Artificial Intelligence in Automotive
SKU
MRR-4355714631D8
Region
Global
Publication Date
March 2024
Delivery
Immediate
2023
USD 4.85 billion
2030
USD 25.87 billion
2024
USD 6.11 billion
CAGR
26.98%
Artificial Intelligence in Automotive Market by Offerings (Hardware, Software), Technology (Computer Vision, Context Awareness, Deep Learning), Process, Functionality, Application - Global Forecast 2024-2030

[195 Pages Report] The Artificial Intelligence in Automotive Market size was estimated at USD 4.85 billion in 2023 and expected to reach USD 6.11 billion in 2024, at a CAGR 26.98% to reach USD 25.87 billion by 2030.

Artificial Intelligence in Automotive Market
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Automotive artificial intelligence (AI) uses AI technology to develop intelligent vehicle systems. These AI systems empower vehicles with advanced capabilities, such as autonomous driving, safety features, and smart connectivity. It facilitates the development of self-driving cars, automated fleet management, advanced safety features, and intuitive user interfaces. One of the most significant advancements in this domain is the introduction of AI-powered automotive cockpits. These advanced systems serve various functions that enhance both driver and passenger experiences. AI automotive cockpit integrates voice-activated assistants and advanced driver assistance systems (ADAS) to help drivers interact with their vehicles without taking their hands off the wheel or eyes off the road, significantly improving safety while offering convenience. Artificial intelligence's application in the automotive industry has significantly impacted the construction of in-vehicle user experience and security, resulting in a growing demand for AI technology within the automotive sector. Government regulations, the adoption of ADAS, and the increasing preference for autonomous vehicles have further fueled the implementation of AI in the automotive space. While there are growth opportunities, particularly in the premium segment cars, the cybersecurity concerns associated with AI-enabled vehicles pose a significant challenge in the market. Moreover, the development of advanced AI platforms for autonomous driving is expected to create a lucrative market o[opportunity in the forecasted period.

Artificial Intelligence in Automotive Market - Global Forecast 2024-2030
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Offerings: Significant adoption of software platforms owing to their versatile, scalable, and user-friendly interfaces

Neuromorphic Architecture mimics neuro-biological architectures using very-large-scale integration (VLSI) systems. Known for low-power consumption and rapid processing capabilities, it endows AI with enhanced machine learning and decision-making capabilities, thus making it a vital component in developing autonomous vehicles and advanced driver-assistance systems (ADAS). Von Neumann architecture is quintessential in computers and AI systems. It utilizes a single bus to carry out data and instructions, thus facilitating speed and efficiency in AI-based automotive computations. Despite being relatively older, Von Neumann's Architecture is famed for its simplicity, scale, and flexibility and is often used in modern AI applications such as ADAS and connected cars. Platforms offer robust tools and libraries for designing, training and validating deep learning models. Platforms provide versatile, scalable, and user-friendly interfaces that streamline the implementation of AI in diverse automotive applications, from navigation systems to predictive maintenance. AI-based solutions are tailored to address specific industry challenges. For instance, machine learning algorithms are able to detect patterns and anomalies, predict vehicle health, or automate driving functions, thereby enhancing vehicle safety, efficiency, and user experience.

Technology: Growing utilization of Deep Learning technology as it helps vehicles learn complex patterns and adapt to dynamic environments

