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市场调查报告书
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1519831

2024-2032 年按组件、技术、製程、应用和地区分類的汽车人工智慧市场报告

Automotive Artificial Intelligence Market Report by Component, Technology, Process, Application, and Region 2024-2032
出版日期: | 出版商: IMARC | 英文 149 Pages | 商品交期: 2-3个工作天内

价格

IMARC Group年全球汽车人工智慧市场规模达39亿美元。消费者对先进功能的需求不断增长、各种政府法规的实施、重大技术进步、感测器技术成本的快速降低、交通管理中对人工智慧(AI) 的需求不断增长以及对永续性的日益重视是推动这一趋势的一些主要因素。

汽车人工智慧（AI）是指将技术整合到车辆中，以增强其功能、安全性和用户体验。它包括各种系统，例如驾驶员辅助、车内虚拟助理、预测性维护和完全自主系统。汽车人工智慧广泛应用于自适应巡航控制、防撞、驾驶员监控、声控控制、交通标誌识别、自动停车和即时交通监控等领域。它有助于增强安全性、提高效率、降低排放水平、节省时间、增加交通流量、改善用户体验并促进永续发展。

感测器技术和运算能力的成本迅速下降，使得人工智慧的实施对于汽车製造商来说在经济上更加可行，对市场成长产生了积极的影响。除此之外，由于城市化进程不断加快以及随之而来的交通拥堵，对交通管理和路线优化方面人工智慧的需求不断增长，也推动了市场的成长。此外，汽车製造商越来越多地利用人工智慧来实现卓越的预测性维护、即时决策和个人化用户体验，这也支持了市场的成长。此外，物联网 (IoT) 和车联网 (V2X) 通讯的最新进展为人工智慧整合提供了新途径，例如先进的远端资讯处理和远端车辆控制，正在推动市场成长。此外，对永续性的日益重视正在促进对人工智慧优化燃油效率和管理替代燃料系统的需求。

汽车人工智慧市场趋势/驱动因素：

对高阶功能不断增长的需求

消费者对先进功能的需求不断增长是推动汽车人工智慧（AI）市场成长的一个突出因素。使用者越来越精通技术，这导致对车辆先进功能的期望越来越高，例如自适应巡航控制、自动停车和先进的导航系统。此外，对便利性的追求，尤其是在日常生活中深入接触科技的年轻人群中，正在推动市场的成长。除此之外，城市中心日益严重的拥塞正在促进对具有智慧功能以管理城市驾驶复杂性的车辆的需求。消费者期望的这种转变给製造商带来了巨大的压力，要求他们在汽车设计中采用人工智慧技术，不仅将其作为增值，而且将其作为直接影响购买决策的核心组件。

实施各种政府法规

政府法规在推动人工智慧融入汽车产业方面发挥着越来越重要的作用。道路安全正成为全球最重要的议题，促使当局对车辆实施更严格的安全准则和要求。这些指南通常要求纳入先进的安全功能，例如防撞系统、车道偏离警告和紧急煞车系统，这些功能严重依赖人工智慧技术。此外，监管架构不仅在国家层级制定，而且在各地区之间也日益协调，以在全球范围内推广更高的安全标准。此外，该立法具有双重目的，因为它有助于改善道路安全，并充当汽车行业技术创新的催化剂。除此之外，法规也有效地充当了迫使汽车製造商专注于人工智慧技术研发的外力。

重大技术进步

快速的技术进步对于推动汽车人工智慧市场至关重要。与此一致的是，机器学习（ML）演算法的进步使车辆能够做出即时决策，从而大幅提高其自主能力。此外，由于先进的感测器技术具有更高的准确性和耐用性，在物体识别和距离测量应用中的结合正在对市场成长产生积极影响。此外，利用资料分析即时处理和解释大资料集，以进行预测性维护、路线优化，甚至提高骑士舒适度，也有助于市场成长。除此之外，技术进步还降低了成本，使得将先进的人工智慧功能整合到更广泛的车辆中更加经济可行。

目录

第一章：前言

第 2 章：范围与方法

  • 研究目的
  • 利害关係人
  • 资料来源
    • 主要资源
    • 二手资料
  • 市场预测
    • 自下而上的方法
    • 自上而下的方法
  • 预测方法

