Artificial Intelligence (AI) in Automotive Market to 2026 - Demand, Growth, Revenues Analysis by Leading Players

The hardware segment held majority of the Artificial Intelligence (AI) in Automotive market with over 60% share in 2019 and is expected to continue its dominance over the forecast timespan. This is attributed to the increasing adoption of automotive AI components for implementation of AI solutions. Energy-efficient System-on-Chips (SoCs) and dedicated AI GPUs are assisting enterprises in deploying highly sophisticated onboard computers with robust computing power. In July 2019, Intel launched Pohoiki Beach, a new AI-enabled chip, which features 8 million neural networks and can reach up to 10,000 times faster computing speeds compared to traditional CPUs. Furthermore, the growing uptake of sensors including high-resolution cameras, LiDARs, and ultrasonic sensors for vehicle situational awareness is fueling the growth of AI hardware.

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Artificial Intelligence (AI) in Automotive market is projected to surpass USD 12 billion by 2026.

Artificial Intelligence (AI) in Automotive market growth is attributed to the steadily growing uptake of driver assistance technologies for increasing driving comfort and ensuring safe driving experience. Consumers are increasingly exhibiting a positive attitude toward AI-powered vehicle driving systems, creating new avenues for market growth.

Europe held majority of the Artificial Intelligence (AI) in Automotive market with over 35% share in 2019 due to the growing demand for autonomous technologies in the region. Presence of several industry leaders including BMW, Audi, Mercedes, Daimler, and Bentley accelerated the advancements in autonomous mobility including several successful trial runs of level-5 autonomous vehicles. The increasing focus of automotive manufacturers on AI technologies, especially in Germany and the UK is driving the adoption of AI across the Europe automotive sector. Supportive initiatives from the government to adopt AI for smart traffic control has propelled the development of automotive AI solutions. In 2017, the UK government invested more than USD 75 million for the development of AI solutions and improved mobility.

Supporting initiatives from various governments to incorporate semi-autonomous vehicle technologies by 2022 will positively impact Artificial Intelligence (AI) in Automotive market growth. Major automotive manufacturers, such as Chrysler, Audi, and Ford, have started integrating semi-autopilot and drive cruise control technologies into their latest models. Driver behavior monitoring, road condition awareness, and lane tracking are a few of the innovative solutions that have been introduced through the implementation of AI technologies in semi-autonomous vehicles.

Automotive market with over 65% share in 2019 due to the growing importance of vehicle speed control for reducing on-road accidents. Image/signal recognition technologies can detect traffic signs & speed limit indicators and reduce the vehicle speed accordingly without human intervention. The technology is also expected to grow significantly as several government initiatives are promoting traffic sign recognition to ensure adherence to speed limits. In March 2019, the European Commission made it mandatory for all vehicles manufactured from 2022 to have built-in image/signal recognition capabilities. This is expected to reduce rash driving, over-speeding, and promote on-road safety.

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Automotive manufacturers are capitalizing on the steadily growing industry by introducing new features in their vehicles including automated parking, lane assistance, driver behavior monitoring, and adaptive cruise control. For instance, in October 2019, Toyota announced the launch of level-4 driver assistance systems for enabling automated valet parking in its upcoming cars. The technology is developed in conjunction with Panasonic and is built with inexpensive sensors, offering affordable parking assistance solutions to Toyota's customers.

Companies operating in Artificial Intelligence (AI) in Automotive market are focusing on various business growth strategies including investments in autonomous mobility solutions, strengthening partner network, and expanding R&D activities. Through such strategic moves, companies are trying to gain a broader market share and maintain their leadership in the market. For instance, in September 2019, Daimler partnered with Torc Robotics, an automated mobility firm, to design and develop level-4 autonomous trucks. Under the partnership, the companies are jointly testing autonomous trucks in the U.S. and focusing on evolving automated driving for heavy-duty vehicles.

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Semi-autonomous technologies have already been commercialized and are expected to gain significant Artificial Intelligence (AI) in Automotive market proliferation over the forecast timespan. The image/signal recognition segment held majority of the Artificial Intelligence (AI) in The semi-autonomous vehicles segment will grow at an impressive CAGR of over 38% by 2026 due to the extensive demand for Advanced Driver Assistance Systems (ADAS) and facilitating driving during heavy traffic scenarios.

The context awareness segment of the Artificial Intelligence (AI) in Automotive market is anticipated to register an impressive growth with a CAGR of over 35% from 2019 to 2026 due to the rapid proliferation of driver assistance solutions and semi-automated cruise control. Context awareness systems provide situational intelligence through multi-sensory input and enable onboard computers to detect & classify on-road entities including pedestrians, traffic, and road infrastructure. Customers are reaping the benefits of context-awareness systems by deploying effective navigation assistance, which enables safe driving even during driver distraction. Major technology companies are investing in innovative automotive technologies including context awareness. For instance, in November 2016, Intel announced an investment of USD 250 million in autonomous driving technology. This investment was focused on key technologies such as context awareness, deep learning, security, and connectivity.

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