Computer Vision equips vehicles with the capability to interpret their surrounding environment. Image processing techniques enable vehicles to identify and categorize objects such as pedestrians, traffic signals, and other vehicles. It enhances safety by contributing to features such as traffic sign recognition, adaptive cruise control systems, and lane departure warnings, making vehicles smarter and safer. Context Awareness in automotive AI refers to the vehicle's ability to perceive and react to its driving context - including other cars, terrain, weather conditions, and driver behavior. It aims to facilitate adaptive, and thus safer, driving. Using sensors, radars, and real-time data, context awareness promotes more intelligent decision-making, improving overall driving experience and vehicle performance. Context Awareness in automotive AI refers to the vehicle's ability to perceive and react to its driving context, including other cars, terrain, weather conditions, and driver behavior. It aims to facilitate adaptive, and thus safer, driving. With sensors, radars, and real-time data, context awareness promotes more intelligent decision-making, improving the overall driving experience and vehicle performance. Deep Learning plays a pivotal role in refining automotive AI. By leveraging neural networks, it helps vehicles learn complex patterns, adapt to dynamic environments, and make real-time decisions. Applications include predictive vehicle maintenance, optimized energy consumption, proactive safety features, and, most notably, enabling autonomous driving capabilities. Machine Learning is the backbone of Automotive AI, creating systems that learn, adapt, and improve over time. These technologies are employed to predict and understand user behavior, optimize efficiency, and react to unexpected situations. In addition, Machine Learning serves as the engine behind autonomous vehicles - enabling the technology to respond appropriately to the ever-changing conditions on the road. Natural Language Processing (NLP) brings new levels of interaction between vehicles and drivers. NLP enables the car to comprehend and generate human language, facilitating voice-controlled functionalities. It supports navigation, calls, and infotainment commands and allows for hands-free operations, ensuring a safer and enjoyable driving experience.

Process: Increasing preference for data mining process for enhancing streamlining of design and manufacturing processes

Data mining is a pivotal technique employed in the automotive sector to harness the potential of Artificial Intelligence (AI). In this context, data mining refers to the drawing and analysis of substantial volumes of data from diverse sources to generate relevant insights and identify patterns. These patterns are then used to make informed decisions, fostering significant operational efficiency across the entire automotive value chain. Image recognition technology is presently deployed in systems such as Advanced Driver Assistance Systems (ADAS) and autonomous vehicles, offering object detection, lane recognition, and navigation aid features. By processing and interpreting images, these systems become capable of perceiving the vehicle's surroundings better and reacting accordingly, enhancing driver safety and reducing the risks of road accidents. Signal recognition plays a fundamental role in improving the AI-driven capabilities of vehicles. It involves the analysis of different signals, such as audio, visual, and radar, to interpret and respond to various situations. In autonomous vehicles, signal recognition technology is used to process LiDAR and radar data to understand the vehicle's environment better.

Application: Evolving usage of AI in Automotive is in Human–Machine Interface as it gives personalized suggestions based on the driver's habits and preferences

In the context of autonomous vehicles, AI algorithms, combined with sensors and HD map information, enable a vehicle to navigate, change lanes, park, and adjust its speed based on real-time traffic conditions, all without human intervention. AI also facilitates predictive maintenance by identifying mechanical problems before they occur, increasing the vehicle's lifespan. Human-machine interface (HMI) in the automotive industry has evolved from mere physical controls to advanced touchscreen and voice-controlled mechanisms. AI enables natural language understanding, speech recognition, and gesture control, providing a seamless interaction between the user and the vehicle. This AI-driven evolution assists in managing everything from temperature controls and infotainment systems to personalized suggestions based on the driver's habits and preferences. Furthermore, AI-powered face recognition systems can monitor drivers' alertness levels, thereby enhancing driver safety. AI plays a crucial role in semi-autonomous vehicles, offering features including adaptive cruise control and lane departure warnings. Drivers can rely on the car to perform specific tasks while remaining in control. Using AI, the vehicle can gather data from various sensors to understand its environment and then take appropriate actions such as adjusting speed or issuing warning signals. This ensures a safer, smoother, and more efficient driving experience.

Regional Insights

The Americas has a significant landscape in artificial intelligence in the automotive market owing to the increasing development of autonomous technology and the presence of several tech giants and automotive companies investing heavily in AI research and development. Europe has a robust automotive industry with established automakers and suppliers actively exploring AI applications. Technological advancements in the automotive industry by key market vendors have accelerated the market demand in the region. Europe has well-defined regulations and standards for AI applications and autonomous vehicles in the automotive sector. Clear guidelines and support from regulatory bodies create a conducive environment for AI adoption, fostering the demand for AI-driven automotive technologies in Europe. APAC has a growing landscape in artificial intelligence in the automotive market due to the large and fast-growing automotive manufacturing hub and significant demand for smart and connected vehicles, which fuels the adoption of AI technologies in the automotive sector in the region.