第 3 章：执行摘要

第 4 章：简介

  • 概述
  • 主要行业趋势

第 5 章：全球汽车人工智慧市场

  • 市场概况
  • 市场业绩
  • COVID-19 的影响
  • 市场预测

第 6 章：市场区隔：按组成部分

  • 硬体
    • 市场走向
    • 市场预测
  • 软体
    • 市场走向
    • 市场预测
  • 服务
    • 市场走向
    • 市场预测

第 7 章：市场区隔：依技术

  • 机器学习和深度学习
    • 市场走向
    • 市场预测
  • 电脑视觉
    • 市场走向
    • 市场预测
  • 自然语言处理
    • 市场走向
    • 市场预测

第 8 章：市场区隔：依流程

  • 资料探勘
    • 市场走向
    • 市场预测
  • 影像辨识
    • 市场走向
    • 市场预测
  • 讯号识别
    • 市场走向
    • 市场预测

第 9 章：市场区隔：按应用

  • 半自主
    • 市场走向
    • 市场预测
  • 自主性
    • 市场走向
    • 市场预测

第 10 章：市场区隔：按地区

  • 北美洲
    • 美国
    • 加拿大
  • 亚太
    • 中国
    • 日本
    • 印度
    • 韩国
    • 澳洲
    • 印尼
    • 其他的
  • 欧洲
    • 德国
    • 法国
    • 英国
    • 义大利
    • 西班牙
    • 俄罗斯
    • 其他的
  • 拉丁美洲
    • 巴西
    • 墨西哥
    • 其他的
  • 中东和非洲
    • 市场走向
    • 市场细分：按国家/地区
    • 市场预测

第 11 章：SWOT 分析

  • 概述
  • 优势
  • 弱点
  • 机会
  • 威胁

第 12 章：价值链分析

第 13 章：波特五力分析

  • 概述
  • 买家的议价能力
  • 供应商的议价能力
  • 竞争程度
  • 新进入者的威胁
  • 替代品的威胁

第 14 章：价格分析

第15章：竞争格局

  • 市场结构
  • 关键参与者
  • 关键参与者简介
    • Bayerische Motoren Werke AG
    • Daimler AG
    • Ford Motor Company
    • Hyundai Motor Company
    • Intel Corporation
    • International Business Machines Corporation
    • Micron Technology Inc.
    • Microsoft Corporation
    • NVIDIA Corporation
    • Qualcomm Incorporated
    • Tesla Inc.
    • Toyota Motor Corporation
    • Uber Technologies Inc.
Product Code: SR112024A5824

The global automotive artificial intelligence market size reached US$ 3.9 Billion in 2023. Looking forward, IMARC Group expects the market to reach US$ 33.9 Billion by 2032, exhibiting a growth rate (CAGR) of 26.6% during 2024-2032. The escalating consumer demand for advanced features, imposition of various government regulations, significant technological advancements, rapid cost reduction in sensor technology, growing demand for artificial intelligence (AI) in traffic management, and increasing emphasis on sustainability are some of the major factors propelling the market.

Automotive artificial intelligence (AI) refers to the integration of technology within vehicles to enhance their functionalities, safety, and user experience. It comprises various systems, such as driver assistance, in-car virtual assistants, predictive maintenance, and fully autonomous systems. Automotive AI is widely used in adaptive cruise control, collision avoidance, driver monitoring, voice-activated controls, traffic sign recognition, automated parking, and real-time traffic monitoring. It aids in enhancing safety, increasing efficiency, reducing emission levels, saving time, augmenting traffic flow, improving user experience, and promoting sustainability.

The rapid cost reduction in sensor technology and computing power, which is making AI implementation more financially viable for automotive manufacturers, is positively influencing the market growth. Besides this, the growing demand for AI in traffic management and route optimization owing to the increasing urbanization and subsequent traffic congestion are contributing to the market growth. Furthermore, the rising utilization of AI by automotive manufacturers to enable superior predictive maintenance, real-time decision-making, and personalized user experiences is supporting the market growth. In addition, the recent advancements in the Internet of Things (IoT) and vehicle-to-everything (V2X) communication that are offering new avenues for AI integration, such as advanced telematics and remote vehicle control, are fueling the market growth. Moreover, the increasing emphasis on sustainability is facilitating the demand for AI to optimize fuel efficiency and manage alternative fuel systems.

