Dublin, April 23, 2025 (GLOBE NEWSWIRE) -- The "Chinese OEMs' AI-Defined Vehicle Strategy Research Report, 2025" has been added to ResearchAndMarkets.com's offering.
The report delves into the transformative impact of artificial intelligence (AI) on the vehicle industry, offering a comprehensive analysis of how AI-defined vehicles differ from their software-defined counterparts. Central to this evolution are data, computing power, and AI models, which together form the backbone of this technological shift.
Mainstream OEMs are strategically positioning themselves in these areas to revolutionize intelligent vehicle manufacturing, focusing on innovations like intelligent driving systems and smart cockpits. AI-defined vehicles represent a groundbreaking shift in vehicle technology by integrating AI at core levels of vehicle lifecycle management, from research and development to production and beyond.
Unlike software-defined vehicles, which enhance functionality through upgrades, AI-defined vehicles rely on data and AI models to adapt and learn, enhancing capabilities in complex scenarios. This transformation moves vehicles from merely being usable to being exceptionally user-friendly, significantly elevating the traditional driving experience.
To advance AI-defined vehicles, the integration of data, computing power, and models is crucial. Data, the fuel of AI-defined vehicles, is gathered from diverse interactions between the vehicle and its environment. Computing power, the system's engine, is facilitated by AI chips and cloud computing, pushing the boundaries of vehicle performance. Meanwhile, AI models, regarded as the vehicle’s brain, are responsible for processing data and enabling intelligent functionalities. OEMs are advised to harness these elements effectively to cultivate a self-evolving, intelligent vehicle system.
A significant milestone in the evolution of intelligent driving is set for 2025, with competition in Vision-Language-Action (VLA) models projected to rise. VLA models signify a leap in integrating perception, reasoning, and execution, moving beyond traditional AI paradigms. Companies such as Li Auto, Xpeng, Geely, and Xiaomi have already announced plans to incorporate VLA into their vehicles in 2025. This development not only signifies a technological upgrade but also positions these vehicles as agents in the mobility ecosystem, enhancing decision-making capabilities, interpretability, and generalization in driving scenarios.
In line with these advancements, OEMs are accelerating the integration of AI in vehicles. Li Auto, for instance, has led the charge with its dual-system intelligent driving and plans major releases in 2025, including its Mind VLA architecture. This aggressive R&D strategy, initiated with a substantial team and investment, is further supported by an open-source vehicle operating system— Halo OS—which promises significant cost savings across the industry. Geely mirrors this innovative spirit, showcasing its comprehensive "Full-Domain AI for Smart Vehicles" technology at CES 2025. Notably, the company has launched a joint venture aimed at pushing the boundaries of intelligent driving technology further.
This aligns with predictions of an AI application surge starting in 2025, transforming cars from tools to interactive agents, driven by advancements like Ultra-Natural User Interfaces, Autonomous Driving & Execution, and AI scaling for electric vehicles.
As the adoption of AI-defined vehicles accelerates, 2025 emerges as a pivotal year, marked by heightened competition and advancements. This evolution will likely redefine the automotive landscape, benefitting consumers with improved mobility experiences and fostering dynamic competition within the industry.
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 in the Era of AI-Defined Vehicles
- AI-Defined Vehicles Drives Changes in Urban Governance Models
- AI-Defined Vehicles Accelerates the Arrival of Future Transportation Modes
- Challenges in AI-Defined Vehicles and Solutions
2 OEMs’ AI Infrastructure Layer Layout: Data + Computing Power
- AI-Defined Vehicle Infrastructure Layer: Data
- AI-Defined Vehicle Infrastructure Layer: Cloud Computing Power
- AI-Defined Vehicle Infrastructure Layer: Vehicle Computing Power
3 OEMs’ AI Model Layer Layout
- Overview of Application of AI Foundation Models in the Automotive Sector
- Application of AI Foundation Models in Intelligent Driving
- Application of AI Foundation Models in Intelligent Cockpit and Interaction
- Summary of OEMs’ AI Foundation Model Applications
- Challenges in Application of AI Foundation Models in the Automotive Sector and Development Trends
4 How OEMs Apply AI in R&D, Production, Sales, Service, and Other Fields
- AI Technology Empowers OEMs Across the Entire Chain
- Application of AI Technology in R&D and Design
- Application of AI Technology in Vehicle Production
- Application of AI Technology in Sales and Service
- How OEMs Build AI Teams
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/6tkpjn
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