サンプル依頼リスト カート
  • English
  • Traditional Chinese
  • Simplified Chinese
デフォルト表紙
市場調査レポート
商品コード
1519831

自動車用人工知能市場レポート：コンポーネント、技術、プロセス、用途、地域別、2024年～2032年

Automotive Artificial Intelligence Market Report by Component, Technology, Process, Application, and Region 2024-2032

出版日
発行
IMARC
ページ情報
英文 149 Pages
納期
2～3営業日
カスタマイズ可能
価格
価格表記: USDを日本円(税抜)に換算
本日の銀行送金レート: 1USD=146.96円
自動車用人工知能市場レポート：コンポーネント、技術、プロセス、用途、地域別、2024年～2032年
出版日: 2024年07月01日
発行: IMARC
ページ情報: 英文 149 Pages
納期: 2～3営業日
GIIご利用のメリット
  • 全表示
  • 概要
  • 図表
  • 目次
概要

世界の自動車用人工知能の市場規模は2023年に39億米ドルに達しました。今後、IMARC Groupは、市場は2032年までに339億米ドルに達し、2024年から2032年の間に26.6％の成長率（CAGR）を示すと予測しています。高度な機能に対する消費者の需要の高まり、さまざまな政府規制の賦課、大幅な技術進歩、センサー技術の急速なコスト削減、交通管理における人工知能（AI）の需要の高まり、持続可能性の重視の高まりなどが、市場を推進している主な要因の一部です。

自動車用人工知能（AI）とは、自動車の機能性、安全性、ユーザーエクスペリエンスを高めるために、自動車内に技術を統合することを指します。運転支援、車載バーチャルアシスタント、予知保全、完全自律システムなど、さまざまなシステムで構成されています。自動車AIは、アダプティブ・クルーズ・コントロール、衝突回避、 促進要因・モニタリング、音声操作、交通標識認識、自動駐車、リアルタイム交通モニタリングなどに広く利用されています。AIは、安全性の強化、効率の向上、排出ガスの削減、時間の節約、交通の流れの強化、ユーザー体験の向上、持続可能性の促進を支援します。

センサー技術とコンピューティング・パワーの急速なコスト削減は、自動車メーカーにとってAIの導入をより経済的に実行可能なものにしており、市場成長にプラスの影響を与えています。このほか、都市化の進展とそれに伴う交通渋滞の増加により、交通管理や経路最適化におけるAIの需要が高まっていることも、市場成長に寄与しています。さらに、優れた予知保全、リアルタイムの意思決定、パーソナライズされたユーザー体験を可能にするために、自動車メーカーによるAIの活用が増加していることも、市場の成長を支えています。さらに、高度なテレマティクスや遠隔車両制御など、AI統合の新たな道を提供するモノのインターネット（IoT）やV2X（Vehicle-to-Everything）通信の最近の進歩が、市場の成長を後押ししています。さらに、持続可能性を重視する傾向が強まっていることが、燃費の最適化や代替燃料システムの管理を目的としたAIの需要を促進しています。

自動車用人工知能市場動向/促進要因：

高度な機能に対する需要の高まり

高度な機能に対する消費者の需要の高まりは、自動車用人工知能（AI）市場の成長を促す顕著な要因です。ユーザーはますますハイテクに精通するようになっており、アダプティブ・クルーズ・コントロール、自動駐車、高度なナビゲーション・システムなど、自動車の高度な機能に対する期待が高まっています。さらに、特に日常生活でテクノロジーと深く関わっている若年層が利便性を追求していることが、市場の成長に拍車をかけています。これとは別に、都市中心部での混雑の増大が、複雑な市街地走行を管理するインテリジェント機能を提供する自動車への需要を促進しています。このような消費者の期待の変化は、自動車設計にAI技術を採用することを、単なる付加価値としてではなく、購買決定に直接影響する中核的な要素としてメーカーに大きなプレッシャーを与えています。

