자동차용 AI 시장 평가 : 제공, 프로세스, 기술, 용도, 컴포넌트, 차량 유형, 지역별 기회 및 예측(2017-2031년)

Global automotive artificial intelligence market is projected to witness a CAGR of 20.67% during the forecast period 2024-2031, growing from USD 3.02 billion in 2023 to USD 13.58 billion in 2031. The higher focus on adding elements that elevate the customer experience is garnering market growth. Concepts like self-driving cars, voice controls, and advanced safety features are anticipated to propel the market growth. Furthermore, the integration of artificial intelligence with infotainment systems is putting ease into end-user experience. The expanding manufacturing space is adopting artificial intelligence to deliver faster production and lower human error.

Industry 4.0 and its components have transformed the manufacturing space and contributed to the automotive sector. However, artificial intelligence has become an active component of the automotive sector, from easing manufacturing to advancing advanced driver assistance systems (ADAS). The next phase of artificial intelligence deployment includes its integration with cloud technology for predictive maintenance and data monitoring procedures. Furthermore, AI has increased the vehicle security layers with its role in smart key systems, adaptive cruise control (ACC), and lane departure warning systems.

For instance, in December 2023, Nvidia Corporation and MediaTek allied to propel artificial intelligence in the automotive sector that transforms in-car experience and sets new standards for smart vehicles. MediaTek and Nvidia, two of the world's leading semiconductor companies, recently announced a strategic alliance to bring AI to the automotive industry.

Improved Safety Dynamics to Fuel the AI Adoption

The long-range sensors, cameras, and other components integrate with the central infotainment system to deliver real-time monitoring on-board. Artificial intelligence is an inseparable part of self-driving vehicles, and it unlocks comfort for all including passengers, drivers, and automobile manufacturers. The voice recognition and control units in autonomous vehicles are powered by AI technologies such as natural language processing (NLP) and machine learning (ML). Apart from AI's role in each stage of automotive development, path planning and navigation support is delivered through AI. It includes localization, perception, and collision avoidance to directly optimize the routes.

The utilization of artificial intelligence in the automotive sector enables personalized driving experiences, working as a bridge between human and machine technology to minimize errors and facilitate real-time information, prediction, and suggestions for the driver.

For instance, in May 2023, Huawei introduced its new ADAS platform named ADS 2.0 with a long range of improvements related to driving experience and safety. The new platform consists of hardware, new AI-powered features, and a timeline for NCA (Navigation Cruise Assist). It delivers improved map accuracy, enhanced safety, and human-like judgment and operation.

Connected Car Technology and Predictive Maintenance to Propel Market Growth

The evolving connected car technology and integration of generative AI complement each other and help the vehicles. The structure of the Internet of Things (IoT) with 5G deployments has access to a continuous stream of the Internet, enabling access to vehicle communication systems and other online services. It includes the vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), and vehicle-to-everything (V2X). Artificial intelligence has advanced due to internet connectivity and app-to-car connectivity.

Since AI leverages IoT in cars, it contributes to predictive maintenance in the industry. IoT systems help monitor real-time vehicle conditions by analyzing the massive amount of vehicle data, allowing managers to know when maintenance is needed. As soon as an IoT sensor detects a potential problem, it warns automobile managers to take preventative action before it becomes a major issue. In addition, AI helps reduce emissions, improve fuel efficiency, and enhance overall vehicle performance.

For instance, in December 2023, TomTom N.V. allied with Microsoft to bring generative AI to the automotive industry. The result of the partnership is a fully integrated conversational assistant powered by AI that improves voice interactions with infotainment and location search, as well as vehicle command systems. The result of TomTom's experience combined with Microsoft's cutting-edge AI technology enables drivers to engage in conversational conversations with their vehicles.

Government Support to Drive Automotive AI Market Size

Governments around the world seek innovation and experimentation in each sector. Hence, it provides subsidies and investments for new technological integrations. Artificial intelligence is already used in implementing traffic rules with its integration with traffic cameras. Governments collaborate with technological giants to develop new technology. Furthermore, the push for EV adoption has fuelled the demand for AI. The government supports automakers in their manufacturing process.

