Global Automotive AI 麻豆原创 2024 by Company, Regions, Type and Application, Forecast to 2030

Publication ID:

GIR102412863

Publication Date:

October 22, 2024

Pages:

110

Publisher:

GIR

Countries:

Global [1]

USD 3,480.00

Software [2]

IT Services [3]

Computing & Electronics [4]

Description:

The global Automotive AI market size was valued at USD million in 2023 and is forecast to a readjusted size of USD million by 2030 with a CAGR of % during review period.
Automotive is a key driver of this industry. According to data from the World Automobile Organization (OICA), global automobile production and sales in 2017 reached their peak in the past 10 years, at 97.3 million and 95.89 million respectively. In 2018, the global economic expansion ended, and the global auto market declined as a whole. In 2022, there will wear units 81.6 million vehicles in the world. At present, more than 90% of the world's automobiles are concentrated in the three continents of Asia, Europe and North America, of which Asia automobile production accounts for 56% of the world, Europe accounts for 20%, and North America accounts for 16%. The world major automobile producing countries include China, the United States, Japan, South Korea, Germany, India, Mexico, and other countries; among them, China is the largest automobile producing country in the world, accounting for about 32%. Japan is the world's largest car exporter, exporting more than 3.5 million vehicles in 2022.
Thepublisher report includes an overview of the development of the Automotive AI industry chain, the market status of Passenger Cars (Automatic Drive, ADAS), Commercial Vehicles (Automatic Drive, ADAS), and key enterprises in developed and developing market, and analysed the cutting-edge technology, patent, hot applications and market trends of Automotive AI.
Regionally, the report analyzes the Automotive AI markets in key regions. North America and Europe are experiencing steady growth, driven by government initiatives and increasing consumer awareness. Asia-Pacific, particularly China, leads the global Automotive AI market, with robust domestic demand, supportive policies, and a strong manufacturing base.
Key Features:
The report presents comprehensive understanding of the Automotive AI market. It provides a holistic view of the industry, as well as detailed insights into individual components and stakeholders. The report analysis market dynamics, trends, challenges, and opportunities within the Automotive AI industry.
The report involves analyzing the market at a macro level:
麻豆原创 Sizing and Segmentation: Report collect data on the overall market size, including the revenue generated, and market share of different by Type (e.g., Automatic Drive, ADAS).
Industry Analysis: Report analyse the broader industry trends, such as government policies and regulations, technological advancements, consumer preferences, and market dynamics. This analysis helps in understanding the key drivers and challenges influencing the Automotive AI market.
Regional Analysis: The report involves examining the Automotive AI market at a regional or national level. Report analyses regional factors such as government incentives, infrastructure development, economic conditions, and consumer behaviour to identify variations and opportunities within different markets.
麻豆原创 Projections: Report covers the gathered data and analysis to make future projections and forecasts for the Automotive AI market. This may include estimating market growth rates, predicting market demand, and identifying emerging trends.
The report also involves a more granular approach to Automotive AI:
Company Analysis: Report covers individual Automotive AI players, suppliers, and other relevant industry players. This analysis includes studying their financial performance, market positioning, product portfolios, partnerships, and strategies.
Consumer Analysis: Report covers data on consumer behaviour, preferences, and attitudes towards Automotive AI This may involve surveys, interviews, and analysis of consumer reviews and feedback from different by Application (Passenger Cars, Commercial Vehicles).
Technology Analysis: Report covers specific technologies relevant to Automotive AI. It assesses the current state, advancements, and potential future developments in Automotive AI areas.
Competitive Landscape: By analyzing individual companies, suppliers, and consumers, the report present insights into the competitive landscape of the Automotive AI market. This analysis helps understand market share, competitive advantages, and potential areas for differentiation among industry players.
麻豆原创 Validation: The report involves validating findings and projections through primary research, such as surveys, interviews, and focus groups.
麻豆原创 Segmentation
Automotive AI market is split by Type and by Application. For the period 2019-2030, the growth among segments provides accurate calculations and forecasts for consumption value by Type, and by Application in terms of value.
麻豆原创 segment by Type
Automatic Drive
ADAS
麻豆原创 segment by Application
Passenger Cars
Commercial Vehicles
麻豆原创 segment by players, this report covers
Tesla Motors
Audi
Ford
Toyota
Google
Volvo
Nissan
Baidu
Apple
Daimler
Bosch
Microsoft
IBM
Intel
麻豆原创 segment by regions, regional analysis covers
North America (United States, Canada, and Mexico)
Europe (Germany, France, UK, Russia, Italy, and Rest of Europe)
Asia-Pacific (China, Japan, South Korea, India, Southeast Asia, Australia and Rest of Asia-Pacific)
South America (Brazil, Argentina and Rest of South America)
Middle East & Africa (Turkey, Saudi Arabia, UAE, Rest of Middle East & Africa)
The content of the study subjects, includes a total of 13 chapters:
Chapter 1, to describe Automotive AI product scope, market overview, market estimation caveats and base year.
Chapter 2, to profile the top players of Automotive AI, with revenue, gross margin and global market share of Automotive AI from 2019 to 2024.
Chapter 3, the Automotive AI competitive situation, revenue and global market share of top players are analyzed emphatically by landscape contrast.
Chapter 4 and 5, to segment the market size by Type and application, with consumption value and growth rate by Type, application, from 2019 to 2030.
Chapter 6, 7, 8, 9, and 10, to break the market size data at the country level, with revenue and market share for key countries in the world, from 2019 to 2024.and Automotive AI market forecast, by regions, type and application, with consumption value, from 2025 to 2030.
Chapter 11, market dynamics, drivers, restraints, trends and Porters Five Forces analysis.
Chapter 12, the key raw materials and key suppliers, and industry chain of Automotive AI.
Chapter 13, to describe Automotive AI research findings and conclusion.

