DUBLIN: The "Chinese OEMs' AI-Defined Vehicle Strategy Research Report, 2025" has been added to ResearchAndMarkets.com's offering.

The report delves into the advancements and strategies in the domain of AI-defined vehicles. Focusing on key elements such as data, computing power, and models, the report elaborates on how these aspects are integral to the rise of AI-defined vehicles over the traditional software-defined approach. It offers insights into how AI enables innovative manufacturing and how industry giants like Li Auto, Xpeng, Geely, and Xiaomi are pioneering this transformation.

AI-defined vehicles are revolutionizing the automotive industry by utilizing AI as a pivotal component throughout the vehicle lifecycle—from research and development to design, production, and service. This shift marks a significant transition as vehicles evolve from software-driven to AI-centric models, enhancing understanding, perception, and decision-making abilities in complex scenarios. This change allows vehicles to move beyond basic functionality, becoming intuitive partners enhancing the driving experience.

Central to the evolution of AI-defined vehicles are three intertwined elements: data, computing power, and models. Data gathered from various vehicle interactions provides the essential training material for algorithms. Computing power, facilitated by cloud computing and AI chips, propels the system's capabilities. Meanwhile, models based on advanced AI theories and mathematical frameworks serve as the vehicle's intelligent decision-making core.

Original Equipment Manufacturers (OEMs) must strategically integrate these components to facilitate a self-evolving system where data becomes more refined, computing power efficient, and models progressively smarter. This integration heralds a transformation in intelligent driving technologies, particularly with the advent of Vision-Language-Action (VLA) models by 2025. These models promise to overcome traditional challenges, combining perception, reasoning, and execution into one seamless process.

Industry leaders such as Li Auto and Geely are at the forefront of these AI advancements. Li Auto has been deploying pioneering systems since 2024, introducing end-to-end intelligent driving systems, such as the VLM dual-system architecture, with plans for mass-production of Mind VLA technology by Q3 2025. The open-sourcing of their Halo OS is set to significantly reduce automotive R&D costs industry-wide. Meanwhile, Geely, through its partnership with Lifan Technology via the Chongqing Qianli Intelligent Driving Technology venture, is pioneering a comprehensive AI technology system for vehicles, emphasizing the necessity of AI enablement over mere feature aggregation.

Moreover, AI technology is propelling a shift from L2 "reasoner" systems to L3 "agent" frameworks, suggesting an imminent AI application explosion, with the automotive sector being a primary focus. This evolution is poised to redefine the vehicle as a smart, responsive, and adaptive entity, fundamentally altering our interaction with automobiles.

Strategic cooperation between industry leaders like Geely and Qianli Technology may provide valuable insights in areas such as Ultra-Natural User Interface (NUI), Autonomous Driving and Execution (ADE), and the scaling law for AI in electric vehicles (EVs). These developments highlight the growing influence of AI in transforming vehicles from simple transport tools to intelligent mobility solutions.

Key Topics Covered:

1 Overview of AI-Defined Vehicles

• AI-Defined Vehicles vs. Software-Defined Vehicles
• Three Key Elements of AI-Defined Vehicles
• AI Is Reshaping the Automotive Industry Pattern
• Transportation Industry Changes Brought by AI-Defined Vehicles
• Human-Machine Cooperation Models
• AI-Defined Vehicles and Urban Governance Models
• Future Transportation Modes
• Challenges and Solutions

2 OEMs’ AI Infrastructure Layer Layout: Data + Computing Power

• Data & AI Applications
• Cloud and Vehicle Computing Power

3 OEMs’ AI Model Layer Layout

• AI Foundation Models in Automotive Sector
• Applications in Different Vehicle Layers
• Intelligent Driving
• Intelligent Cockpit and Interaction
• Trends and Challenges

4 How OEMs Apply AI in R&D, Production, Sales, Service, and Other Fields

• AI Technology Across the Chain

5 OEMs’ Progress and Layout in AI-Defined Vehicles

• Li Auto
• NIO
• Xpeng
• Xiaomi Auto
• Geely
• BYD
• Changan
• BAIC
• Great Wall Motor
• Chery
• SAIC

For more information about this report visit https://www.researchandmarkets.com/r/588bng

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Fonte: Business Wire