Report Content
Chapter 1 Methodology & Scope
1.1 Market Definitions
1.2 Base estimates & calculations
1.3 Forecast calculation
1.4 Data sources
1.4.1 Primary
1.4.2 Secondary
1.4.2.1 Paid sources
1.4.2.2 Public sources
Chapter 2 Executive Summary
2.1 AI in Automotive market 360º synopsis, 2018 – 2032
2.2 Business Trends
2.2.1 Total addressable market(TAM)
2.3 Regional trends
2.4 Component trends
2.5 Technology trends
2.6 Process trends
2.7 Application trends
Chapter 3 AI in Automotive Market Insights
3.1 Introduction
3.2 Impact of COVID-19 outbreak
3.2.1 North America
3.2.2 Europe
3.2.3 Asia Pacific
3.2.4 South America
3.2.5 MEA
3.3 Russia- Ukraine war impact on AI in Automotive market
3.4 Evolution of AI in Automotive
3.5 Industry ecosystem analysis
3.5.1 Hardware suppliers
3.5.2 Software providers
3.5.3 Third-party party service providers
3.5.4 Automotive manufacturers
3.5.5 Marketing & Distribution
3.5.6 Peripheral stakeholders
3.5.7 Profit margin
3.5.8 Vendor matrix
3.5.8.1 Hardware suppliers
3.5.8.2 Software providers
3.5.8.3 Third-party party service providers
3.5.8.4 Automotive manufacturers
3.5.8.5 Marketing & Distribution
3.5.8.6 Peripheral stakeholders
3.6 Technology & innovation landscape
3.6.1 Machine learning and neural networks
3.6.2 Multiple sensor fusion technologies
3.7 Patent analysis
3.8 Investment portfolio
3.9 Key initiatives and news
3.10 Regulatory landscape
3.10.1 North America
3.10.2 Europe
3.10.3 Asia Pacific
3.10.4 Latin America
3.10.5 MEA
3.11 Industry impact forces
3.11.1 Growth drivers
3.11.1.1 Growing adoption of AI in automotive value chain
3.11.1.2 Growing trend of Advance Driver Assist System (ADAS) level 2 technology
3.11.1.3 Growing AI implementation through ROI
3.11.1.4 Rising importance of ‘Car as a Platform’ business model
3.11.1.5 Rising demand for enhanced driver convenience
3.11.2 Industry pitfalls & challenges
3.11.2.1 Limitation of sensors and equipment
3.11.2.2 Issues related to hardware and software reliability
3.12 Growth potential analysis
3.13 Porter’s analysis
3.14 PESTEL analysis
Chapter 4 Competitive Landscape, 2022
4.1 Introduction
4.2 Company market share, 2022
4.3 Competitive analysis of major market players, 2022
4.3.1 Amazon Web Services (AWS)
4.3.2 Alphabet Inc
4.3.3 International Business Machines Corporation(IBM)
4.3.4 Tencent
4.3.5 Microsoft
4.3.6 NVIDIA Corporation
4.3.7 Baidu Core
4.3.8 SAP SE
4.3.9 Salesforce
4.4 Competitive analysis of innovative market players, 2022
4.4.1 Argo AI
4.4.2 Cruise Automation
4.4.3 Appen
4.4.4 Interactions LLC
4.4.5 Lexalytics
4.4.6 Waymo
4.4.7 Nuro
4.5 Competitive positioning matrix
4.6 Stratgic outlook matrix
Chapter 5 AI in Automotive Market, By Component
5.1 Key trends, by component
5.2 Hardware
5.2.1 Market estimates and forecast, 2018 – 2032
5.3 Software
5.3.1 Market estimates and forecast, 2018 – 2032
5.4 Services
5.4.1 Market estimates and forecast, 2018 – 2032
Chapter 6 AI in Automotive Market, By Technology
6.1 Key trends, by Technology
6.2 Computer Vision
6.2.1 Market estimates and forecast, 2018 – 2032
6.3 Context Awareness
6.3.1 Market estimates and forecast, 2018 – 2032
6.4 Deep Learning
6.4.1 Market estimates and forecast, 2018 – 2032
6.5 Machine Learning
