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1446821

全球汽车人工智慧市场 - 2024-2031

Global Automotive Artificial Intelligence Market - 2024-2031

出版日期: 2024年02月13日 | 出版商:

DataM Intelligence | 英文 186 Pages | 商品交期: 约2个工作天内

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简介目录

概述

全球汽车人工智慧市场将于2023年达到21亿美元，预计2031年将达到86亿美元，2024-2031年预测期间CAGR为24.1%。

汽车对人工智慧技术的需求是由增强安全性、提高效率和增加便利性的潜力所推动的。人工智慧演算法和系统即时分析来自感测器、摄影机和其他来源的大量资料，使车辆能够做出智慧决策并适应不断变化的路况。这些技术正在适应先进驾驶辅助系统和全自动驾驶汽车的发展方向。

人工智慧正在彻底改变汽车产业，特别是在自动驾驶汽车领域。自动驾驶汽车的概念与未来的技术愿景相关，实际进展高于预期。然而，根据《富比士》报道，预计全球汽车人工智慧市场将大幅成长，到 2031 年价值将达到 600 亿美元左右。

到2023年，北美预计将成为成长第二快的地区，约占全球汽车人工智慧市场的25%。美国等国家随着通货膨胀削减法案的实施而不断成长。例如，根据 IEA 的数据，2022 年 8 月至 2023 年 3 月期间，主要电动车和电池製造商宣布在 IRA 后对北美电动车供应链累计投资 520 亿美元，这将进一步扩大汽车人工智慧市场。

动力学

专注于人工智慧的永续发展

人工智慧在汽车行业，尤其是电动汽车行业的可持续性因素是不可否认的。人工智慧有益于交通运输的绿色和永续的未来，并为其做出贡献。人工智慧在电动车领域的主要优势是提高效率。人工智慧智慧地管理能源资源，最大限度地扩大电动车的续航里程并最大限度地减少能源浪费，使其更加高效和永续。

此外，例如，根据 IBM 的一项研究，50% 的消费者计划在未来三年内采用电动车。人工智慧被用来优化充电基础设施、预测能源需求并提高电网效率，以满足不断增长的电动车需求。消费者采用电动车的动机包括充电桩的使用、环保意识和充电便利性。

对人工智慧驱动的电动车的需求不断增长

电动车的日益普及是全球汽车产业人工智慧市场的主要成长因素。人工智慧透过实现预测性维护、智慧能源管理和自动驾驶等功能，进一步增强电动车的功能。它创造了对人工智慧技术的需求，以优化电动车性能、增强用户体验和管理能源效率。

此外，例如丰田研究院推出了一种新的生成式人工智慧技术，透过改进汽车设计流程和优化车辆空气动力学来增强电动车（EV）的续航里程。丰田的目标是最大限度地提高电动车的续航里程。这项创新与丰田计划在 2026 年至 2028 年间推出下一代电动车电池的计划相一致，承诺将其当前电动车型 bZ4X 的续航里程增加一倍。

与黑盒和人工智慧技能相关的挑战

人工智慧的黑盒子问题是理解人工智慧模型如何做出决策的困难，这确实是汽车产业自主系统开发的重大挑战。人工智慧模型缺乏透明度和可解释性，限制了人们完全信任和验证其决策过程的能力。

缺乏人工智慧专业知识是汽车产业和其他产业面临的主要缺点。开发和部署具有专业技能和知识的人工智慧技术需要资料科学、机器学习和演算法开发的概念。人工智慧专业人员的短缺和这些技术的复杂性为充分发挥人工智慧在汽车产业的潜力带来了挑战。

The demand for AI technologies in cars is driven by the potential for enhanced safety, improved efficiency and increased convenience. AI algorithms and systems analyze vast amounts of data from sensors, cameras and other sources in real time which allows vehicles to make intelligent decisions and adapt to changing road conditions. The technologies are adapting the way for advanced driver assistance systems and fully autonomous vehicles.

Artificial intelligence is revolutionizing the automotive industry as particularly in the realm of autonomous cars. The concept of self-driving cars associated with futuristic visions of technology and the actual progress is higher than expected. However, according to Forbes, estimate suggest that the global market for AI in automobiles will experience substantial growth and reach the value of around US$ 60 billion by 2031.