Automotive Artificial Intelligence Market Trends/Drivers:

The escalating demand for advanced features

The increasing consumer demand for advanced features is a prominent factor propelling the growth of the automotive artificial intelligence (AI) market. Users are becoming increasingly tech-savvy, leading to higher expectations for advanced features in vehicles, such as adaptive cruise control, automated parking, and advanced navigation systems. Furthermore, the push for convenience, especially among younger demographics who are deeply engaged with technology in their daily lives, is fueling the market growth. Apart from this, the growing congestion in urban centers is facilitating the demand for vehicles that offer intelligent features to manage the complexities of city driving. This shift in consumer expectations puts considerable pressure on manufacturers to adopt AI technologies in automotive design, not merely as a value-add but as a core component that directly influences purchasing decisions.

The imposition of various government regulations

Government regulations are playing an increasingly critical role in driving the incorporation of AI in the automotive sector. Road safety is becoming a paramount concern across the globe, prompting authorities to impose stricter safety guidelines and requirements for vehicles. These guidelines often mandate the incorporation of advanced safety features, such as collision avoidance systems, lane-departure warnings, and emergency braking systems, which rely heavily on AI technologies. Furthermore, regulatory frameworks are not just being developed at a national level but are also increasingly harmonized across regions to promote higher safety standards globally. Moreover, the legislation serves dual purposes, as it aids in improving road safety and acts as a catalyst for technological innovation within the automotive industry. Besides this, the regulations effectively act as an external force that compels automakers to focus on research and development (R&D) in AI technologies.

The significant technological advancements

Rapid technological advancements are pivotal in propelling the automotive AI market. In line with this, the progress in machine learning (ML) algorithms has enabled vehicles to make real-time decisions, thereby drastically improving their autonomous capabilities. Furthermore, the incorporation of advanced sensor technologies in object recognition and distance measurement applications, owing to their higher accuracy and durability, is positively influencing the market growth. Moreover, the utilization of data analytics to process and interpret large data sets in real-time for predictive maintenance, route optimization, and even rider comfort is contributing to the market growth. Besides this, technological advancements have resulted in cost reduction, making it more economically viable to integrate advanced AI features into a broader range of vehicles.

Automotive Artificial Intelligence Industry Segmentation:

IMARC Group provides an analysis of the key trends in each segment of the global automotive artificial intelligence market report, along with forecasts at the global, regional and country levels from 2024-2032. Our report has categorized the market based on component, technology, process, and application.

Breakup by Component:

Hardware

Software

Services

Hardware dominates the market

The report has provided a detailed breakup and analysis of the market based on component. This includes hardware, software, and services. According to the report, hardware represented the largest segment.

Hardware is dominating the market as the foundational capabilities for AI in vehicles stem from advanced hardware components, such as sensors, cameras, light detection and ranging (LiDAR), and central processing units (CPUs). These elements are essential for the collection and initial processing of real-time data, which is then used by AI algorithms for decision-making. Furthermore, the ever-increasing complexity and capabilities of AI algorithms, which require more robust and specialized hardware for optimal performance, are positively influencing the market growth. Additionally, the hardware serves as the backbone that enables the functionalities of various AI-based technologies, such as machine vision, spatial awareness, and real-time analytics. Moreover, compared to software, which can often be updated remotely to add new features, hardware requires a physical change in the component, making it a more stable but also critical investment.

Breakup by Technology:

Machine Learning and Deep Learning

Computer Vision

Natural Language Processing

A detailed breakup and analysis of the market based on the technology has also been provided in the report. This includes machine learning and deep learning, computer vision, and natural language processing.

Machine learning (ML) and deep learning are dominating the market due to their capability to facilitate real-time decision-making and predictive analysis, which are essential in modern vehicular applications. Furthermore, they can process vast quantities of data and learn from it, enabling features, such as adaptive cruise control, collision avoidance, and predictive maintenance. In addition, they can operate in sync with sensor technologies, such as LiDAR, radio detecting and ranging (RADAR), and cameras, thereby providing a comprehensive and integrated approach to vehicle automation.