6.5.1 Market estimates and forecast, 2018 – 2032
6.6 Natural Language Processing
6.6.1 Market estimates and forecast, 2018 – 2032
Chapter 7 AI in Automotive Market, By Process
7.1 Key trends, by process
7.2 Data mining
7.2.1 Market estimates and forecast, 2018 – 2032
7.3 Image/signal Recognition
7.3.1 Market estimates and forecast, 2018 – 2032
Chapter 8 AI in Automotive Market, By Application
8.1 Key trends, by application
8.2 Semi-Autonomous Vehicle
8.2.1 Market estimates and forecast, 2018 – 2032
8.3 Fully Autonomous Vehicle
8.3.1 Market estimates and forecast, 2018 – 2032
Chapter 9 AI in Automotive Market, By Region
9.1 Key trends, by region
9.2 North America
9.2.1 Market estimates and forecast, by component, 2018 – 2032
9.2.2 Market estimates and forecast, by technology, 2018 – 2032
9.2.3 Market estimates and forecast, by process, 2018-2032
9.2.4 Market estimates and forecast, by application, 2018 – 2032
9.2.5 U.S.
9.2.5.1 Market estimates and forecast, by component, 2018 – 2032
9.2.5.2 Market estimates and forecast, by technology, 2018 – 2032
9.2.5.3 Market estimates and forecast, by process, 2018-2032
9.2.5.4 Market estimates and forecast, by application 2018 – 2032
9.2.6 Canada
9.2.6.1 Market estimates and forecast, by component, 2018 – 2032
9.2.6.2 Market estimates and forecast, by technology, 2018 – 2032
9.2.6.3 Market estimates and forecast, by process, 2018-2032
9.2.6.4 Market estimates and forecast, by application 2018 – 2032
9.2.7 Mexico
9.2.7.1 Market estimates and forecast, by component, 2018 – 2032
9.2.7.2 Market estimates and forecast, by technology, 2018 – 2032
9.2.7.3 Market estimates and forecast, by process, 2018-2032
9.2.7.4 Market estimates and forecast, by application 2018 – 2032
9.3 Europe
9.3.1 Market estimates and forecast, by component, 2018 – 2032
9.3.2 Market estimates and forecast, by technology, 2018 – 2032
9.3.3 Market estimates and forecast, by process, 2018-2032
9.3.4 Market estimates and forecast, by application, 2018 – 2032
9.3.5 UK
9.3.5.1 Market estimates and forecast, by component, 2018 – 2032
9.3.5.2 Market estimates and forecast, by technology, 2018 – 2032
9.3.5.3 Market estimates and forecast, by process, 2018-2032
9.3.5.4 Market estimates and forecast, by application 2018 – 2032
9.3.6 Germany
9.3.6.1 Market estimates and forecast, by component, 2018 – 2032
9.3.6.2 Market estimates and forecast, by technology, 2018 – 2032
9.3.6.3 Market estimates and forecast, by process, 2018-2032
9.3.6.4 Market estimates and forecast, by application 2018 – 2032
9.3.7 France
9.3.7.1 Market estimates and forecast, by component, 2018 – 2032
9.3.7.2 Market estimates and forecast, by technology, 2018 – 2032
9.3.7.3 Market estimates and forecast, by process, 2018-2032
9.3.7.4 Market estimates and forecast, by application 2018 – 2032
9.3.8 Italy
9.3.8.1 Market estimates and forecast, by component, 2018 – 2032
9.3.8.2 Market estimates and forecast, by technology, 2018 – 2032
9.3.8.3 Market estimates and forecast, by process, 2018-2032
9.3.8.4 Market estimates and forecast, by application 2018 – 2032
9.3.9 Spain
9.3.9.1 Market estimates and forecast, by component, 2018 – 2032
9.3.9.2 Market estimates and forecast, by technology, 2018 – 2032
