market Revenue and Forecast (2017-2030)
9.1.4. Computer Vision
9.1.4.1. Market Revenue and Forecast (2017-2030)
9.1.5. Natural Language Processing
9.1.5.1. Market Revenue and Forecast (2017-2030)
Chapter 10. Global Automotive Artificial Intelligence Market, By Application
10.1. Automotive Artificial Intelligence Market, by Application, 2022-2030
10.1.1. Autonomous Driving
10.1.1.1. Market Revenue and Forecast (2017-2030)
10.1.2. Human–Machine Interface
10.1.2.1. Market Revenue and Forecast (2017-2030)
10.1.3. Semi-autonomous Driving
10.1.3.1. Market Revenue and Forecast (2017-2030)
Chapter 11. Global Automotive Artificial Intelligence Market, Regional Estimates and Trend Forecast
11.1. North America
11.1.1. Market Revenue and Forecast, by Offering (2017-2030)
11.1.2. Market Revenue and Forecast, by Technology (2017-2030)
11.1.3. Market Revenue and Forecast, by Application (2017-2030)
11.1.4. U.S.
11.1.4.1. Market Revenue and Forecast, by Offering (2017-2030)
11.1.4.2. Market Revenue and Forecast, by Technology (2017-2030)
11.1.4.3. Market Revenue and Forecast, by Application (2017-2030)
11.1.5. Rest of North America
11.1.5.1. Market Revenue and Forecast, by Offering (2017-2030)
11.1.5.2. Market Revenue and Forecast, by Technology (2017-2030)
11.1.5.3. Market Revenue and Forecast, by Application (2017-2030)
11.2. Europe
11.2.1. Market Revenue and Forecast, by Offering (2017-2030)
11.2.2. Market Revenue and Forecast, by Technology (2017-2030)
11.2.3. Market Revenue and Forecast, by Application (2017-2030)
11.2.4. UK
11.2.4.1. Market Revenue and Forecast, by Offering (2017-2030)
11.2.4.2. Market Revenue and Forecast, by Technology (2017-2030)
11.2.4.3. Market Revenue and Forecast, by Application (2017-2030)
11.2.5. Germany
11.2.5.1. Market Revenue and Forecast, by Offering (2017-2030)
11.2.5.2. Market Revenue and Forecast, by Technology (2017-2030)
11.2.5.3. Market Revenue and Forecast, by Application (2017-2030)
11.2.6. France
11.2.6.1. Market Revenue and Forecast, by Offering (2017-2030)
11.2.6.2. Market Revenue and Forecast, by Technology (2017-2030)
11.2.6.3. Market Revenue and Forecast, by Application (2017-2030)
11.2.7. Rest of Europe
11.2.7.1. Market Revenue and Forecast, by Offering (2017-2030)
11.2.7.2. Market Revenue and Forecast, by Technology (2017-2030)
11.2.7.3. Market Revenue and Forecast, by Application (2017-2030)
11.3. APAC
11.3.1. Market Revenue and Forecast, by Offering (2017-2030)
11.3.2. Market Revenue and Forecast, by Technology (2017-2030)
11.3.3. Market Revenue and Forecast, by Application (2017-2030)
11.3.4. India
11.3.4.1. Market Revenue and Forecast, by Offering (2017-2030)
11.3.4.2. Market Revenue and Forecast, by Technology (2017-2030)
11.3.4.3. Market Revenue and Forecast, by Application (2017-2030)
11.3.5. China
11.3.5.1. Market Revenue and Forecast, by Offering (2017-2030)
11.3.5.2. Market Revenue and Forecast, by Technology (2017-2030)
11.3.5.3. Market Revenue and Forecast, by Application (2017-2030)
11.3.6. Japan
11.3.6.1. Market Revenue and Forecast, by Offering (2017-2030)
11.3.6.2. Market Revenue and Forecast, by Technology (2017-2030)
11.3.6.3. Market Revenue and Forecast, by Application (2017-2030)
11.3.7. Rest of APAC
11.3.7.1. Market Revenue and Forecast, by Offering (2017-2030)
11.3.7.2. Market Revenue and Forecast, by Technology (2017-2030)
11.3.7.3. Market Revenue and Forecast, by Application (2017-2030)
11.4. MEA
11.4.1. Market Revenue and Forecast, by Offering (2017-2030)
11.4.2. Market Revenue and Forecast, by Technology (2017-2030)
11.4.3. Market Revenue and Forecast, by Application (2017-2030)
11.4.4. GCC
11.4.4.1. Market Revenue and Forecast, by Offering (2017-2030)
11.4.4.2. Market Revenue and Forecast, by Technology (2017-2030)
11.4.4.3. Market Revenue and Forecast, by Application (2017-2030)
11.4.5. North Africa
11.4.5.1. Market Revenue and Forecast, by Offering (2017-2030)
11.4.5.2. Market Revenue and Forecast, by Technology (2017-2030)
11.4.5.3. Market Revenue and Forecast, by Application (2017-2030)
11.4.6. South Africa
11.4.6.1. Market Revenue and Forecast, by Offering (2017-2030)
11.4.6.2. Market Revenue and Forecast, by Technology (2017-2030)
11.4.6.3. Market Revenue and Forecast, by Application (2017-2030)
11.4.7. Rest of MEA
11.4.7.1. Market Revenue and Forecast, by Offering (2017-2030)
11.4.7.2. Market Revenue and Forecast, by Technology (2017-2030)
11.4.7.3. Market Revenue and Forecast, by Application (2017-2030)
11.5. Latin America
11.5.1. Market Revenue and Forecast, by Offering (2017-2030)
11.5.2. Market Revenue and Forecast, by Technology (2017-2030)
11.5.3. Market Revenue and Forecast, by Application (2017-2030)
11.5.4. Brazil
11.5.4.1. Market Revenue and Forecast, by Offering (2017-2030)
11.5.4.2. Market Revenue and Forecast, by Technology (2017-2030)
11.5.4.3. Market Revenue and Forecast, by Application (2017-2030)
11.5.5. Rest of LATAM
11.5.5.1. Market Revenue and Forecast, by Offering (2017-2030)
11.5.5.2. Market Revenue and Forecast, by Technology (2017-2030)
11.5.5.3. Market Revenue and Forecast, by Application (2017-2030)
Chapter 12. Company Profiles
12.1. Alphabet
12.1.1. Company Overview
12.1.2. Product Offerings
12.1.3. Financial Performance
12.1.4. Recent Initiatives
12.2. GM
12.2.1. Company Overview
12.2.2. Product Offerings
12.2.3. Financial Performance
12.2.4. Recent Initiatives
12.3. IBM Corporation
12.3.1. Company Overview
12.3.2. Product Offerings
12.3.3. Financial Performance
12.3.4. Recent Initiatives
12.4. Microsoft
12.4.1. Company Overview
12.4.2. Product Offerings
12.4.3. Financial Performance
12.4.4. Recent Initiatives
12.5. Tesla
12.5.1. Company Overview
12.5.2. Product Offerings
12.5.3. Financial Performance
12.5.4. Recent Initiatives
Chapter 13. Research Methodology
13.1. Primary Research
13.2. Secondary Research
13.3. Assumptions
Chapter 14. Appendix
14.1. About Us
14.2. Glossary of Terms
Cross-segment Market Size and Analysis for
Mentioned Segments
Additional Company Profiles (Upto 5 With No Cost)
Additional Countries (Apart From Mentioned Countries)
Country/Region-specific Report
Go To Market Strategy
Region Specific Market DynamicsRegion Level Market Share Import Export AnalysisProduction AnalysisOthers