Computer vision is witnessing significant growth due to its indispensable role in enabling real-time perception and decision-making capabilities, which is essential for various critical applications in automotive AI, including object detection, lane departure warning, and collision avoidance systems. Furthermore, the escalating adoption of computer vision to meet regulatory requirements regarding the safety of vehicles and pedestrians is favoring the market growth. Additionally, computer vision offers seamless integration with sensor fusion technologies, which combine data from different sensors like radars and LiDAR, to offer a more comprehensive understanding of the vehicle's surroundings.

Breakup by Process:

Data Mining

Image Recognition

Signal Recognition

Data mining hold the largest share in the market

A detailed breakup and analysis of the market based on the process has also been provided in the report. This includes data mining, image recognition, and signal recognition. According to the report, data mining accounted for the largest market share.

Data mining is dominating the market due to its critical role in extracting valuable insights from vast amounts of data generated by modern vehicles. These insights serve as the foundation for many AI-based features, such as predictive maintenance and real-time decision-making. Furthermore, data mining techniques help to identify vehicle performance data, driver behavior, environmental conditions, and patterns and correlations that can be translated into actionable insights or improvements in AI algorithms. Besides this, it can analyze both structured and unstructured data, offering a comprehensive understanding of vehicle operations and user experiences. Moreover, data mining enables predictive analytics, which is one of the most promising applications in automotive AI. In addition, it is also essential for optimizing routing algorithms, improving fuel efficiency, and minimizing emissions, which are key objectives for modern vehicles.

Breakup by Application:

Semi-Autonomous

Autonomous

Semi-autonomous hold the largest share in the market

A detailed breakup and analysis of the market based on the application has also been provided in the report. This includes semi-autonomous and autonomous. According to the report, semi-autonomous accounted for the largest market share.

The semi-autonomous is dominating the market as it offers enhanced safety features, such as lane departure warnings, adaptive cruise control, and emergency braking, that are easier to integrate into vehicles and have gained regulatory approval in many jurisdictions. Furthermore, several consumers are still skeptical about relinquishing full control to a machine. In line with this, semi-autonomous features allow drivers to experience the benefits of AI while retaining control over the vehicle. Moreover, semi-autonomous features can be integrated into vehicles at a fraction of the cost, making them more economically viable for both manufacturers and consumers. Additionally, the rapid rate of technological advancements in AI and machine learning (ML) algorithms, which allow for continuous upgrades in semi-autonomous systems, is supporting the market growth.

Breakup by Region:

North America

United States

Canada

Asia-Pacific

China

Japan

India

South Korea

Australia

Indonesia

Others

Europe

Germany

France

United Kingdom

Italy

Spain

Russia

Others

Latin America

Brazil

Mexico

Others

Middle East and Africa

North America exhibits a clear dominance, accounting for the largest automotive artificial intelligence market share

The market research report has also provided a comprehensive analysis of all the major regional markets, which include North America (the United States and Canada); Asia Pacific (China, Japan, India, South Korea, Australia, Indonesia, and others); Europe (Germany, France, the United Kingdom, Italy, Spain, Russia, and others); Latin America (Brazil, Mexico, and others); and the Middle East and Africa. According to the report, North America accounted for the largest market share.

North America hosts a large number of technology companies that are at the forefront of AI and automotive innovation. In addition, regional consumers are known for their early adoption of new technologies due to high average income levels. Furthermore, the imposition of various regulations by the regional governments that are conducive to the development and integration of AI technologies in the automotive sector is positively influencing the market growth. Besides this, the region is witnessing high levels of investment in research and innovation activities from government bodies and private organizations to accelerate the pace of innovation and implementation of AI features in vehicles. Moreover, the presence of world-class universities and research institutions in North America, which contributes to a highly skilled workforce that is adept at advanced technologies, including AI, is boosting the market growth.

