Automotive Artificial Intelligence Market Size, Share & Trends Analysis Report By Component, By Level Of Autonomy (Level 1, Level 2, Level 3, Level 4), By Technology, By Vehicle Type, By Region, And Segment Forecasts, 2022 - 2030

Report Overview

The global automotive artificial intelligence market size was valued at USD 2.54 billion in 2021 and is expected to expand at a compound annual growth rate (CAGR) of 21.6% from 2022 to 2030. Introducing (Artificial Intelligence) AI in the automotive industry ushers in a new era, allowing businesses to track operations, improve business plans, develop autonomous and semi-autonomous vehicles, and enhance digital outcomes. The global automotive AI industry is driven by the rising demand for autonomous vehicles, the adoption of artificial intelligence for traffic management, advanced automotive solutions, and government initiatives. Nevertheless, the absence of infrastructure, expensive procurement, and operational expenses remain obstacles to growth.

Artificial intelligence is projected to disrupt the automobile sector by streamlining production capacities and increasing corporate growth. Developing and deploying novel technologies such as autonomous mobility, rapid prototyping, vehicle simulations, and AI-enabled automotive factories boost the market for autonomous technology. Automakers rapidly modernize their existing production systems by incorporating AI platforms. Companies continue to increase their focus on developing self-driving vehicles to increase passenger mobility.

AI in automotive has gained traction in recent years. AI improves customer experience through conversational interfaces and personalized recommendations based on preferences. Additionally, it is used to expand the capabilities of existing technologies such as voice assistants by allowing them to understand what you need and provide you with relevant information. For instance, in June 2022, Hailo, an AI chipmaker, partnered with Renesas to seamlessly enable automotive customers to transition from ADAS to automated driving. With the collaboration between Hailo and Renesas, sophisticated ADAS technology will be more accessible to vehicles of all types.

COVID-19 hastened the implementation of artificial intelligence in critical industries, particularly the automotive industry. AI is applied efficiently throughout the automotive value chain, including post-production, manufacturing, supply chain, design, production, driver assistance, and risk assessment systems. Although market players have witnessed relatively low sales volume during the first year of the pandemic, the market is gradually gaining traction. The COVID-19 pandemic has compelled automakers to reconsider their short-term strategy for redefining automation.

Component Insights

The hardware segment held the largest revenue share of over 76% in 2021. Hardware and software constitute the component section. Automotive AI systems on chip (SoCs) are more heterogeneous than other edge devices' SoCs due to the intimate coupling between the chip hardware. Furthermore, ADAS or autonomous driving runtime software and the employment of specialized processing element types speed up specific algorithmic steps. The ongoing trend of AI adoption in the automotive industry will drive market growth in the coming years.

AI and machine learning work together in the automotive sector to develop algorithms that analyze traffic situations, make quick decisions, and learn from other participants. Adapting technology to quickly changing conditions and reducing the human factor in auto accidents is challenging for automotive software developers. Top car firms increasingly compete based on ML and AI software for autonomous vehicles. Increasingly, Tier 1 vendors and OEMs are working with IT services providers to meet their engineering needs. Self-driving and autonomous vehicles are still in the development phase. Working prototypes from many OEMs are being tested in various areas. Lyft, Uber, Ford, Toyota, Honda, and Tesla are a few players vying to be the pioneer in the market with entirely autonomous vehicles.

Level of Autonomy Insights

The level 2 segment represented the highest revenue share of over 48% in 2021. Advanced Driving Assistance Systems (ADAS) in level 2 vehicles can take over acceleration, steering, and braking under specific circumstances. Several automated systems work in sync with others during more complex driving tasks, but a human driver must always intervene if the car encounters a problem it cannot resolve. Semi-autonomous vehicles provide a pragmatic, rapid solution to the requirement for on-demand mobility. In addition to being sustainable, autonomous, and convenient, semi-autonomous cars are safer and easier to manage than completely automated vehicles. Therefore, safety concerns drive the segment’s growth.

The fully autonomous segment will witness a lower CAGR over the forecast period. Self-driving or fully autonomous cars are undergoing tests for safety-related issues and require some time to gain a foothold in the market with users' trust. Market players are embracing partnerships and acquisitions to drive the developments in autonomous cars. For instance, in March 2022 Jaguar Land Rover partnered with Nvidia to integrate advanced autonomous functionality and connectivity in all cars launched by Jaguar Land Rover by 2025. The cars launched by Jaguar Land Rover have level 3 autonomous capability.

Vehicle Type Insights

The passenger vehicles segment made up over 85% of the automotive Artificial Intelligence (AI) market in 2021. Currently, passenger vehicles constitute a significant share of the market as the adoption of AI in commercial vehicles increases. Passenger vehicles such as cars as well as motorcycles have implemented AI integration. For instance, in December 2020, Kawasaki began developing motorcycles with hybrid and AI assistant technology. Such significant developments are likely to fuel the growth.