In 2023, North America is expected to be the second-fastest growing region, holding about 25% of the global automotive artificial intelligence market. Countries like U.S. are growing with the implementation of the Inflation Reduction Act. For instance, according to IEA between August 2022 and March 2023, major electric vehicle and battery makers announced a cumulative post-IRA investment of US$ 52 billion in North American EV supply chains which is further going to increase the automotive AI market.

Dynamics

Focus on Sustainability with AI

The sustainability factor of AI in the automotive industry and particularly in the e-mobility sector is undeniable. AI benefits and contributes to a greener and sustainable future of transportation. Major advantage of AI in the e-mobility sector is increased efficiency. AI intelligently manages energy resources maximizing the range of electric vehicles and minimizing energy waste which makes them more efficient and sustainable.

Furthermore, for instance, according to an IBM study, 50% of consumers plan to adopt EVs in the next three years. AI is being used to optimize charging infrastructure, predict energy demand and improve grid efficiency to meet rising EV demands. Consumer motivations for adopting EVs include access to charge points, environmental awareness and charging convenience.

Rising Demand for AI-Powered EVs

The increasing adoption of electric vehicles is a major growth factor for the global market for AI in the automotive industry. AI further enhances the capabilities of EVs by enabling features like predictive maintenance, intelligent energy management and autonomous driving. It created a demand for AI technologies to optimize EV performance, enhance user experience and manage energy efficiency.

Furthermore, for instance Toyota's Research Institute unveiled a new generative AI technique to enhance electric vehicle (EV) range by improving the car design process and optimizing vehicle aerodynamic. Toyota aims to maximize EV range. The innovation aligns with Toyota's plans to introduce next-gen EV batteries between 2026 and 2028, promising double the range of their current electric model, the bZ4X.

Challenges Related to Black-box and AI Skills

The black-box problem of AI which is a difficulty in understanding how AI models make decisions, is indeed a significant challenge in the development of autonomous systems for the automotive industry. The lack of transparency and interpretability in AI models limiting people ability to fully trust and validate their decision-making processes.

The lack of AI expertise is a major drawback faced by the automotive industry and other sectors. Developing and deploying AI technologies with specialized skills and knowledge requires the concepts of data science, machine learning and algorithm development. The shortage of AI professionals and the complexity of these technologies make challenges for fully harnessing the potential of AI in the automotive industry.

Segment Analysis

The global automotive artificial intelligence market is segmented based on technology, application and region.

Rising Demand for Driving Assistance Drives the Segment Growth

AI driving features is expected to be the fastest growing segment with 1/3rd of the market during the forecast period 2024-2031. Self-driving vehicles depends on five essential components to navigate and operate on roads. The initial step in this process is computer vision which differs from how humans rely on their eyes and brain to drive. Driverless cars utilize computer images to identify lane lines and track other vehicles.

To effectively monitor their surroundings vehicles also incorporate multiple cameras. Tesla equips its cars with eight surround cameras which enable a 360-degree view of the area within approximately 500 feet of the vehicle. The cameras facilitate various tasks like lane detection, estimating road curvature, detecting obstacles, classifying stop signs, identifying traffic lights and many more.

Geographical Penetration

Rising AI Implementation in Automotive in Asia-Pacific

Asia-Pacific is the dominant region in the global automotive artificial intelligence market covering about 30% of the market. The region is growing in AI-based automotive market driven by factors like technological advancements, strong manufacturing base, government support, rising demand for smart and connected vehicles and collaborations between automotive companies and technology partners. Japan and China made a notable strides in AI and automotive technologies with companies like Toyota, Hyundai and Honda investing in AI to enhance vehicle capabilities.

The latest data from China indicates a significant increase in shipments and retail sales of new-EVs in 2022. Shipments of EVs to dealerships surged by about 95% to reach around 6.5 million units and in line with the forecast of about 6.5 million made by the Passenger Car Association. Moreover, nationwide retail sales of NEVs including pure electric cars and hybrids have experienced a notable growth of 90% to reach about 5.7 million units. In December 2022 NEV retail sales rose by 6.5% compared to November, reaching around 641,000 units.

Competitive Landscape

The major global players in the market include Carvi, German Autolabs, Raven, Argo AI, Deepscale, Cisco, Waymo, Microsoft Azure, Nvidia and Tesla.