Competitive Landscape:

Leading companies are developing more sophisticated AI algorithms to enhance autonomous driving capabilities and optimize vehicle operations. Furthermore, they are collaborating with other industry stakeholders to bring together expertise in hardware and software, creating synergies that drive the rapid development of automotive AI technologies. Besides this, top players are extensively utilizing data analytics to improve their products and refine their AI algorithms. Moreover, key players are engaging with consumers to understand what features are most desired and aim to incorporate these in their offerings. They are also adapting their technologies for different markets and driving conditions around the world, which assists them in addressing a broad spectrum of consumer needs and regulatory requirements. Moreover, companies are aligning their AI technologies with sustainability goals, developing solutions that contribute to fuel efficiency and reduced carbon emissions.

The report has provided a comprehensive analysis of the competitive landscape in the market. Detailed profiles of all major companies have also been provided. Some of the key players in the market include:

Bayerische Motoren Werke AG

Daimler AG

Ford Motor Company

Hyundai Motor Company

Intel Corporation

International Business Machines Corporation

Micron Technology Inc.

Microsoft Corporation

NVIDIA Corporation

Qualcomm Incorporated

Tesla Inc.

Toyota Motor Corporation

Uber Technologies Inc.

Recent Developments:

In March 2023, Daimler AG announced that it had signed an agreement to acquire Algolux, an AI company known for its expertise in machine learning (ML) and computer vision.

In March 2023, Ford Motor Company established Latitude AI, a subsidiary, to develop new automated driving technologies.

In August 2023, Hyundai Motor Company and Kia announced an investment of US$ 50 million in a Canadian AI semiconductor company to integrate AI into their future vehicle models.

Key Questions Answered in This Report

  • 1. How big is the global automotive artificial intelligence market?
  • 2. What is the expected growth rate of the global automotive artificial intelligence market during 2024-2032?
  • 3. What are the key factors driving the global automotive artificial intelligence market?
  • 4. What has been the impact of COVID-19 on the global automotive artificial intelligence market?
  • 5. What is the breakup of the global automotive artificial intelligence market based on the component?
  • 6. What is the breakup of the global automotive artificial intelligence market based on the process?
  • 7. What is the breakup of the global automotive artificial intelligence market based on the application?
  • 8. What are the key regions in the global automotive artificial intelligence market?
  • 9. Who are the key players/companies in the global automotive artificial intelligence market?

Table of Contents

1 Preface

2 Scope and Methodology

  • 2.1 Objectives of the Study
  • 2.2 Stakeholders
  • 2.3 Data Sources
    • 2.3.1 Primary Sources
    • 2.3.2 Secondary Sources
  • 2.4 Market Estimation
    • 2.4.1 Bottom-Up Approach
    • 2.4.2 Top-Down Approach
  • 2.5 Forecasting Methodology

3 Executive Summary

4 Introduction

  • 4.1 Overview
  • 4.2 Key Industry Trends

5 Global Automotive Artificial Intelligence Market

  • 5.1 Market Overview
  • 5.2 Market Performance
  • 5.3 Impact of COVID-19
  • 5.4 Market Forecast

6 Market Breakup by Component

  • 6.1 Hardware
    • 6.1.1 Market Trends
    • 6.1.2 Market Forecast
  • 6.2 Software
    • 6.2.1 Market Trends
    • 6.2.2 Market Forecast
  • 6.3 Services
    • 6.3.1 Market Trends
    • 6.3.2 Market Forecast

7 Market Breakup by Technology

  • 7.1 Machine Learning and Deep Learning
    • 7.1.1 Market Trends
    • 7.1.2 Market Forecast
  • 7.2 Computer Vision
    • 7.2.1 Market Trends
    • 7.2.2 Market Forecast
  • 7.3 Natural Language Processing
    • 7.3.1 Market Trends
    • 7.3.2 Market Forecast

8 Market Breakup by Process

  • 8.1 Data Mining
    • 8.1.1 Market Trends
    • 8.1.2 Market Forecast
  • 8.2 Image Recognition
    • 8.2.1 Market Trends
    • 8.2.2 Market Forecast
  • 8.3 Signal Recognition
    • 8.3.1 Market Trends
    • 8.3.2 Market Forecast

9 Market Breakup by Application

  • 9.1 Semi-Autonomous
    • 9.1.1 Market Trends
    • 9.1.2 Market Forecast
  • 9.2 Autonomous
    • 9.2.1 Market Trends
    • 9.2.2 Market Forecast