The government invests in major technological projects to boost green mobility and manufacturing projects to build sustainable automotive structures. The United Kingdom's Centre for Connected and Autonomous Vehicles (CCAV) invested USD 20.07 million to fund 13 different projects focusing on self-driving technologies, services, and products. The funding is part of the government's USD 54.25 million program to support green technology innovation, the economy, and job creation.

Self-Driving Cars and Steering Assistance Systems to Fuel Segmental Growth

Based on application, the autonomous driving segment is projected to hold a decent market share during the forecast period. The advent of the most popular vehicles with driving assist or autonomous control is fuelling segmental growth. To put it another way, autonomous driving parameters are determined by the level of control given to the AI. Technology companies and automakers are developing advanced AI systems, especially for driverless vehicles. Lidar, cameras, ultrasound sensors, and radar are a few of the sensors that self-driving cars use to collect data about their surroundings. AI algorithms then use that data to create detailed maps of the environment and make decisions.

For instance, in October 2023, oToBrite Electronics Inc. launched a comprehensive ADAS product portfolio for heavy commercial vehicles to help road safety towards vision zero. As heavy commercial vehicles (HTVs) are more likely to cause fatalities in vulnerable road user (VRU) collisions, the new European Union General Safety Regulation (GSR) has set high safety requirements.

Asia-Pacific Accelerates in Global Automotive AI Market

Based on region, Asia-Pacific is anticipated to thrive at an accelerated rate in the market. The growth is attributed to the record-breaking sales of advanced automobiles, and native brands launching new AI-based products, and systems. Furthermore, the higher adoption of electric vehicles along with the connected car technology is expected to fuel the demand for automotive artificial intelligence systems. The region's rapid growth is due to the increasing demand for luxury passenger cars, rising disposable income, and positive consumer sentiment towards artificial intelligence.

While Asia-Pacific grows at a faster rate, North America holds the largest share of the market due to the presence of major technological giants and automotive makers in the United States. The government supports innovative technology vendors along with auto giants like Tesla and Tata Motors. Rise in per capita income, cutting-edge automotive technology, and partnerships between vehicle manufacturers and AI tech providers are driving new market growth while boosting overall demand for AI in automotive solutions.

For instance, in January 2024, Intel Corporation announced that it is building an AI-enabled system-on-chip for next-generation cars. The company unveiled a new software-defined vehicle system-on-chip that is engineered to infuse AI properties into next-generation vehicles.

Future Market Scenario (2024 - 2031F)

Self-driving or autonomous vehicles are increasing the adoption of technologies like IoT and artificial intelligence in vehicles.

The advanced chip-based vehicle control systems for voice recognition and face recognition services are projected to transform the current market dynamic.

The advent of electric vehicles along with the higher demand for vehicles with higher ease and comfort is anticipated to expand the market size.

The human-machine interface (HMI), machine learning, and IoT (Internet of Things) are likely to reshape AI adoption in the automotive industry.

Key Players Landscape and Outlook

The competitive landscape for the automotive artificial intelligence market holds a mixture of major automotive OEMs and aftermarket companies. The key players focus on increasing the number of adopters along with building AI platforms that are more compatible and inclusive. Furthermore, the key players indulged in activities like partnerships, collaborations, and acquisitions to expand the market hold through strengthening of supply chain.

For instance, in January 2024, Cerence Inc. (CRNC) and Microsoft Corp. (MSFT) joined forces to improve in-car experiences by connecting Cerence's automotive technology to Microsoft's cloud-based AI services. The new partnership brings an automotive-grade implementation of OpenAI's ChatGPT Model, available through Microsoft's openAI service in cars.

In January 2024, Qualcomm Inc. announced its partnership with Bosch to produce system-on-chip, enabling AI in the form of the industry's first central vehicle computer. The system comes with the capability of running infotainment and an advanced driver assistance system. Qualcomm has been promoting the concept of a "digital chassis" as well.

