Artificial Intelligence (AI) in Automotive Market Drives Innovation, Projected to Reach US$ 744.39 Billion by 2033 at a 55% CAGR

The Artificial Intelligence (AI) in the automotive market is anticipated to record a robust CAGR of 55% between 2023 and 2033. The market is anticipated to cross a market share of US$ 9.3 billion by 2033, while it is expected to be valued at US$ 744.39 billion in 2023.

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Key Points

  1. The United States market is another significant market. The market growth is attributed to the presence of EV giants like Tesla, which delivers advanced AI and ML integration. The increased acceptance of autonomous and self-driving vehicles is fueling the sales of AI in the automotive
  2. Artificial intelligence (AI) in the automotive market in China is another significant market. The growth is attributed to the expanded manufacturing units, high-end research, and advanced experimentation.
  3. Europe with its environmental compliance adopts EVs and Hybrid Vehicles, which further fuels the demand for AI-integration prospects.
  4. The software segment is likely to thrive in the component category due to the common application and automotive implementation. It is expected to hold a value of US$ 200 billion by 2033.
  5. The fully autonomous segment tops the application category with an anticipated value of US$ 30 billion by 2033. The growth is attributed to the advent of self-driving assistance systems

Modern vehicles with fully autonomous and self-driving gearboxes are very desirable. The necessity for artificial intelligence (AI) in the automotive sector has grown as a result of the development of customised solutions by AI integration suppliers.

The broad adoption of EVs and hybrid vehicles, which benefit from features like park-guided systems that increase operational effectiveness, user convenience, and vehicle protection, coincides with the deployment of AI units.

The popularity of Level 2 Advanced Driver Assistance Systems (ADAS) among vehicle enthusiasts is assisting in the research and development of ADAS integration.

The new car manufacturers’ OEM-based AI chips help with a variety of vehicle functions. Every component is supported by AI, including the lighting, cruise control, air conditioning, assisted parking, and

Modern vehicles with fully autonomous and self-driving gearboxes are very desirable. The necessity for artificial intelligence (AI) in the automotive sector has grown as a result of the development of customised solutions by AI integration suppliers.

The broad adoption of EVs and hybrid vehicles, which benefit from features like park-guided systems that increase operational effectiveness, user convenience, and vehicle protection, coincides with the deployment of AI units.

The popularity of Level 2 Advanced Driver Assistance Systems (ADAS) among vehicle enthusiasts is assisting in the research and development of ADAS integration.

The new car manufacturers’ OEM-based AI chips help with a variety of vehicle functions. Every component is supported by AI, including the lighting, cruise control, air conditioning, assisted parking

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Competitive Landscape

The key competitors focus on inclusivity, while adding sensors and smart software to enhance the guided systems. Companies follow the artificial intelligence innovation with the key competitors and merge, acquire, and partner with other companies to increase the network range, connectivity, supply chain, and distribution channel. The key players in the market are: BMW AG, AUDI AG, Intel Corporation, Tesla Inc, Uber Technologies, Volvo Car Corporation, Honda Motors, Ford Motor Company, NVIDIA Corporation, and Tencent

Recent Market Developments

  • Ford Motor Co is the leading patent filer when it comes to the neural network for radar-LiDAR. The company operates with Baidu in China to implement AI technology in automotive.
  • A technology company, Aptiv is promoting enhanced automated vehicles that are loaded with AI-based sensors, cameras, and other components.

Key Segments

By Component:

  • Hardware
  • Software
  • Services

By Technology:

  • Computer Vision
  • Context Awareness
  • Deep Learning
  • Machine Learning
  • Natural Language Processing (NLP)

By Process:

  • Data Mining
  • Image/signal Recognition

By Application:

  • Semi-autonomous vehicles
  • Fully-autonomous Vehicles

By Region:

  • North America
  • Latin America
  • Europe
  • Asia Pacific (APAC)
  • The Middle East & Africa (MEA)

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About the Author

Nikhil Kaitwade

Associate Vice President at Future Market Insights, Inc. has over a decade of experience in market research and business consulting. He has successfully delivered 1500+ client assignments, predominantly in Automotive, Chemicals, Industrial Equipment, Oil & Gas, and Service industries.
His core competency circles around developing research methodology, creating a unique analysis framework, statistical data models for pricing analysis, competition mapping, and market feasibility analysis. His expertise also extends wide and beyond analysis, advising clients on identifying growth potential in established and niche market segments, investment/divestment decisions, and market entry decision-making.
Nikhil holds an MBA degree in Marketing and IT and a Graduate in Mechanical Engineering. Nikhil has authored several publications and quoted in journals like EMS Now, EPR Magazine, and EE Times.

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