さまざまな政府規制の賦課

政府の規制は、自動車分野へのAIの導入を推進する上でますます重要な役割を果たしています。交通安全は世界中で最も重要な関心事となりつつあり、当局は自動車により厳しい安全ガイドラインと要件を課すよう促しています。こうしたガイドラインでは、衝突回避システム、車線逸脱警告、緊急ブレーキシステムなど、AI技術に大きく依存する高度な安全機能の搭載が義務付けられていることが多いです。さらに、規制の枠組みは国レベルで策定されるだけでなく、より高い安全基準を世界に推進するため、地域間の調和も進んでいます。さらに、法規制は交通安全の向上に役立つと同時に、自動車産業における技術革新の触媒として機能するなど、2つの役割を果たしています。これに加えて、規制は自動車メーカーにAI技術の研究開発（R&D）に注力するよう迫る外的な力として効果的に作用します。

著しい技術進歩

急速な技術進歩は、自動車AI市場を推進する上で極めて重要です。これに伴い、機械学習（ML）アルゴリズムの進歩により、自動車はリアルタイムの意思決定を行えるようになり、それによって自律走行能力が飛躍的に向上しました。さらに、より高い精度と耐久性により、物体認識と距離測定アプリケーションに高度なセンサー技術を取り入れることが、市場成長にプラスの影響を与えています。さらに、予測保守、経路最適化、さらにはライダーの快適性のために、大規模なデータセットをリアルタイムで処理・解釈するデータ分析の活用が市場成長に寄与しています。これに加えて、技術の進歩はコスト削減をもたらし、より広範な車両に高度なAI機能を統合することが経済的に実行可能になっています。

目次

第1章 序文

第2章 調査範囲と調査手法

  • 調査の目的
  • ステークホルダー
  • データソース
    • 一次情報
    • 二次情報
  • 市場推定
    • ボトムアップアプローチ
    • トップダウンアプローチ
  • 調査手法

第3章 エグゼクティブサマリー

第4章 イントロダクション

  • 概要
  • 主要業界動向

第5章 世界の自動車用人工知能市場

  • 市場概要
  • 市場実績
  • COVID-19の影響
  • 市場予測

第6章 市場内訳：コンポーネント別

  • ハードウェア
    • 市場動向
    • 市場予測
  • ソフトウェア
    • 市場動向
    • 市場予測
  • サービス
    • 市場動向
    • 市場予測

第7章 市場内訳：技術別

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

第8章 市場内訳：プロセス別

  • データマイニング
    • 市場動向
    • 市場予測
  • 画像認識
    • 市場動向
    • 市場予測
  • 信号認識
    • 市場動向
    • 市場予測

第9章 市場内訳：用途別

  • 半自律型
    • 市場動向
    • 市場予測
  • 自律型
    • 市場動向
    • 市場予測

第10章 市場内訳：地域別

  • 北米
    • 米国
    • カナダ
  • アジア太平洋地域
    • 中国
    • 日本
    • インド
    • 韓国
    • オーストラリア
    • インドネシア
    • その他
  • 欧州
    • ドイツ
    • フランス
    • 英国
    • イタリア
    • スペイン
    • ロシア
    • その他
  • ラテンアメリカ
    • ブラジル
    • メキシコ
    • その他
  • 中東・アフリカ
    • 市場動向
    • 市場内訳：国別
    • 市場予測

第11章 SWOT分析

  • 概要
  • 強み
  • 弱み
  • 機会
  • 脅威

第12章 バリューチェーン分析

第13章 ポーターのファイブフォース分析

  • 概要
  • 買い手の交渉力
  • 供給企業の交渉力
  • 競合の程度
  • 新規参入業者の脅威
  • 代替品の脅威

第14章 価格分析

第15章 競合情勢

  • 市場構造
  • 主要企業
  • 主要企業のプロファイル
    • 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.
図表

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
目次
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