Table of Contents

1.Research Methodology

2.Project Scope & Definitions

3.Executive Summary

4.Voice of Customer

• 4.1.Product and Market Intelligence
• 4.2.Mode of Brand Awareness
• 4.3.Factors Considered in Purchase Decisions
  • 4.3.1.Performance
  • 4.3.2.Accuracy and Reliability
  • 4.3.3.Integration with Other Systems
  • 4.3.4.Data Privacy and Security
  • 4.3.5.Regulatory Compliance
  • 4.3.6.Scalability and Upgradeability
• 4.4.Consideration of Privacy & Safety Regulations

5.Global Automotive Artificial Intelligence Market Outlook, 2017-2031F

• 5.1.Market Size & Forecast
  • 5.1.1.By Value
  • 5.1.2.By Volume
• 5.2.By Offering
  • 5.2.1.Hardware
  • 5.2.2.Software
• 5.3.By Process
  • 5.3.1.Signal Recognition
  • 5.3.2.Image Recognition
  • 5.3.3.Data Mining
• 5.4.By Technology
  • 5.4.1.Deep Learning
  • 5.4.2.Machine Learning
  • 5.4.3.Context-aware Computing
  • 5.4.4.Computer Vision
  • 5.4.5.Natural Language Processing
  • 5.4.6.Others
• 5.5.By Application
  • 5.5.1.Human-Machine Interface
  • 5.5.2.Semi-autonomous Driving
  • 5.5.3.Autonomous Driving
  • 5.5.4.Others
• 5.6.By Component
  • 5.6.1.Graphics Processing Unit (GPU)
  • 5.6.2.Microprocessors (Incl. ASIC)
  • 5.6.3.Image Sensors
  • 5.6.4.Field Programmable Gate Array (FPGA)
  • 5.6.5.Others
• 5.7.By Vehicle Type
  • 5.7.1.Passenger Vehicles
  • 5.7.2.Commercial Vehicles
• 5.8.By Region
  • 5.8.1.North America
  • 5.8.2.Europe
  • 5.8.3.Asia-Pacific
  • 5.8.4.South America
  • 5.8.5.Middle East and Africa
• 5.9.By Company Market Share (%), 2023

6.Global Automotive Artificial Intelligence Market Outlook, By Region, 2017-2031F

• 6.1.North America*
  • 6.1.1.Market Size & Forecast
    • 6.1.1.1.By Value
    • 6.1.1.2.By Volume
  • 6.1.2.By Offering
    • 6.1.2.1.Hardware
    • 6.1.2.2.Software
  • 6.1.3.By Process
    • 6.1.3.1.Signal Recognition
    • 6.1.3.2.Image Recognition
    • 6.1.3.3.Data Mining
  • 6.1.4.By Technology
    • 6.1.4.1.Deep Learning
    • 6.1.4.2.Machine Learning
    • 6.1.4.3.Context-aware Computing
    • 6.1.4.4.Computer Vision
    • 6.1.4.5.Natural Language Processing
    • 6.1.4.6.Others
  • 6.1.5.By Application
    • 6.1.5.1.Human-Machine Interface
    • 6.1.5.2.Semi-autonomous Driving
    • 6.1.5.3.Autonomous Driving
    • 6.1.5.4.Others
  • 6.1.6.By Component
    • 6.1.6.1.Graphics Processing Unit (GPU)
    • 6.1.6.2.Microprocessors (Incl. ASIC)
    • 6.1.6.3.Image Sensors
    • 6.1.6.4.Field Programmable Gate Array (FPGA)
    • 6.1.6.5.Others
  • 6.1.7.By Vehicle Type
    • 6.1.7.1.Passenger Vehicles
    • 6.1.7.2.Commercial Vehicles
  • 6.1.8.United States*
    • 6.1.8.1.Market Size & Forecast
    • 6.1.8.1.1.By Value
    • 6.1.8.1.2.By Volume
    • 6.1.8.2.By Offering
    • 6.1.8.2.1.Hardware
    • 6.1.8.2.2.Software
    • 6.1.8.3.By Process
    • 6.1.8.3.1.Signal Recognition
    • 6.1.8.3.2.Image Recognition
    • 6.1.8.3.3.Data Mining
    • 6.1.8.4.By Technology
    • 6.1.8.4.1.Deep Learning
    • 6.1.8.4.2.Machine Learning
    • 6.1.8.4.3.Context-aware Computing
    • 6.1.8.4.4.Computer Vision
    • 6.1.8.4.5.Natural Language Processing
    • 6.1.8.4.6.Others
    • 6.1.8.5.By Application
    • 6.1.8.5.1.Human-Machine Interface
    • 6.1.8.5.2.Semi-autonomous Driving
    • 6.1.8.5.3.Autonomous Driving
    • 6.1.8.5.4.Others
    • 6.1.8.6.By Component
    • 6.1.8.6.1.Graphics Processing Unit (GPU)
    • 6.1.8.6.2.Microprocessors (Incl. ASIC)
    • 6.1.8.6.3.Image Sensors
    • 6.1.8.6.4.Field Programmable Gate Array (FPGA)
    • 6.1.8.6.5.Others
    • 6.1.8.7.By Vehicle Type
    • 6.1.8.7.1.Passenger Vehicles
    • 6.1.8.7.2.Commercial Vehicles
  • 6.1.9.Canada
  • 6.1.10.Mexico