COVID-19 Impact

The COVID-19 pandemic shows both positive and negative impact on the integration of AI in the automotive industry. It caused delays in development and testing of AI-based automotive technologies, but also accelerated the adoption of digital tools and remote collaboration platforms. The focus on safety and hygiene led to increased interest in AI-powered features such as touchless interfaces and improved air filtration systems.

COVID-19 caused disruptions in R&D activities due to travel restrictions and facility closures which results in delays in projects and testing. The pandemic also prompted increased investment in digital tools and virtual collaboration platforms to continue R&D efforts remotely. The global supply chains of automotive companies were severely affected by delayed production and shortages of key components due to lockdown measures and transportation restriction.

Russia-Ukraine War Impact

The conflict between Russia and Ukraine has potentially impacted the AI automotive market in several ways. The disruption of supply chains and trade routes between the two countries could affect the sourcing of components including AI-related technologies for the automotive industry. The conflict results in damage to infrastructure including transportation networks and supply chains, further complicating business operations and hindering the smooth flow of goods and services.

Geopolitical uncertainties resulting from the conflict may lead to cautious investment decisions and business operations, potentially slowing down collaborations and expansions related to AI integration in the automotive sectors. The conflict's focus on military and security technologies could divert attention and resources away from commercial developments which potentially impact the pace of AI innovation within the automotive industry.

The conflict puts a negative impact on consumer confidence. The uncertainties surrounding the conflict and its potential consequences led to a decrease in consumer confidence which results in reduced spending and a decline in demand for products and services, including automobiles and AI-powered vehicles. The factors collectively highlight the adverse effects of the conflict on business operations, infrastructure and consumer sentiment in the region.

AI Impact

The integration of artificial intelligence had a transformative impact on the automotive industry. AI technologies played a crucial role in enhancing vehicle intelligence, safety and autonomous capabilities. In the new world of advanced driver-assistance systems AI algorithms supports features like adaptive cruise control, lane-keeping assistance and automatic emergency braking and enhancing the overall safety of vehicles. Also, AI powers computer vision systems recognizes and interpret road signs, pedestrians and other objects which provide valuable information to the driver and supporting decision-making.

Generative AI models like Jasper and DALL-E 2, are indeed revolutionizing customer engagement in marketing and advertising which includes within the automotive industry. The powerful tools leverage the capabilities of generative models like GPT-3 to automatically generate customer-centric marketing content across various channels.

By Technology

Machine Learning & Deep Learning
Computer Vision
Natural Language Processing

By Application

AI Driving Features
AI Cloud Services
AI Automotive Insurance
AI in Car Manufacturing

By Region

North America
- U.S.
- Canada
- Mexico
Europe
- Germany
- UK
- France
- Italy
- Russia
- Rest of Europe
South America
- Brazil
- Argentina
- Rest of South America
Asia-Pacific
- China
- India
- Japan
- Australia
- Rest of Asia-Pacific
Middle East and Africa

Key Developments

In May 2021, Didi Chuxing announced a strategic agreement with Volvo Cars to develop autonomous vehicles for DiDi's self-driving test fleet. Volvo Cars' autonomous drive-ready XC90 vehicles will be the first to feature DiDi Gemini, a new self-driving hardware platform powered by NVIDIA DRIVE AGX Pegasus. The vehicles, outfitted with DiDi's Gemini self-driving hardware platform, will eventually be used for robotaxi services.
In March 2021, BMW announced its next-generation infotainment system, iDrive 8, intended to operate as a digital, intelligent and active partner for drivers. The technology driven by machine learning, natural language processing, AI cloud and 5G will have its debut with the next BMW iX and i4.
In February 2021, Volkswagen and Microsoft collaborated to make self-driving car software. VW's new software division will establish a cloud-based platform with Microsoft to assist streamline development processes, allow for speedier integration into its vehicle fleet and make it much easier to send software upgrades to add new features to cars.

Why Purchase the Report?

To visualize the global automotive artificial intelligence market segmentation based on technology, application and region, as well as understand key commercial assets and players.
Identify commercial opportunities by analyzing trends and co-development.
Excel data sheet with numerous data points of automotive artificial intelligence market-level with all segments.
PDF report consists of a comprehensive analysis after exhaustive qualitative interviews and an in-depth study.
Product mapping available as excel consisting of key products of all the major players.

The global Automotive Artificial Intelligence market report would provide approximately 54 tables, 43 figures and 186 pages.

