Automotive Artificial Intelligence Market Forecasts to 2028 – Global Analysis By Technology (Computer Vision, Context-Aware Computing, Machine Learning & Deep Learning, Natural Language Processing (NLP)), Component, and By Geography

Automotive Artificial Intelligence Market Forecasts to 2028 – Global Analysis By Technology (Computer Vision, Context-Aware Computing, Machine Learning & Deep Learning, Natural Language Processing (NLP)), Component, and By Geography

According to Stratistics MRC, the Global Automotive Artificial Intelligence Market is accounted for $2.23 billion in 2021 and is expected to reach $22.05 billion by 2028 growing at a CAGR of 38.7% during the forecast period. Artificial intelligence is becoming a dynamic business norm. It is associated with human intelligence through similar characteristics such as language understanding, reasoning, learning, problem solving, and others. The rising adoption of automotive artificial intelligence is routing in a new era allowing the companies to track their operations, enhance in-car user experience, augment business strategies, provide a better outcome in the digital world, and develop autonomous and semi-autonomous vehicles.

Market Dynamics:

Driver:

Growing technological advancements

Considering the largest auto companies investing extensively in artificial intelligence for autos, industry-wide standards like navigation systems, sophisticated automated driving, and blind-spot alerts are expected to further fuel market expansion. Automotive vehicle provides many features such as adaptive cruise control, automatic emergency braking, automatic parking, lane departure warning systems, and adaptive headlights. With technological enhancements, the number of such features is continuously expanding. Automotive manufacturers are aggressively working towards incorporating advanced technologies in their vehicles for enhancing the user experience.

Restraint:

Lack of AI expertise

A lack of AI expertise is another big drawback in the auto and other industries, a skills gap that is not likely to be remedied anytime soon. The problem-solving inference phase also has drawbacks. Large models, especially for AVs, require tremendous computing resources to crunch sensor data and support complex software. Those resources also require power, which is always limited in auto applications. Emerging technologies will improve capabilities and reduce inferencing costs, including emerging AI chip technology, declining LIDAR prices and increased sensor performance.

Opportunity:

Rising demand for autonomous vehicles

As the adoption of artificial intelligence in autonomous vehicles progresses from needing driver assistance to having full autonomy, enhanced user experience and convenience features, driverless cars are becoming a reality. Autonomous vehicles are called driverless vehicles or self-driven that use artificial intelligence (AI) software, light detection & ranging (LiDAR), RADAR, computer vision, GPS sensing technology and sensors to operate without any human interference. The increasing government focus on streamlined traffic infrastructure and regulations, growing demand for a reliable transportation system, and availability of advanced technologies relevant for the automotive industry are driving the demand for autonomous and semi-autonomous vehicles.

Threat:

Rising privacy and security concerns

The autonomous vehicles have made life of consumers convenient and safe. On the other hand, there are certain threats that are faced by the manufacturers related to privacy and security concerns such as cyber-attacks, safety of personal data, and driver distractions. For instance, around 1.4 million Fiat Chryslers were recalled in the US due to a glitch in their dashboard computers that permitted hackers to disable the vehicle. In the similar manner, white hat hackers were successful in implanting malware into the system of a Tesla car. These instances of intruding customer’s privacy are some of the major threats for the global market.

The software segment is expected to be the largest during the forecast period

The software segment is estimated to have a lucrative growth due to the advanced technologies emerging in the market and necessity to upgrade systems in order to streamline processes and operations within the automotive industry. Moreover, the gradually decreasing deployment cost of cloud-based software solutions along with a rising need to connect multiple data points for seamless integration of processes will result in software segment emerging as the major shareholder in terms of components.

The computer vision segment is expected to have the highest CAGR during the forecast period

The computer vision segment is anticipated to witness the fastest CAGR growth during the forecast period. Most of the companies across the globe have started to adopt image recognition as one of the artificial intelligence-based solutions in autonomous or semi-autonomous applications which is anticipated to reshape their business. This is mainly attributed to the soaring labor cost, widening the implementation scope of computer vision in autonomous vehicles for signal recognition, driver monitoring and increase in automation for carrying out core operations.