All segments will be provided for all regions and countries covered

• 6.2.Europe
  • 6.2.1.Germany
  • 6.2.2.France
  • 6.2.3.Italy
  • 6.2.4.United Kingdom
  • 6.2.5.Russia
  • 6.2.6.Netherlands
  • 6.2.7.Spain
  • 6.2.8.Turkey
  • 6.2.9.Poland
• 6.3.Asia-Pacific
  • 6.3.1.India
  • 6.3.2.China
  • 6.3.3.Japan
  • 6.3.4.Australia
  • 6.3.5.Vietnam
  • 6.3.6.South Korea
  • 6.3.7.Indonesia
  • 6.3.8.Philippines
• 6.4.South America
  • 6.4.1.Brazil
  • 6.4.2.Argentina
• 6.5.Middle East & Africa
  • 6.5.1.Saudi Arabia
  • 6.5.2.UAE
  • 6.5.3.South Africa

7.Market Mapping, 2023

• 7.1.By Offerings
• 7.2.By Process
• 7.3.By Technology
• 7.4.By Application
• 7.5.By Component
• 7.6.By Vehicle Type
• 7.7.By Region

8.Macro Environment and Industry Structure

• 8.1.Demand Supply Analysis
• 8.2.Import Export Analysis
• 8.3.Value Chain Analysis
• 8.4.PESTEL Analysis
  • 8.4.1.Political Factors
  • 8.4.2.Economic System
  • 8.4.3.Social Implications
  • 8.4.4.Technological Advancements
  • 8.4.5.Environmental Impacts
  • 8.4.6.Legal Compliances and Regulatory Policies (Statutory Bodies Included)
• 8.5.Porter's Five Forces Analysis
  • 8.5.1.Supplier Power
  • 8.5.2.Buyer Power
  • 8.5.3.Substitution Threat
  • 8.5.4.Threat from New Entrants
  • 8.5.5.Competitive Rivalry

9.Market Dynamics

• 9.1.Growth Drivers
• 9.2.Growth Inhibitors (Challenges and Restraints)

10.Key Players Landscape

• 10.1.Competition Matrix of Top Five Market Leaders
• 10.2.Market Revenue Analysis of Top Five Market Leaders (in %, 2023)
• 10.3.Mergers and Acquisitions/Joint Ventures (If Applicable)
• 10.4.SWOT Analysis (For Five Market Players)
• 10.5.Patent Analysis (If Applicable)

11.Case Studies

12.Key Players Outlook

• 12.1.Nvidia Corporation
  • 12.1.1.Company Details
  • 12.1.2.Key Management Personnel
  • 12.1.3.Products & Services
  • 12.1.4.Financials (As reported)
  • 12.1.5.Key Market Focus & Geographical Presence
  • 12.1.6.Recent Developments
• 12.2.Alphabet Inc.
• 12.3.Intel Corporation
• 12.4.Microsoft Corporation
• 12.5.IBM Corporation
• 12.6.Qualcomm Inc.
• 12.7.Tesla Inc.
• 12.8.BMW AG
• 12.9.Micron Technology Inc
• 12.10.Xilinx, Inc.
• 12.11.Arbe Robotics
• 12.12.Cerence, Inc.

Companies mentioned above DO NOT hold any order as per market share and can be changed as per information available during research work.

13.Strategic Recommendations

14.About Us & Disclaimer