Integrating deep neural networks, machine learning, and computer vision open up new possibilities for addressing many functions associated with commercial vehicle operations. Due to advances in sensor technology and artificial intelligence (AI), automated vehicles can analyze several objects on the road and determine how to respond. For instance, International Road Dynamics Inc. investigates several methods of applying artificial intelligence to commercial vehicle operations. The goals are to increase commercial vehicle fleet and freight movement safety and efficiency.

Technology Insights

Machine learning held the highest revenue share of over 36% in 2021. Machine learning for automotive, AI automotive algorithms, and artificial neural networks assist intelligent vehicles in gauging road conditions better than human drivers.  Intellias, an AI solution provider from the U.S., developed a Human-machine Interface (HMI) solution for the automotive industry. In addition to offering technical support to OEMs and automotive AI solution providers, it analyzes human behavior patterns to make data-driven decisions on the road based on road signs. A machine learning algorithm for automobiles can predict travel times, traffic congestion, and even vehicle breakdowns based on historical and real-time data.

The computer vision segment of AI in the automotive market is expected to grow at the highest CAGR by the end of 2030. Computer vision, often known as machine vision, is an AI-based technology. This technique collects valuable data from photos using machine learning algorithms and acts as the vehicle's eye. Additionally, computer vision is also used to inspect details during automotive production. The segment’s rapid growth can be credited to the mentioned functionality.

Regional Insights

North America had the highest revenue share of above 38% in 2021. Over the forecast period, the region is expected to maintain its most significant industry share. It can be credited to the early adoption of technology such as artificial intelligence and analytics. The region will continue to witness growth owing to the increased hiring in AI roles in the automotive industry. Furthermore, North America has long been a leader in the automated vehicle sector, and the west coast of the U.S tech centers have been a significant source of its contributions to self-driving technology. The U.S. is leading the race to make autonomous vehicles safe, with companies such as Uber and Tesla increasingly gaining limelight with their successes and mishaps.

Asia Pacific is expected to witness a CAGR of more than 24.3% during the forecast period. The region's rapid rise can be attributed to growing sales of premium passenger automobiles, increasing disposable income, and a positive consumer opinion of AI. Singapore topped KPMG's Autonomous Vehicles Readiness Index in 2020, demonstrating the state's support for using automated vehicles through public acceptance, policy, and regulation. Additionally, the Japanese government has revealed plans to have highly automated vehicles operating in specified areas by 2022.

Key Companies & Market Share Insights

Automotive AI competitors focus on innovation and product portfolio upgrades to achieve a competitive advantage. For instance, in June 2022, Li Auto L9 and NVIDIA's Drive Orin introduced luxury SUVs with intelligent driving technology. Vehicles from Li Auto are equipped with the company's advanced driver assistance system, Li AD Max. In addition to DRIVE Orin SoCs, the system uses 11 cameras, forward-facing LIDAR, radar, and 12 ultrasonic sensors.

Acquiring new companies and integrating them backward is strategy companies use to cut costs and increase performance. For instance, in July 2022, Michelin acquired RoadBotics, an American startup leveraging artificial intelligence for visual data analysis. The acquisition will help Michelin continue providing the data-driven solutions and services offered by MICHELIN DDi (Driven Data to Intelligence). RoadBotics' computer vision capabilities, paired with Michelin's DDi, will deliver unique insights on near-miss root causes based on driving behavior. Some prominent players in the global automotive Artificial Intelligence market include:

• Alphabet Inc.

• Intel Corporation

• Microsoft Corporation

• NVIDIA Corporation

• International Business Machines Corporation

• Qualcomm Inc.

• Tesla, Inc.

• Volvo Car Corporation

• Bayerische Motoren Werke AG

• Audi AG

Automotive Artificial Intelligence Market Report Scope

Global Automotive Artificial Intelligence Market Segmentation

This report forecasts revenue growth at global, regional, and country levels and provides an analysis of the latest industry trends in each of the sub-segments from 2017 to 2030. For this study, Grand View Research has segmented the global automotive Artificial Intelligence (AI) market report based on component, level of autonomy, technology, vehicle type, and region:

• Component Outlook (Revenue, USD Million, 2017 - 2030)

  • Hardware

  • Software

• Level of Autonomy Outlook (Revenue, USD Million, 2017 - 2030)

  • Level 1

  • Level 2

  • Level 3

  • Level 4

• Technology Outlook (Revenue, USD Million, 2017 - 2030)

  • Machine Learning

  • Natural Language Processing

  • Computer Vision

  • Context-aware Computing

  • Others

• Vehicle Type Outlook (Revenue, USD Million, 2017 - 2030)

  • Passenger Vehicles

  • Commercial Vehicles

• Region Outlook (Revenue, USD Million; 2017 - 2030)

  • North America

    • U.S.

    • Canada

    • Mexico

  • Europe

    • U.K.

    • Germany

    • France

  • Asia Pacific

    • China

    • India

    • Japan

  • Central and South America

    • Brazil

  • Middle East & Africa