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Artificial Intelligence In Automotive Market Overview 2024-2033: Growth and Market Overview
Artificial Intelligence In Automotive Market Overview
As per the report, the artificial intelligence in automotive market size has grown exponentially in recent years. It will grow from $6.7 billion in 2023 to $10.88 billion in 2024 at a compound annual growth rate (CAGR) of 62.3%. The artificial intelligence in automotive market size is expected to see exponential growth in the next few years. It will grow to $64.2 billion in 2028 at a compound annual growth rate (CAGR) of 55.9%.
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The Pivotal Role Of Artificial Intelligence In Meeting The Rising Demand For Autonomous Vehicles In The Automotive Market
The growing need for autonomous vehicles is expected to propel the growth of artificial intelligence in the automotive market going forward. An autonomous vehicle is a vehicle capable of operating itself and performing necessary functions without any human intervention through its ability to sense its surroundings. AI in automotive is being used to develop autonomous driving systems that can sense and interpret the environment, make decisions, and control the vehicle without human intervention. For instance, in December 2022, according to the National Highway Traffic Safety Administration, a US-based government agency, there will be 3.5 million self-driving vehicles on U.S. roads by 2025 and 4.5 million by 2030. Therefore, the growing need for autonomous vehicles is driving the growth of artificial intelligence in the automotive market.
Qualcomm Redefines Automotive Infotainment With 4th Generation Snapdragon Automotive Cockpit Platforms
Major companies operating in the artificial intelligence in the automotive market are developing innovative products such as Snapdragon automotive cockpit platforms to better serve their customers. The Snapdragon automotive cockpit platforms are advanced in-car technology platforms designed to enhance the automotive infotainment experience and enable connected and intelligent features in modern vehicles. For instance, in January 2021, Qualcomm, a US-based semiconductor company, launched the 4th Generation Snapdragon Automotive Cockpit Platforms. This new generation promises to redefine the in-car experience, offering a blend of advanced AI capabilities and seamless connectivity. The platforms are designed to revolutionize the digital cockpit, offering enhanced graphics, multimedia, computer vision, and in-car connectivity. They are fully scalable, supporting all three Snapdragon Automotive performance tiers, ranging from Performance, Premiere, and Paramount.
The artificial intelligence in automotive market covered in this report is segmented -
1) By Component: Hardware, Software, Services
2) By Process: Data Mining, Image Or Signal Recognition
3) By Technology: Computer Vision, Context Awareness, Deep Learning, Machine Learning, Natural Language Processing (NLP)
4) By Application: Semi-autonomous vehicles, Fully-autonomous Vehicles
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Major companies operating in the artificial intelligence in automotive market report are Alphabet Inc., Toyota Motor Corporation , Microsoft Corporation, Ford Motor Company, General Motors Company, Bayerische Motoren Werke AG, Honda Motor Co. Ltd., Tencent Holdings Ltd., Tesla Inc., Intel Corporation, The International Business Machines Corporation (IBM), Audi AG, Volvo Cars, AB Volvo, Qualcomm Technologies Inc., The Mercedes-Benz Group AG, Mitsubishi Electric , Uber Technologies Inc., Micron Technology Inc., NVIDIA Corporation, Harman International Industries Inc., Waymo LLC, Xilinx Inc., Argo AI, Cognata ltd
Contents of the report:
1. Executive Summary
2. Artificial Intelligence In Automotive Market Report Structure
3. Artificial Intelligence In Automotive Market Trends And Strategies
4. Artificial Intelligence In Automotive Market - Macro Economic Scenario
5. Artificial Intelligence In Automotive Market Size And Growth
…..
27. Artificial Intelligence In Automotive Market Competitor Landscape And Company Profiles
28. Key Mergers And Acquisitions
29. Future Outlook and Potential Analysis
30. Appendix
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