Target Audience 2024

Manufacturers/ Buyers
Industry Investors/Investment Bankers
Research Professionals
Emerging Companies

1. Methodology and Scope

1.1. Research Methodology
1.2. Research Objective and Scope of the Report

2. Definition and Overview

3. Executive Summary

3.1. Snippet by Technology
3.2. Snippet by Application
3.3. Snippet by Region

4. Dynamics

4.1. Impacting Factors
- 4.1.1. Drivers
  - 4.1.1.1. Focus on Sustainability with AI
  - 4.1.1.2. Rising Demand for AI-Powered EVs
- 4.1.2. Restraints
  - 4.1.2.1. Challenges Related to Black-box and AI Skills
- 4.1.3. Opportunity
- 4.1.4. Impact Analysis

5. Industry Analysis

5.1. Porter's Five Force Analysis
5.2. Supply Chain Analysis
5.3. Pricing Analysis
5.4. Regulatory Analysis
5.5. Russia-Ukraine War Impact Analysis
5.6. DMI Opinion

6. COVID-19 Analysis

6.1. Analysis of COVID-19
- 6.1.1. Scenario Before COVID
- 6.1.2. Scenario During COVID
- 6.1.3. Scenario Post COVID
6.2. Pricing Dynamics Amid COVID-19
6.3. Demand-Supply Spectrum
6.4. Consumer Electronics Initiatives Related to the Market During Pandemic
6.5. Manufacturers Strategic Initiatives
6.6. Conclusion

7. By Technology

7.1. Introduction
- 7.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
- 7.1.2. Market Attractiveness Index, By Technology
7.2. Machine Learning & Deep Learning*
- 7.2.1. Introduction
- 7.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
7.3. Computer Vision
7.4. Natural Language Processing

8. By Application

8.1. Introduction
- 8.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
- 8.1.2. Market Attractiveness Index, By Application
8.2. AI Driving Features*
- 8.2.1. Introduction
- 8.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
8.3. AI Cloud Services
8.4. AI Automotive Insurance
8.5. AI in Car Manufacturing

9. By Region

9.1. Introduction
- 9.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Region
- 9.1.2. Market Attractiveness Index, By Region
9.2. North America
- 9.2.1. Introduction
- 9.2.2. Key Region-Specific Dynamics
- 9.2.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
- 9.2.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
- 9.2.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
  - 9.2.5.1. U.S.
  - 9.2.5.2. Canada
  - 9.2.5.3. Mexico
9.3. Europe
- 9.3.1. Introduction
- 9.3.2. Key Region-Specific Dynamics
- 9.3.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
- 9.3.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
- 9.3.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
  - 9.3.5.1. Germany
  - 9.3.5.2. UK
  - 9.3.5.3. France
  - 9.3.5.4. Italy
  - 9.3.5.5. Russia
  - 9.3.5.6. Rest of Europe
9.4. South America
- 9.4.1. Introduction
- 9.4.2. Key Region-Specific Dynamics
- 9.4.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
- 9.4.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
- 9.4.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
  - 9.4.5.1. Brazil
  - 9.4.5.2. Argentina
  - 9.4.5.3. Rest of South America
9.5. Asia-Pacific
- 9.5.1. Introduction
- 9.5.2. Key Region-Specific Dynamics
- 9.5.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
- 9.5.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
- 9.5.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
  - 9.5.5.1. China
  - 9.5.5.2. India
  - 9.5.5.3. Japan
  - 9.5.5.4. Australia
  - 9.5.5.5. Rest of Asia-Pacific
9.6. Middle East and Africa
- 9.6.1. Introduction
- 9.6.2. Key Region-Specific Dynamics
- 9.6.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
- 9.6.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application

10. Competitive Landscape

10.1. Competitive Scenario
10.2. Market Positioning/Share Analysis
10.3. Mergers and Acquisitions Analysis

11. Company Profiles

11.1. Carvi*
- 11.1.1. Company Overview
- 11.1.2. Product Portfolio and Description
- 11.1.3. Financial Overview
- 11.1.4. Key Developments
11.2. German Autolabs
11.3. Raven
11.4. Argo AI
11.5. Deepscale
11.6. Cisco
11.7. Waymo
11.8. Microsoft Azure
11.9. Nvidia
11.10. Tesla

LIST NOT EXHAUSTIVE