9.3.9.3 Market estimates and forecast, by process, 2018-2032
9.3.9.4 Market estimates and forecast, by application 2018 – 2032
9.3.10 Russia
9.3.10.1 Market estimates and forecast, by component, 2018 – 2032
9.3.10.2 Market estimates and forecast, by technology, 2018 – 2032
9.3.10.3 Market estimates and forecast, by process, 2018-2032
9.3.10.4 Market estimates and forecast, by application 2018 – 2032
9.4 Asia Pacific
9.4.1 Market estimates and forecast, by component, 2018 – 2032
9.4.2 Market estimates and forecast, by technology, 2018 – 2032
9.4.3 Market estimates and forecast, by process, 2018-2032
9.4.4 Market estimates and forecast, by application, 2018 – 2032
9.4.5 China
9.4.5.1 Market estimates and forecast, by component, 2018 – 2032
9.4.5.2 Market estimates and forecast, by technology, 2018 – 2032
9.4.5.3 Market estimates and forecast, by process, 2018-2032
9.4.5.4 Market estimates and forecast, by application 2018 – 2032
9.4.6 India
9.4.6.1 Market estimates and forecast, by component, 2018 – 2032
9.4.6.2 Market estimates and forecast, by technology, 2018 – 2032
9.4.6.3 Market estimates and forecast, by process, 2018-2032
9.4.6.4 Market estimates and forecast, by application 2018 – 2032
9.4.7 Japan
9.4.7.1 Market estimates and forecast, by component, 2018 – 2032
9.4.7.2 Market estimates and forecast, by technology, 2018 – 2032
9.4.7.3 Market estimates and forecast, by process, 2018-2032
9.4.7.4 Market estimates and forecast, by application 2018 – 2032
9.4.8 Australia
9.4.8.1 Market estimates and forecast, by component, 2018 – 2032
9.4.8.2 Market estimates and forecast, by technology, 2018 – 2032
9.4.8.3 Market estimates and forecast, by process, 2018-2032
9.4.8.4 Market estimates and forecast, by application 2018 – 2032
9.4.9 South Korea
9.4.9.1 Market estimates and forecast, by component, 2018 – 2032
9.4.9.2 Market estimates and forecast, by technology, 2018 – 2032
9.4.9.3 Market estimates and forecast, by process, 2018-2032
9.4.9.4 Market estimates and forecast, by application 2018 – 2032
9.5 LAMEA
9.5.1 Market estimates and forecast, by component, 2018 – 2032
9.5.2 Market estimates and forecast, by technology, 2018 – 2032
9.5.3 Market estimates and forecast, by process, 2018-2032
9.5.4 Market estimates and forecast, by application, 2018 – 2032
9.5.5 Brazil
9.5.5.1 Market estimates and forecast, by component, 2018 – 2032
9.5.5.2 Market estimates and forecast, by technology, 2018 – 2032
9.5.5.3 Market estimates and forecast, by process, 2018-2032
9.5.5.4 Market estimates and forecast, by application 2018 – 2032
9.5.6 Mexico
9.5.6.1 Market estimates and forecast, by component, 2018 – 2032
9.5.6.2 Market estimates and forecast, by technology, 2018 – 2032
9.5.6.3 Market estimates and forecast, by process, 2018-2032
9.5.6.4 Market estimates and forecast, by application 2018 – 2032
9.5.7 Saudi Arabia
9.5.7.1 Market estimates and forecast, by component, 2018 – 2032
9.5.7.2 Market estimates and forecast, by technology, 2018 – 2032
9.5.7.3 Market estimates and forecast, by process, 2018-2032
9.5.7.4 Market estimates and forecast, by application 2018 – 2032
9.5.8 UAE
9.5.8.1 Market estimates and forecast, by component, 2018 – 2032
9.5.8.2 Market estimates and forecast, by technology, 2018 – 2032