FPNV Positioning Matrix

The FPNV Positioning Matrix is pivotal in evaluating the Artificial Intelligence in Automotive Market. It offers a comprehensive assessment of vendors, examining key metrics related to Business Strategy and Product Satisfaction. This in-depth analysis empowers users to make well-informed decisions aligned with their requirements. Based on the evaluation, the vendors are then categorized into four distinct quadrants representing varying levels of success: Forefront (F), Pathfinder (P), Niche (N), or Vital (V).

Market Share Analysis

The Market Share Analysis is a comprehensive tool that provides an insightful and in-depth examination of the current state of vendors in the Artificial Intelligence in Automotive Market. By meticulously comparing and analyzing vendor contributions in terms of overall revenue, customer base, and other key metrics, we can offer companies a greater understanding of their performance and the challenges they face when competing for market share. Additionally, this analysis provides valuable insights into the competitive nature of the sector, including factors such as accumulation, fragmentation dominance, and amalgamation traits observed over the base year period studied. With this expanded level of detail, vendors can make more informed decisions and devise effective strategies to gain a competitive edge in the market.

Recent Developments
  • AI-based self-driving tech start-up Minus Zero unveils India’s first fully autonomous vehicle

    Minus Zero, a Bengaluru-based AI start-up, recently unveiled zPod, India's first-ever autonomous vehicle. This fully electric prototype is equipped with an advanced camera-sensor suite, enabling it to operate in diverse environmental and geographical conditions with Level 5 autonomy capabilities. [Published On: 2023-06-04]

  • Ford launches automated driving unit Latitude AI months after winding down Argo

    Ford Motor Co recently established a subsidiary called Latitude AI, specializing in automated driving systems. Latitude AI aims to enhance Ford's existing BlueCruise technology, enabling hands-free highway driving in select models. [Published On: 2023-03-02]

  • XPENG launches AI platform for autonomous driving and robot features

    XPeng's unveiled its next-generation neural network-based perception architecture, XNet, at its fourth annual Tech Day in Guangzhou. This event showcased various cutting-edge technologies, including data management platforms, closed-loop AI, voice and smart cabin technologies, and the latest advancements in their mobility ecosystem, including the latest robotaxi, flying cars, and robotics projects. [Published On: 2022-10-26]

Key Company Profiles

The report delves into recent significant developments in the Artificial Intelligence in Automotive Market, highlighting leading vendors and their innovative profiles. These include Advanced Micro Devices, Inc., Alphabet Inc., Aptiv PLC, Audi AG, Baidu Inc., Bayerische Motoren Werke AG, Continental AG, General Motors Company, Harman International Industries, Inc., Honda Motor Co., Ltd., Intel Corporation, International Business Machines Corporation, Mercedes-Benz Group AG, Micron Technology, Inc., Microsoft Corporation, NVIDIA Corporation, Optimus Ride, Qualcomm Inc., Rivian Automotive, Inc.,, Robert Bosch GmbH, Tesla, Inc., TomTom, Toyota Motor Corporation, Velodyne Lidar Inc., Volkswagen AG, Volvo Car Corporation, and Xpeng Inc..

Market Segmentation & Coverage

This research report categorizes the Artificial Intelligence in Automotive Market to forecast the revenues and analyze trends in each of the following sub-markets:

  • Offerings
    • Hardware
      • Neuromorphic Architecture
      • Von Neumann Architecture
    • Software
      • Platforms
      • Solutions
  • Technology
    • Computer Vision
    • Context Awareness
    • Deep Learning
    • Machine Learning
    • Natural Language Processing
  • Process
    • Data Mining
    • Image Recognition
    • Signal Recognition
  • Functionality
    • Adaptive Climate Control
    • Advanced Driver Assistance Systems (ADAS)
    • Full-Cabin Monitoring
    • Gesture Control
    • Predictive Maintenance Alerts
    • Vehicle Occupancy Detection
    • Voice Recognition
  • Application
    • Autonomous Vehicle
    • Human–Machine Interface
    • Semi-Autonomous Driving