10 Market Breakup by Region

  • 10.1 North America
    • 10.1.1 United States
      • 10.1.1.1 Market Trends
      • 10.1.1.2 Market Forecast
    • 10.1.2 Canada
      • 10.1.2.1 Market Trends
      • 10.1.2.2 Market Forecast
  • 10.2 Asia-Pacific
    • 10.2.1 China
      • 10.2.1.1 Market Trends
      • 10.2.1.2 Market Forecast
    • 10.2.2 Japan
      • 10.2.2.1 Market Trends
      • 10.2.2.2 Market Forecast
    • 10.2.3 India
      • 10.2.3.1 Market Trends
      • 10.2.3.2 Market Forecast
    • 10.2.4 South Korea
      • 10.2.4.1 Market Trends
      • 10.2.4.2 Market Forecast
    • 10.2.5 Australia
      • 10.2.5.1 Market Trends
      • 10.2.5.2 Market Forecast
    • 10.2.6 Indonesia
      • 10.2.6.1 Market Trends
      • 10.2.6.2 Market Forecast
    • 10.2.7 Others
      • 10.2.7.1 Market Trends
      • 10.2.7.2 Market Forecast
  • 10.3 Europe
    • 10.3.1 Germany
      • 10.3.1.1 Market Trends
      • 10.3.1.2 Market Forecast
    • 10.3.2 France
      • 10.3.2.1 Market Trends
      • 10.3.2.2 Market Forecast
    • 10.3.3 United Kingdom
      • 10.3.3.1 Market Trends
      • 10.3.3.2 Market Forecast
    • 10.3.4 Italy
      • 10.3.4.1 Market Trends
      • 10.3.4.2 Market Forecast
    • 10.3.5 Spain
      • 10.3.5.1 Market Trends
      • 10.3.5.2 Market Forecast
    • 10.3.6 Russia
      • 10.3.6.1 Market Trends
      • 10.3.6.2 Market Forecast
    • 10.3.7 Others
      • 10.3.7.1 Market Trends
      • 10.3.7.2 Market Forecast
  • 10.4 Latin America
    • 10.4.1 Brazil
      • 10.4.1.1 Market Trends
      • 10.4.1.2 Market Forecast
    • 10.4.2 Mexico
      • 10.4.2.1 Market Trends
      • 10.4.2.2 Market Forecast
    • 10.4.3 Others
      • 10.4.3.1 Market Trends
      • 10.4.3.2 Market Forecast
  • 10.5 Middle East and Africa
    • 10.5.1 Market Trends
    • 10.5.2 Market Breakup by Country
    • 10.5.3 Market Forecast

11 SWOT Analysis

  • 11.1 Overview
  • 11.2 Strengths
  • 11.3 Weaknesses
  • 11.4 Opportunities
  • 11.5 Threats

12 Value Chain Analysis

13 Porters Five Forces Analysis

  • 13.1 Overview
  • 13.2 Bargaining Power of Buyers
  • 13.3 Bargaining Power of Suppliers
  • 13.4 Degree of Competition
  • 13.5 Threat of New Entrants
  • 13.6 Threat of Substitutes