Please Note - This is an on demand report and will be delivered in 2 business days (48 Hours) post payment.

Table Of Contents:

1 麻豆原创 Overview
1.1 Product Overview and Scope of Automotive AI
1.2 麻豆原创 Estimation Caveats and Base Year
1.3 Classification of Automotive AI by Type
1.3.1 Overview: Global Automotive AI 麻豆原创 Size by Type: 2019 Versus 2023 Versus 2030
1.3.2 Global Automotive AI Consumption Value 麻豆原创 Share by Type in 2023
1.3.3 Automatic Drive
1.3.4 ADAS
1.4 Global Automotive AI 麻豆原创 by Application
1.4.1 Overview: Global Automotive AI 麻豆原创 Size by Application: 2019 Versus 2023 Versus 2030
1.4.2 Passenger Cars
1.4.3 Commercial Vehicles
1.5 Global Automotive AI 麻豆原创 Size & Forecast
1.6 Global Automotive AI 麻豆原创 Size and Forecast by Region
1.6.1 Global Automotive AI 麻豆原创 Size by Region: 2019 VS 2023 VS 2030
1.6.2 Global Automotive AI 麻豆原创 Size by Region, (2019-2030)
1.6.3 North America Automotive AI 麻豆原创 Size and Prospect (2019-2030)
1.6.4 Europe Automotive AI 麻豆原创 Size and Prospect (2019-2030)
1.6.5 Asia-Pacific Automotive AI 麻豆原创 Size and Prospect (2019-2030)
1.6.6 South America Automotive AI 麻豆原创 Size and Prospect (2019-2030)
1.6.7 Middle East and Africa Automotive AI 麻豆原创 Size and Prospect (2019-2030)
2 Company Profiles
2.1 Tesla Motors
2.1.1 Tesla Motors Details
2.1.2 Tesla Motors Major Business
2.1.3 Tesla Motors Automotive AI Product and Solutions
2.1.4 Tesla Motors Automotive AI Revenue, Gross Margin and 麻豆原创 Share (2019-2024)
2.1.5 Tesla Motors Recent Developments and Future Plans
2.2 Audi
2.2.1 Audi Details
2.2.2 Audi Major Business
2.2.3 Audi Automotive AI Product and Solutions
2.2.4 Audi Automotive AI Revenue, Gross Margin and 麻豆原创 Share (2019-2024)
2.2.5 Audi Recent Developments and Future Plans
2.3 Ford
2.3.1 Ford Details
2.3.2 Ford Major Business
2.3.3 Ford Automotive AI Product and Solutions
2.3.4 Ford Automotive AI Revenue, Gross Margin and 麻豆原创 Share (2019-2024)
2.3.5 Ford Recent Developments and Future Plans
2.4 Toyota
2.4.1 Toyota Details
2.4.2 Toyota Major Business
2.4.3 Toyota Automotive AI Product and Solutions
2.4.4 Toyota Automotive AI Revenue, Gross Margin and 麻豆原创 Share (2019-2024)
2.4.5 Toyota Recent Developments and Future Plans
2.5 Google
2.5.1 Google Details
2.5.2 Google Major Business
2.5.3 Google Automotive AI Product and Solutions
2.5.4 Google Automotive AI Revenue, Gross Margin and 麻豆原创 Share (2019-2024)
2.5.5 Google Recent Developments and Future Plans
2.6 Volvo
2.6.1 Volvo Details
2.6.2 Volvo Major Business
2.6.3 Volvo Automotive AI Product and Solutions
2.6.4 Volvo Automotive AI Revenue, Gross Margin and 麻豆原创 Share (2019-2024)
2.6.5 Volvo Recent Developments and Future Plans
2.7 Nissan
2.7.1 Nissan Details
2.7.2 Nissan Major Business
2.7.3 Nissan Automotive AI Product and Solutions
2.7.4 Nissan Automotive AI Revenue, Gross Margin and 麻豆原创 Share (2019-2024)
2.7.5 Nissan Recent Developments and Future Plans
2.8 Baidu
2.8.1 Baidu Details
2.8.2 Baidu Major Business
2.8.3 Baidu Automotive AI Product and Solutions