Region with highest share:

North America is projected to hold the largest market share during the forecast period due to the existence of significant manufacturers in this region. The increasing expectation of autonomous cars in the United States has made a substantial contribution to the expansion of the industry in this country. Moreover, as compared to other regions, this area has considerably greater accessibility of advanced technology to develop artificial intelligence systems. Favorable government regulations, combined with the fact that the automotive industry's leading companies, such as Ford Motor Company, Fiat Chrysler Automotive, and General Motors are taking a stand in the advancement of artificial intelligence in automobiles by continuously enhancing their products, will have a better prospect in the global market.

Region with highest CAGR:

Asia Pacific is projected to have the highest CAGR over the forecast period due to the rising government initiatives, an increase in demand for premium vehicles, rising investments in AI technology for improved productivity, and adoption of AI-based solutions and services among autonomous and semi-autonomous applications. For instance, the South Korean government plans to expand the country’s production of automation systems and industrial robotics with investments into significant resources worth $6.15 billion. Several other instances similar to the aforementioned ones are indicating lucrative growth of the automotive artificial intelligence market in the region. In addition, developing internet and connectivity infrastructure, growing adoption of intelligent based solutions for automating operations and increasing digitalization are also augmenting the market growth in the Asia Pacific region.

Key players in the market

Some of the key players profiled in the Automotive Artificial Intelligence Market include Audi AG, BMW, Didi Chuxing, Ford Motor Company, General Motors Company, Honda Motor Co., Ltd, IBM Corporation, Intel Corporation, Micron Technology, Microsoft Corporation, NVIDIA Corporation, Otto Motors, Qualcomm Technologies, Inc, Tesla Inc, Toyota, Waymo, and Xilinx, Inc.

Key Developments:

In May 2021, Didi Chuxing has announced a strategic partnership with Volvo Cars on self-driving vehicles for DiDi's test fleet. Volvo Cars' autonomous drive-ready XC90 vehicles will be the first to feature DiDi Gemini, a new self-driving hardware platform outfitted with NVIDIA DRIVE AGX Pegasus. These vehicles, which are outfitted with DiDi's Gemini self-driving hardware platform, will eventually be used in robotaxi services.

In June 2020, Waymo and the Volvo Cars Group agreed to collaborate on the development of a self-driving electric vehicle for ride hailing as part of a new global cooperation. Waymo will concentrate on artificial intelligence and specific technology, like cameras, lidar, and radar, for the autonomous “driver.” Volvo will design and construct the automobiles.

Technologies Covered:
• Computer Vision
• Context-Aware Computing
• Machine Learning & Deep Learning
• Natural Language Processing (NLP)

Components Covered:
• Hardware
• Software
• Services

Processes Covered:
• Data Mining
• Image Recognition
• Signal Recognition
• Voice Recognition

Applications Covered:
• Autonomous
• Semi-Autonomous Driving
• Human Machine Interface

Regions Covered:
• North America
US
Canada
Mexico
• Europe
Germany
UK
Italy
France
Spain
Rest of Europe
• Asia Pacific
Japan
China
India
Australia
New Zealand
South Korea
Rest of Asia Pacific
• South America
Argentina
Brazil
Chile
Rest of South America
• Middle East & Africa
Saudi Arabia
UAE
Qatar
South Africa
Rest of Middle East & Africa

What our report offers:
- Market share assessments for the regional and country-level segments
- Strategic recommendations for the new entrants
- Covers Market data for the years 2020, 2021, 2022, 2025, and 2028
- Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
- Strategic recommendations in key business segments based on the market estimations
- Competitive landscaping mapping the key common trends
- Company profiling with detailed strategies, financials, and recent developments
- Supply chain trends mapping the latest technological advancements

Free Customization Offerings:
All the customers of this report will be entitled to receive one of the following free customization options:
• Company Profiling
Comprehensive profiling of additional market players (up to 3)
SWOT Analysis of key players (up to 3)
• Regional Segmentation
Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
• Competitive Benchmarking
Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances