자동차 분야 AI 시장 : 기회, 성장 촉진요인, 산업 동향 분석 및 예측(2025-2034년)

The Global AI In Automotive Market was valued at USD 4.8 billion in 2024 and is projected to witness a staggering CAGR of 42.8% between 2025 and 2034. This exponential growth reflects the rising demand for intelligent automotive solutions as AI technologies continue to redefine the future of mobility. The integration of AI into vehicles is transforming the way cars operate, elevating both the safety and driving experience of passengers. Leading automakers and technology companies are heavily investing in AI-driven systems, particularly for autonomous vehicles and next-generation Advanced Driver Assistance Systems (ADAS).

AI's role in enhancing vehicle intelligence, situational awareness, and real-time decision-making is pushing the automotive sector toward a future where cars are safer, more connected, and increasingly autonomous. From traffic management and collision avoidance to predictive maintenance and personalized in-car experiences, AI is becoming a central component of modern vehicle architecture. Automakers are also capitalizing on AI to offer predictive navigation, voice recognition, and behavior analysis features, enhancing both driver and passenger convenience. With growing consumer demand for safer and smarter mobility solutions, AI is set to become indispensable in the automotive world, further accelerating market growth over the next decade.

The surge in AI adoption is largely driven by the increasing implementation of technologies such as ADAS and autonomous driving solutions. AI significantly enhances vehicle safety and overall driving experience through seamless integration with advanced sensors, high-resolution cameras, radar, and LiDAR systems. Features like lane-keeping assistance, adaptive cruise control, automatic emergency braking, and pedestrian detection are powered by AI algorithms that enable vehicles to analyze their surroundings and make instant driving decisions, reducing accidents and improving road safety.

The market is primarily segmented based on processes like data mining and image recognition, with image recognition dominating the landscape. This segment is expected to generate over USD 110 billion by 2034, driven by its critical role in enabling autonomous vehicles and ADAS functionalities. Image recognition technology allows AI systems to process and interpret real-time environmental data, identifying pedestrians, traffic signs, vehicles, and lane markings with precision. The ability to perceive and understand dynamic road conditions makes image recognition a cornerstone of autonomous driving development.

In terms of components, the AI in automotive market is divided into hardware, software, and services, with hardware accounting for a significant 40% share in 2024. Automotive manufacturers are heavily investing in advanced hardware to support the computational demands of AI-powered vehicles. Specialized components such as AI chips, GPUs, sensors, and LiDAR systems are essential to handle vast streams of data for real-time processing, enabling seamless AI functionalities like automated driving, image detection, sensor fusion, and deep learning-based analytics.

The U.S. AI in automotive market commanded a notable 33% share and generated USD 1 billion in 2024, thanks to the country's robust technological infrastructure and rapid AI adoption. Major automakers and tech giants are leading the charge in developing AI-based autonomous driving technologies and advanced safety systems, firmly positioning the U.S. as a key player in shaping the global AI-driven automotive landscape.

Table of Contents

Chapter 1 Methodology & Scope

• 1.1 Research design
  • 1.1.1 Research approach
  • 1.1.2 Data collection methods
• 1.2 Base estimates & calculations
  • 1.2.1 Base year calculation
  • 1.2.2 Key trends for market estimation
• 1.3 Forecast model
• 1.4 Primary research and validation
  • 1.4.1 Primary sources
  • 1.4.2 Data mining sources
• 1.5 Market scope & definition

Chapter 2 Executive Summary

• 2.1 Industry 360⁰ synopsis, 2021 - 2034

Chapter 3 Industry Insights

• 3.1 Industry ecosystem analysis
  • 3.1.1 Supplier landscape
    • 3.1.1.1 Technology providers
    • 3.1.1.2 OEM Manufacturers
    • 3.1.1.3 Distributors
    • 3.1.1.4 End use
  • 3.1.2 Profit margin analysis
• 3.2 Technology & innovation landscape
• 3.3 Patent analysis
• 3.4 Regulatory landscape
• 3.5 Impact forces
  • 3.5.1 Growth drivers
    • 3.5.1.1 Advanced Driver Assistance Systems (ADAS) and Autonomous Vehicles
    • 3.5.1.2 Enhanced Vehicle Safety and Collision Avoidance
    • 3.5.1.3 Predictive Maintenance and Fleet Management
    • 3.5.1.4 AI-powered In-Vehicle Infotainment and Voice Assistants
  • 3.5.2 Industry pitfalls & challenges
    • 3.5.2.1 High Implementation Costs and Integration Complexity
    • 3.5.2.2 Data Privacy and Cybersecurity Concerns
• 3.6 Growth potential analysis
• 3.7 Porter's analysis
• 3.8 PESTEL analysis

Chapter 4 Competitive Landscape, 2024

• 4.1 Introduction
• 4.2 Company market share analysis
• 4.3 Competitive positioning matrix
• 4.4 Strategic outlook matrix

Chapter 5 Market Estimates & Forecast, By Component, 2021 - 2034 ($Bn)

• 5.1 Key trends
• 5.2 Hardware
• 5.3 Software
• 5.4 Service

Chapter 6 Market Estimates & Forecast, By Technology, 2021 - 2034 ($Bn)

• 6.1 Key trends
• 6.2 Computer vision
• 6.3 Context awareness
• 6.4 Deep learning
• 6.5 Machine learning
• 6.6 Natural Language Processing (NLP)

Chapter 7 Market Estimates & Forecast, By Process, 2021 - 2034 ($Bn)

• 7.1 Key trends
• 7.2 Data mining
• 7.3 Image recognition

Chapter 8 Market Estimates & Forecast, By Application, 2021 - 2034 ($Bn)

• 8.1 Key trends
• 8.2 Semi-Autonomous vehicles
• 8.3 Fully Autonomous vehicles

Chapter 9 Market Estimates & Forecast, By Region, 2021 - 2034 ($Bn)

• 9.1 Key trends
• 9.2 North America
  • 9.2.1 U.S.
  • 9.2.2 Canada
• 9.3 Europe
  • 9.3.1 UK
  • 9.3.2 Germany
  • 9.3.3 France
  • 9.3.4 Italy
  • 9.3.5 Spain
  • 9.3.6 Russia
  • 9.3.7 Nordics
• 9.4 Asia Pacific
  • 9.4.1 China
  • 9.4.2 India
  • 9.4.3 Japan
  • 9.4.4 Australia
  • 9.4.5 South Korea
  • 9.4.6 Southeast Asia
• 9.5 Latin America
  • 9.5.1 Brazil
  • 9.5.2 Mexico
  • 9.5.3 Argentina
• 9.6 MEA
  • 9.6.1 UAE
  • 9.6.2 South Africa
  • 9.6.3 Saudi Arabia

Chapter 10 Company Profiles

• 10.1 Alphabet
• 10.2 Audi
• 10.3 Bayerische Motoren Werke (BMW)
• 10.4 Daimler
• 10.5 Didi Chuxing
• 10.6 Ford Motor
• 10.7 General Motors
• 10.8 Harman International Industries
• 10.9 Honda Motor
• 10.10 Intel
• 10.11 International Business Machines (IBM)
• 10.12 Microsoft
• 10.13 NVIDIA
• 10.14 Qualcomm
• 10.15 Tesla
• 10.16 Toyota Motor
• 10.17 Uber Technologies
• 10.18 Volvo Car
• 10.19 Waymo
• 10.20 Xilinx