14 Price Analysis

15 Competitive Landscape

  • 15.1 Market Structure
  • 15.2 Key Players
  • 15.3 Profiles of Key Players
    • 15.3.1 Bayerische Motoren Werke AG
      • 15.3.1.1 Company Overview
      • 15.3.1.2 Product Portfolio
      • 15.3.1.3 Financials
      • 15.3.1.4 SWOT Analysis
    • 15.3.2 Daimler AG
      • 15.3.2.1 Company Overview
      • 15.3.2.2 Product Portfolio
      • 15.3.2.3 Financials
      • 15.3.2.4 SWOT Analysis
    • 15.3.3 Ford Motor Company
      • 15.3.3.1 Company Overview
      • 15.3.3.2 Product Portfolio
      • 15.3.3.3 Financials
      • 15.3.3.4 SWOT Analysis
    • 15.3.4 Hyundai Motor Company
      • 15.3.4.1 Company Overview
      • 15.3.4.2 Product Portfolio
      • 15.3.4.3 Financials
      • 15.3.4.4 SWOT Analysis
    • 15.3.5 Intel Corporation
      • 15.3.5.1 Company Overview
      • 15.3.5.2 Product Portfolio
      • 15.3.5.3 Financials
      • 15.3.5.4 SWOT Analysis
    • 15.3.6 International Business Machines Corporation
      • 15.3.6.1 Company Overview
      • 15.3.6.2 Product Portfolio
      • 15.3.6.3 Financials
      • 15.3.6.4 SWOT Analysis
    • 15.3.7 Micron Technology Inc.
      • 15.3.7.1 Company Overview
      • 15.3.7.2 Product Portfolio
      • 15.3.7.3 Financials
      • 15.3.7.4 SWOT Analysis
    • 15.3.8 Microsoft Corporation
      • 15.3.8.1 Company Overview
      • 15.3.8.2 Product Portfolio
      • 15.3.8.3 Financials
      • 15.3.8.4 SWOT Analysis
    • 15.3.9 NVIDIA Corporation
      • 15.3.9.1 Company Overview
      • 15.3.9.2 Product Portfolio
      • 15.3.9.3 Financials
      • 15.3.9.4 SWOT Analysis
    • 15.3.10 Qualcomm Incorporated
      • 15.3.10.1 Company Overview
      • 15.3.10.2 Product Portfolio
      • 15.3.10.3 Financials
      • 15.3.10.4 SWOT Analysis
    • 15.3.11 Tesla Inc.
      • 15.3.11.1 Company Overview
      • 15.3.11.2 Product Portfolio
      • 15.3.11.3 Financials
      • 15.3.11.4 SWOT Analysis
    • 15.3.12 Toyota Motor Corporation
      • 15.3.12.1 Company Overview
      • 15.3.12.2 Product Portfolio
      • 15.3.12.3 Financials
      • 15.3.12.4 SWOT Analysis
    • 15.3.13 Uber Technologies Inc.
      • 15.3.13.1 Company Overview
      • 15.3.13.2 Product Portfolio
      • 15.3.13.3 Financials
      • 15.3.13.4 SWOT Analysis

