自動車用人工知能の世界市場 2024-2031

概要

世界の自動車用人工知能（AI）市場は、2023年に21億米ドルに達し、2024年から2031年の予測期間中にCAGR 24.1％で成長し、2031年には86億米ドルに達すると予測されています。

自動車におけるAI技術の需要は、安全性の向上、効率性の改善、利便性の向上の可能性が原動力となっています。AIアルゴリズムとシステムは、センサーやカメラなどからの膨大なデータをリアルタイムで分析し、これによって自動車はインテリジェントな判断を下し、道路状況の変化に適応できるようになります。この技術はADAS（先進運転支援システム）や完全自律走行車への道を開いています。

人工知能は、特に自律走行車の領域で、自動車産業に革命をもたらしています。自動運転車というコンセプトは、テクノロジーの未来的なビジョンと結びついており、実際の進歩は予想以上です。しかし、フォーブスによると、自動車におけるAIの世界市場は大幅な成長を遂げ、2031年までに約600億米ドルの規模に達すると推定されています。

2023年には、北米が世界の自動車用人工知能市場の約25％を占め、2番目に急成長する地域になると予想されています。米国のような国々は、インフレ抑制法の実施によって成長しています。例えば、IEAによると、2022年8月から2023年3月までの間に、主要な電気自動車メーカーとバッテリーメーカーは、北米のEVサプライチェーンへのIRA後の累積投資額520億米ドルを発表しており、これが自動車AI市場をさらに拡大させようとしています。

ダイナミクス

AIによる持続可能性の重視

自動車産業、特にEモビリティ分野におけるAIの持続可能性要素は否定できないです。AIは、より環境に優しく持続可能な未来の輸送に利益をもたらし、貢献します。e-モビリティ分野におけるAIの主な利点は、効率の向上です。AIはエネルギー資源をインテリジェントに管理することで、電気自動車の航続距離を最大化し、エネルギーの浪費を最小限に抑えます。

さらに、例えばIBMの調査によると、今後3年間で50％の消費者がEVの導入を計画しています。AIは、充電インフラの最適化、エネルギー需要の予測、EV需要の増加に対応するための送電網効率の改善に利用されています。消費者がEVを導入する動機には、充電ポイントへのアクセス、環境意識、充電の利便性などがあります。

AI搭載EVに対する需要の高まり

電気自動車の採用が増加していることは、自動車産業におけるAIの世界市場の主要な成長要因です。AIは、予知保全、インテリジェント・エネルギー管理、自律走行などの機能を実現することで、EVの能力をさらに高める。そのため、EVの性能を最適化し、ユーザー体験を向上させ、エネルギー効率を管理するAI技術に対する需要が生まれました。

さらに、例えばトヨタの研究所は、自動車の設計プロセスを改善し、車両の空力特性を最適化することで、電気自動車（EV）の航続距離を向上させる新しい生成AI技術を発表しました。トヨタはEV航続距離の最大化を目指しています。この技術革新は、2026年から2028年の間に次世代EVバッテリーを導入するというトヨタの計画に沿ったもので、現在の電気自動車モデル「bZ4X」の航続距離を2倍にすることを約束しています。

ブラックボックスとAIスキルに関する課題

AIのブラックボックス問題とは、AIモデルがどのように意思決定を行うかを理解することの難しさであり、自動車産業向けの自律走行システムの開発における重要な課題です。AIモデルの透明性と解釈可能性の欠如は、人々がその意思決定プロセスを完全に信頼し、検証する能力を制限します。

AIの専門知識の欠如は、自動車産業や他のセクターが直面する大きな欠点です。専門的なスキルと知識をもってAI技術を開発・展開するには、データサイエンス、機械学習、アルゴリズム開発の概念が必要です。AIの専門家が不足していることと、これらの技術が複雑であることが、自動車産業でAIの可能性を十分に活用するための課題となっています。

目次

第1章 調査手法と調査範囲

第2章 定義と概要

第3章 エグゼクティブサマリー

第4章 市場力学

• 影響要因
  • 促進要因
    • AIによる持続可能性の重視
    • AI搭載EVに対する需要の高まり
  • 抑制要因
    • ブラックボックスとAIスキルに関する課題
  • 機会
  • 影響分析

第5章 産業分析

• ポーターのファイブフォース分析
• サプライチェーン分析
• 価格分析
• 規制分析
• ロシア・ウクライナ戦争の影響分析
• DMIの見解

第6章 COVID-19分析

第7章 テクノロジー別

• 機械学習とディープラーニング
• コンピュータビジョン
• 自然言語処理

第8章 アプリケーション別

• AIドライビング機能
• AIクラウドサービス
• AI自動車保険
• 自動車製造におけるAI

第9章 地域別

• 北米
  • 米国
  • カナダ
  • メキシコ
• 欧州
  • ドイツ
  • 英国
  • フランス
  • イタリア
  • ロシア
  • その他欧州
• 南米
  • ブラジル
  • アルゼンチン
  • その他南米
• アジア太平洋
  • 中国
  • インド
  • 日本
  • オーストラリア
  • その他アジア太平洋地域
• 中東・アフリカ

第10章 競合情勢

• 競合シナリオ
• 市況/シェア分析
• M&A分析

第11章 企業プロファイル

• Carvi
  • 会社概要
  • 製品ポートフォリオと説明
  • 財務概要
  • 主な発展
• German Autolabs
• Raven
• Argo AI
• Deepscale
• Cisco
• Waymo
• Microsoft Azure
• Nvidia
• Tesla

第12章 付録

Overview

Global Automotive Artificial Intelligence Market reached US$ 2.1 billion in 2023 and is expected to reach US$ 8.6 billion by 2031, growing with a CAGR of 24.1% during the forecast period 2024-2031.

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

Table of Contents

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

12. Appendix

• 12.1. About Us and Services
• 12.2. Contact Us