  • Region
    • Americas
      • Argentina
      • Brazil
      • Canada
      • Mexico
      • United States
        • California
        • Florida
        • Illinois
        • New York
        • Ohio
        • Pennsylvania
        • Texas
    • Asia-Pacific
      • Australia
      • China
      • India
      • Indonesia
      • Japan
      • Malaysia
      • Philippines
      • Singapore
      • South Korea
      • Taiwan
      • Thailand
      • Vietnam
    • Europe, Middle East & Africa
      • Denmark
      • Egypt
      • Finland
      • France
      • Germany
      • Israel
      • Italy
      • Netherlands
      • Nigeria
      • Norway
      • Poland
      • Qatar
      • Russia
      • Saudi Arabia
      • South Africa
      • Spain
      • Sweden
      • Switzerland
      • Turkey
      • United Arab Emirates
      • United Kingdom

The report offers valuable insights on the following aspects:

  1. Market Penetration: It presents comprehensive information on the market provided by key players.
  2. Market Development: It delves deep into lucrative emerging markets and analyzes the penetration across mature market segments.
  3. Market Diversification: It provides detailed information on new product launches, untapped geographic regions, recent developments, and investments.
  4. Competitive Assessment & Intelligence: It conducts an exhaustive assessment of market shares, strategies, products, certifications, regulatory approvals, patent landscape, and manufacturing capabilities of the leading players.
  5. Product Development & Innovation: It offers intelligent insights on future technologies, R&D activities, and breakthrough product developments.

The report addresses key questions such as:

  1. What is the market size and forecast of the Artificial Intelligence in Automotive Market?
  2. Which products, segments, applications, and areas should one consider investing in over the forecast period in the Artificial Intelligence in Automotive Market?
  3. What are the technology trends and regulatory frameworks in the Artificial Intelligence in Automotive Market?
  4. What is the market share of the leading vendors in the Artificial Intelligence in Automotive Market?
  5. Which modes and strategic moves are suitable for entering the Artificial Intelligence in Automotive Market?

Table of Contents
  1. Preface
  2. Research Methodology
  3. Executive Summary
  4. Market Overview
  5. Market Insights
  6. Artificial Intelligence in Automotive Market, by Offerings
  7. Artificial Intelligence in Automotive Market, by Technology
  8. Artificial Intelligence in Automotive Market, by Process
  9. Artificial Intelligence in Automotive Market, by Functionality
  10. Artificial Intelligence in Automotive Market, by Application
  11. Americas Artificial Intelligence in Automotive Market
  12. Asia-Pacific Artificial Intelligence in Automotive Market
  13. Europe, Middle East & Africa Artificial Intelligence in Automotive Market
  14. Competitive Landscape
  15. Competitive Portfolio
Companies Mentioned
  • Advanced Micro Devices, Inc.
  • Alphabet Inc.
  • Aptiv PLC
  • Audi AG
  • Baidu Inc.
  • Bayerische Motoren Werke AG
  • Continental AG
  • General Motors Company
  • Harman International Industries, Inc.
  • Honda Motor Co., Ltd.
  • Intel Corporation
  • International Business Machines Corporation
  • Mercedes-Benz Group AG
  • Micron Technology, Inc.
  • Microsoft Corporation
  • NVIDIA Corporation
  • Optimus Ride
  • Qualcomm Inc.
  • Rivian Automotive, Inc.,
  • Robert Bosch GmbH
  • Tesla, Inc.
  • TomTom
  • Toyota Motor Corporation
  • Velodyne Lidar Inc.
  • Volkswagen AG
  • Volvo Car Corporation
  • Xpeng Inc.
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Frequently Asked Questions about the Artificial Intelligence in Automotive Market
The Global Artificial Intelligence in Automotive Market size was estimated at USD 4.85 billion in 2023 and expected to reach USD 6.11 billion in 2024.
The Global Artificial Intelligence in Automotive Market to grow USD 25.87 billion by 2030, at a CAGR of 26.98%
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