CHICAGO, Aug. 24, 2022 /PRNewswire/ -- Automotive Artificial Intelligence market size is projected to grow from USD 2.3 Billion in 2022 to USD 7.0 Billion by 2027; it is expected to grow at a CAGR of 24.1% from 2022 to 2027, according to a new report by MarketsandMarkets™. The key factors contributing to the growth of the Automotive Artificial Intelligence market include the growing adoption of ADAS technology by OEMs, and the rising demand for enhanced user experience and convenience features are among the factors driving the growth of the Automotive Artificial Intelligence market.
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Software segment is expected to hold a larger share of automotive artificial intelligence market.
The software holds a major share of the overall AI market in the automotive industry because of the various developments of AI software and related software development kits. AI systems require different types of software including application program interfaces such as language, speech, vision, and sensor data along with machine learning algorithms to realize automotive applications. Software platforms and solutions are expensive because of the limited number of skilled machine learning algorithm developers: which is the major reason for the larger share of software in the automotive AI market. Alphabet Inc. (US), Microsoft Corporation (US), IBM Corporation (US), and Intel Corporation (US) are among the frontrunners in the development of AI software for the automotive industry.
APAC exhibit the highest CAGR during the forecast period.
The market in the APAC is expected to grow at the highest CAGR from 2022 to 2027. This region houses established automakers such as Toyota (Japan), Hyundai Motor Company (South Korea), and Honda Motor Company (Japan). The growth in the market is due to the increasing population, improving lifestyles, and growing economies that have accelerated the pace of passenger car demand in the Asia Pacific.
Deep learning expected to hold largest share of the automotive artificial intelligence market in 2022.
Deep learning algorithms help in identifying patterns from the set of unstructured data. Presently, deep learning technology is used in voice recognition, fraud detection, voice search, recommendation engines, sentiment analysis, image recognition, and motion detection. It is also used in object detection, advanced driver assistance systems (ADAS), crash avoidance, and vehicle telematics control using speech recognition. The growing application of deep learning algorithms is the major driving force of the automotive AI market.
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Signal recognition segment is expected to hold the largest share of the automotive artificial intelligence market.
Signal recognition is a method of generating results with the help of speech, visible patterns, and sound. The signals generally refer to the voice or the sound produced by a machine or human being, which can be detected by natural language processing (NLP) machines to generate a result. Signals are the raw data that AI systems should be able to interpret for creating, understanding, and making informed decisions. Signal recognition is the largest market, by process, in the automotive AI market; it plays an important part in autonomous and semi-autonomous driving applications where it is used for traffic sign detection, driver assistance systems, etc.
The key players in this market are NVIDIA Corporation (US), Alphabet Inc. (US), Intel Corporation (US), IBM Corporation (US), Microsoft Corporation (US), Xilinx Inc. (US), Qualcomm Inc. (US), Tesla Inc. (US), BMW AG (Germany), and Micron technology (US). The players in this market have adopted various strategies to expand their global presence and increase their market shares.
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