List of Figures

  • Figure 1: Global: Automotive Artificial Intelligence Market: Major Drivers and Challenges
  • Figure 2: Global: Automotive Artificial Intelligence Market: Sales Value (in Billion US$), 2018-2023
  • Figure 3: Global: Automotive Artificial Intelligence Market Forecast: Sales Value (in Billion US$), 2024-2032
  • Figure 4: Global: Automotive Artificial Intelligence Market: Breakup by Component (in %), 2023
  • Figure 5: Global: Automotive Artificial Intelligence Market: Breakup by Technology (in %), 2023
  • Figure 6: Global: Automotive Artificial Intelligence Market: Breakup by Process (in %), 2023
  • Figure 7: Global: Automotive Artificial Intelligence Market: Breakup by Application (in %), 2023
  • Figure 8: Global: Automotive Artificial Intelligence Market: Breakup by Region (in %), 2023
  • Figure 9: Global: Automotive Artificial Intelligence (Hardware) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 10: Global: Automotive Artificial Intelligence (Hardware) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 11: Global: Automotive Artificial Intelligence (Software) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 12: Global: Automotive Artificial Intelligence (Software) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 13: Global: Automotive Artificial Intelligence (Services) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 14: Global: Automotive Artificial Intelligence (Services) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 15: Global: Automotive Artificial Intelligence (Machine Learning and Deep Learning) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 16: Global: Automotive Artificial Intelligence (Machine Learning and Deep Learning) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 17: Global: Automotive Artificial Intelligence (Computer Vision) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 18: Global: Automotive Artificial Intelligence (Computer Vision) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 19: Global: Automotive Artificial Intelligence (Natural Language Processing) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 20: Global: Automotive Artificial Intelligence (Natural Language Processing) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 21: Global: Automotive Artificial Intelligence (Data Mining) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 22: Global: Automotive Artificial Intelligence (Data Mining) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 23: Global: Automotive Artificial Intelligence (Image Recognition) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 24: Global: Automotive Artificial Intelligence (Image Recognition) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 25: Global: Automotive Artificial Intelligence (Signal Recognition) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 26: Global: Automotive Artificial Intelligence (Signal Recognition) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 27: Global: Automotive Artificial Intelligence (Semi-Autonomous) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 28: Global: Automotive Artificial Intelligence (Semi-Autonomous) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 29: Global: Automotive Artificial Intelligence (Autonomous) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 30: Global: Automotive Artificial Intelligence (Autonomous) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 31: North America: Automotive Artificial Intelligence Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 32: North America: Automotive Artificial Intelligence Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 33: United States: Automotive Artificial Intelligence Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 34: United States: Automotive Artificial Intelligence Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 35: Canada: Automotive Artificial Intelligence Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 36: Canada: Automotive Artificial Intelligence Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 37: Asia-Pacific: Automotive Artificial Intelligence Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 38: Asia-Pacific: Automotive Artificial Intelligence Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 39: China: Automotive Artificial Intelligence Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 40: China: Automotive Artificial Intelligence Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 41: Japan: Automotive Artificial Intelligence Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 42: Japan: Automotive Artificial Intelligence Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 43: India: Automotive Artificial Intelligence Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 44: India: Automotive Artificial Intelligence Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 45: South Korea: Automotive Artificial Intelligence Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 46: South Korea: Automotive Artificial Intelligence Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 47: Australia: Automotive Artificial Intelligence Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 48: Australia: Automotive Artificial Intelligence Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 49: Indonesia: Automotive Artificial Intelligence Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 50: Indonesia: Automotive Artificial Intelligence Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 51: Others: Automotive Artificial Intelligence Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 52: Others: Automotive Artificial Intelligence Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 53: Europe: Automotive Artificial Intelligence Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 54: Europe: Automotive Artificial Intelligence Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 55: Germany: Automotive Artificial Intelligence Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 56: Germany: Automotive Artificial Intelligence Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 57: France: Automotive Artificial Intelligence Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 58: France: Automotive Artificial Intelligence Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 59: United Kingdom: Automotive Artificial Intelligence Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 60: United Kingdom: Automotive Artificial Intelligence Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 61: Italy: Automotive Artificial Intelligence Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 62: Italy: Automotive Artificial Intelligence Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 63: Spain: Automotive Artificial Intelligence Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 64: Spain: Automotive Artificial Intelligence Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 65: Russia: Automotive Artificial Intelligence Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 66: Russia: Automotive Artificial Intelligence Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 67: Others: Automotive Artificial Intelligence Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 68: Others: Automotive Artificial Intelligence Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 69: Latin America: Automotive Artificial Intelligence Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 70: Latin America: Automotive Artificial Intelligence Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 71: Brazil: Automotive Artificial Intelligence Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 72: Brazil: Automotive Artificial Intelligence Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 73: Mexico: Automotive Artificial Intelligence Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 74: Mexico: Automotive Artificial Intelligence Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 75: Others: Automotive Artificial Intelligence Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 76: Others: Automotive Artificial Intelligence Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 77: Middle East and Africa: Automotive Artificial Intelligence Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 78: Middle East and Africa: Automotive Artificial Intelligence Market: Breakup by Country (in %), 2023
  • Figure 79: Middle East and Africa: Automotive Artificial Intelligence Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 80: Global: Automotive Artificial Intelligence Industry: SWOT Analysis
  • Figure 81: Global: Automotive Artificial Intelligence Industry: Value Chain Analysis
  • Figure 82: Global: Automotive Artificial Intelligence Industry: Porter's Five Forces Analysis

List of Tables

  • Table 1: Global: Automotive Artificial Intelligence Market: Key Industry Highlights, 2023 and 2032
  • Table 2: Global: Automotive Artificial Intelligence Market Forecast: Breakup by Component (in Million US$), 2024-2032
  • Table 3: Global: Automotive Artificial Intelligence Market Forecast: Breakup by Technology (in Million US$), 2024-2032
  • Table 4: Global: Automotive Artificial Intelligence Market Forecast: Breakup by Process (in Million US$), 2024-2032
  • Table 5: Global: Automotive Artificial Intelligence Market Forecast: Breakup by Application (in Million US$), 2024-2032
  • Table 6: Global: Automotive Artificial Intelligence Market Forecast: Breakup by Region (in Million US$), 2024-2032
  • Table 7: Global: Automotive Artificial Intelligence Market: Competitive Structure
  • Table 8: Global: Automotive Artificial Intelligence Market: Key Players