2.8.4 Baidu Automotive AI Revenue, Gross Margin and 麻豆原创 Share (2019-2024)
2.8.5 Baidu Recent Developments and Future Plans
2.9 Apple
2.9.1 Apple Details
2.9.2 Apple Major Business
2.9.3 Apple Automotive AI Product and Solutions
2.9.4 Apple Automotive AI Revenue, Gross Margin and 麻豆原创 Share (2019-2024)
2.9.5 Apple Recent Developments and Future Plans
2.10 Daimler
2.10.1 Daimler Details
2.10.2 Daimler Major Business
2.10.3 Daimler Automotive AI Product and Solutions
2.10.4 Daimler Automotive AI Revenue, Gross Margin and 麻豆原创 Share (2019-2024)
2.10.5 Daimler Recent Developments and Future Plans
2.11 Bosch
2.11.1 Bosch Details
2.11.2 Bosch Major Business
2.11.3 Bosch Automotive AI Product and Solutions
2.11.4 Bosch Automotive AI Revenue, Gross Margin and 麻豆原创 Share (2019-2024)
2.11.5 Bosch Recent Developments and Future Plans
2.12 Microsoft
2.12.1 Microsoft Details
2.12.2 Microsoft Major Business
2.12.3 Microsoft Automotive AI Product and Solutions
2.12.4 Microsoft Automotive AI Revenue, Gross Margin and 麻豆原创 Share (2019-2024)
2.12.5 Microsoft Recent Developments and Future Plans
2.13 IBM
2.13.1 IBM Details
2.13.2 IBM Major Business
2.13.3 IBM Automotive AI Product and Solutions
2.13.4 IBM Automotive AI Revenue, Gross Margin and 麻豆原创 Share (2019-2024)
2.13.5 IBM Recent Developments and Future Plans
2.14 Intel
2.14.1 Intel Details
2.14.2 Intel Major Business
2.14.3 Intel Automotive AI Product and Solutions
2.14.4 Intel Automotive AI Revenue, Gross Margin and 麻豆原创 Share (2019-2024)
2.14.5 Intel Recent Developments and Future Plans
3 麻豆原创 Competition, by Players
3.1 Global Automotive AI Revenue and Share by Players (2019-2024)
3.2 麻豆原创 Share Analysis (2023)
3.2.1 麻豆原创 Share of Automotive AI by Company Revenue
3.2.2 Top 3 Automotive AI Players 麻豆原创 Share in 2023
3.2.3 Top 6 Automotive AI Players 麻豆原创 Share in 2023
3.3 Automotive AI 麻豆原创: Overall Company Footprint Analysis
3.3.1 Automotive AI 麻豆原创: Region Footprint
3.3.2 Automotive AI 麻豆原创: Company Product Type Footprint
3.3.3 Automotive AI 麻豆原创: Company Product Application Footprint
3.4 New 麻豆原创 Entrants and Barriers to 麻豆原创 Entry
3.5 Mergers, Acquisition, Agreements, and Collaborations
4 麻豆原创 Size Segment by Type
4.1 Global Automotive AI Consumption Value and 麻豆原创 Share by Type (2019-2024)
4.2 Global Automotive AI 麻豆原创 Forecast by Type (2025-2030)
5 麻豆原创 Size Segment by Application
5.1 Global Automotive AI Consumption Value 麻豆原创 Share by Application (2019-2024)
5.2 Global Automotive AI 麻豆原创 Forecast by Application (2025-2030)
6 North America
6.1 North America Automotive AI Consumption Value by Type (2019-2030)
6.2 North America Automotive AI Consumption Value by Application (2019-2030)
6.3 North America Automotive AI 麻豆原创 Size by Country
6.3.1 North America Automotive AI Consumption Value by Country (2019-2030)
6.3.2 United States Automotive AI 麻豆原创 Size and Forecast (2019-2030)
6.3.3 Canada Automotive AI 麻豆原创 Size and Forecast (2019-2030)
6.3.4 Mexico Automotive AI 麻豆原创 Size and Forecast (2019-2030)