9.5.8.3 Market estimates and forecast, by process, 2018-2032
9.5.8.4 Market estimates and forecast, by application 2018 – 2032
9.5.9 South Africa
9.5.9.1 Market estimates and forecast, by component, 2018 – 2032
9.5.9.2 Market estimates and forecast, by technology, 2018 – 2032
9.5.9.3 Market estimates and forecast, by application 2018 – 2032
Chapter 10 Company Profiles
10.1 Amazon Web Services (AWS)
10.1.1 Business Overview
10.1.2 Financial Data
10.1.3 Product Landscape
10.1.4 Strategic Outlook
10.1.5 SWOT Analysis
10.2 Alphabet Inc
10.2.1 Business Overview
10.2.2 Financial Data
10.2.3 Product Landscape
10.2.4 Strategic Outlook
10.2.5 SWOT Analysis
10.3 IBM Corporation
10.3.1 Business Overview
10.3.2 Financial Data
10.3.3 Product Landscape
10.3.4 Strategic Outlook
10.3.5 SWOT Analysis
10.4 NVIDIA Corporation
10.4.1 Business Overview
10.4.2 Financial Data
10.4.3 Product Landscape
10.4.4 Strategic Outlook
10.4.5 SWOT Analysis
10.5 Tencent
10.5.1 Business Overview
10.5.2 Financial Data
10.5.3 Product Landscape
10.5.4 Strategic Outlook
10.5.5 SWOT Analysis
10.6 Microsoft
10.6.1 Business Overview
10.6.2 Financial Data
10.6.3 Product Landscape
10.6.4 Strategic Outlook
10.6.5 SWOT Analysis
10.7 Audi AG
10.7.1 Business Overview
10.7.2 Financial Data
10.7.3 Product Landscape
10.7.4 Strategic Outlook
10.7.5 SWOT Analysis
10.8 BMW AG
10.8.1 Business Overview
10.8.2 Financial Data
10.8.3 Product Landscape
10.8.4 Strategic Outlook
10.8.5 SWOT Analysis
10.9 Daimler AG
10.9.1 Business Overview
10.9.2 Financial Data
10.9.3 Product Landscape
10.9.4 Strategic Outlook
10.9.5 SWOT Analysis
10.10 Didi Chuxing
10.10.1 Business Overview
10.10.2 Financial Data
10.10.3 Product Landscape
10.10.4 Strategic Outlook
10.10.5 SWOT Analysis
10.11 Ford Motor Company
10.11.1 Business Overview
10.11.2 Financial Data
10.11.3 Product Landscape
10.11.4 Strategic Outlook
10.11.5 SWOT Analysis
10.12 General Motors Company
10.12.1 Business Overview
10.12.2 Financial Data
10.12.3 Product Landscape
10.12.4 Strategic Outlook
10.12.5 SWOT Analysis
10.13 Harman International Industries, Inc
10.13.1 Business Overview
10.13.2 Financial Data
10.13.3 Product Landscape
10.13.4 Strategic Outlook
10.13.5 SWOT Analysis
10.14 Honda Motors
10.14.1 Business Overview
10.14.2 Financial Data
10.14.3 Product Landscape
10.14.4 Strategic Outlook
10.14.5 SWOT Analysis
10.15 Intel Corporation
10.15.1 Business Overview
10.15.2 Financial Data
10.15.3 Product Landscape
10.15.4 Strategic Outlook
10.15.5 SWOT Analysis
10.16 Qualcomm Inc
10.16.1 Business Overview
10.16.2 Financial Data
10.16.3 Product Landscape
10.16.4 Strategic Outlook
10.16.5 SWOT Analysis
10.17 Tesla Inc
10.17.1 Business Overview
10.17.2 Financial Data
10.17.3 Product Landscape
10.17.4 Strategic Outlook
10.17.5 SWOT Analysis
10.18 Uber Technologies, Inc.
10.18.1 Business Overview
10.18.2 Financial Data
10.18.3 Product Landscape
10.18.4 Strategic Outlook
10.18.5 SWOT Analysis
10.19 Volvo Car Coroporation
10.19.1 Business Overview
10.19.2 Financial Data
10.19.3 Product Landscape
10.19.4 Strategic Outlook
10.19.5 SWOT Analysis
10.20 Xilinx Inc.
10.20.1 Business Overview
10.20.2 Financial Data
10.20.3 Product Landscape
10.20.4 Strategic Outlook
10.20.5 SWOT Analysis
