Automotive Artificial Intelligence Market by Size, Share, Trend (2022-2027)

Posted by Steve Stark on September 27th, 2022

The automotive artificial intelligence market size is valued at USD 2.3 Billion in 2022 and is anticipated to be USD 7.0 Billion by 2027; growing at a CAGR of 24.1% from 2022 to 2027. Factors such as rising demand for enhanced user experience and convenience features and the growing adoption of ADAS technology by OEMs are driving the growth of the market during the forecast period.

Driver: Rising demand for enhanced user experience and convenience features

Human-machine interface (HMI) solutions for the automotive industry have become easier to control and operate, thus enhancing user experience. Such solutions can give a user control over applications such as music systems, vehicle lights, and infotainment systems. Earlier, the electronics system in a vehicle accounted for just 1–2% of the vehicle cost, but due to the increasing demand for enhanced user experience and convenience features, the share has increased to 8–12%.

Restraint: Increase in the overall cost of vehicle

Autonomous vehicles are anticipated to be highly-priced chiefly due to the introduction of new commercialized technological systems. Most of the advanced technologies are embedded in luxury and premium cars, which have a limited customer base owing to their high price. Hence, a high vehicle cost is likely to dampen market growth. The demand for expensive autonomous vehicles is anticipated to be moderate, as compared to semi-autonomous vehicles.

Opportunity: High potential of in-car payments

Among the newest developments, in-car payments are designed to revolutionize how customers refuel, pay for parking or tolls, and possibly even how users do their grocery shopping. Open Banking, which enables clients to pay directly from their bank and reduces any friction or security risks in their payment journey, could be used to implement in-car wallets and payment systems. By streamlining transaction fees and providing a more seamless consumer experience overall, would reduce the need for third-party payment networks.

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Challenge: Effect of unfavorable weather on sensors

One of the main difficulties with driverless automobiles is bad vision. Self-driving cars use a variety of sensors, including camera sensors, radars, and lidars, to detect pedestrians, cyclists, or other vehicles on the road, and gauge their speed and distance. A self-driving car's control system receives data from the sensors, and t processes it. The system then determines whether to stop, turn left or right, proceed, or, if necessary, shift into reverse.