7 Europe
7.1 Europe Automotive AI Consumption Value by Type (2019-2030)
7.2 Europe Automotive AI Consumption Value by Application (2019-2030)
7.3 Europe Automotive AI 麻豆原创 Size by Country
7.3.1 Europe Automotive AI Consumption Value by Country (2019-2030)
7.3.2 Germany Automotive AI 麻豆原创 Size and Forecast (2019-2030)
7.3.3 France Automotive AI 麻豆原创 Size and Forecast (2019-2030)
7.3.4 United Kingdom Automotive AI 麻豆原创 Size and Forecast (2019-2030)
7.3.5 Russia Automotive AI 麻豆原创 Size and Forecast (2019-2030)
7.3.6 Italy Automotive AI 麻豆原创 Size and Forecast (2019-2030)
8 Asia-Pacific
8.1 Asia-Pacific Automotive AI Consumption Value by Type (2019-2030)
8.2 Asia-Pacific Automotive AI Consumption Value by Application (2019-2030)
8.3 Asia-Pacific Automotive AI 麻豆原创 Size by Region
8.3.1 Asia-Pacific Automotive AI Consumption Value by Region (2019-2030)
8.3.2 China Automotive AI 麻豆原创 Size and Forecast (2019-2030)
8.3.3 Japan Automotive AI 麻豆原创 Size and Forecast (2019-2030)
8.3.4 South Korea Automotive AI 麻豆原创 Size and Forecast (2019-2030)
8.3.5 India Automotive AI 麻豆原创 Size and Forecast (2019-2030)
8.3.6 Southeast Asia Automotive AI 麻豆原创 Size and Forecast (2019-2030)
8.3.7 Australia Automotive AI 麻豆原创 Size and Forecast (2019-2030)
9 South America
9.1 South America Automotive AI Consumption Value by Type (2019-2030)
9.2 South America Automotive AI Consumption Value by Application (2019-2030)
9.3 South America Automotive AI 麻豆原创 Size by Country
9.3.1 South America Automotive AI Consumption Value by Country (2019-2030)
9.3.2 Brazil Automotive AI 麻豆原创 Size and Forecast (2019-2030)
9.3.3 Argentina Automotive AI 麻豆原创 Size and Forecast (2019-2030)
10 Middle East & Africa
10.1 Middle East & Africa Automotive AI Consumption Value by Type (2019-2030)
10.2 Middle East & Africa Automotive AI Consumption Value by Application (2019-2030)
10.3 Middle East & Africa Automotive AI 麻豆原创 Size by Country
10.3.1 Middle East & Africa Automotive AI Consumption Value by Country (2019-2030)
10.3.2 Turkey Automotive AI 麻豆原创 Size and Forecast (2019-2030)
10.3.3 Saudi Arabia Automotive AI 麻豆原创 Size and Forecast (2019-2030)
10.3.4 UAE Automotive AI 麻豆原创 Size and Forecast (2019-2030)
11 麻豆原创 Dynamics
11.1 Automotive AI 麻豆原创 Drivers
11.2 Automotive AI 麻豆原创 Restraints
11.3 Automotive AI Trends Analysis
11.4 Porters Five Forces Analysis
11.4.1 Threat of New Entrants
11.4.2 Bargaining Power of Suppliers
11.4.3 Bargaining Power of Buyers
11.4.4 Threat of Substitutes
11.4.5 Competitive Rivalry
12 Industry Chain Analysis
12.1 Automotive AI Industry Chain
12.2 Automotive AI Upstream Analysis
12.3 Automotive AI Midstream Analysis
12.4 Automotive AI Downstream Analysis
13 Research Findings and Conclusion
14 Appendix
14.1 Methodology
14.2 Research Process and Data Source
14.3 Disclaimer

Companies Mentioned:

Tesla Motors
Audi
Ford
Toyota
Google
Volvo
Nissan
Baidu
Apple
Daimler
Bosch
Microsoft
IBM
Intel

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