AI-Defined Vehicle Report: How AI Reshapes Vehicle Intelligence?
Chinese OEMs’ AI-Defined Vehicle Strategy Research Report, 2025, studies, analyzes, and summarizes the concept of AI-defined vehicles, the differences between AI-defined vehicles and software-defined vehicles, the three key elements (data, computing power, and model) of AI-defined vehicles, the strategies and layout of mainstream OEMs in these three elements, how AI enables intelligent vehicle manufacturing, and the AI strategies and layout of mainstream OEMs in areas such as intelligent driving and intelligent cockpit.AI-defined vehicles refer to a new generation of vehicles that use artificial intelligence (AI) technology as the core driving force to reshape the full lifecycle of vehicles, involving R&D, design, production, usage, and services, in an all-round way. The core of AI-defined vehicles lies in feeding data and training rule-free AI foundation models to improve understanding, perception, and data decision capabilities in complex scenarios. The rapid iteration of AI foundation models marks a turning point from software-defined vehicles to AI-defined vehicles, that is, rule-based intelligent algorithms are being replaced by more flexible core AI technologies. From a technical perspective, "software-defined vehicles" emphasize expanding functionality through software upgrades, while the introduction of AI technology enables vehicle intelligence to break through fixed rules, giving vehicles the ability to learn and grow on their own.
AI-defined vehicles: Advance intelligent vehicles from "usable" to "easy to use": Some functions of software-defined vehicles still remain at the "usable" stage, and the shortcomings in accuracy, stability, and intelligent decision-making significantly affects user experience. AI-defined vehicles will reshape intelligent vehicles in multiple aspects, including intelligent cockpit, intelligent driving, and chassis domains, facilitating the evolution of intelligent vehicle products from functionality to capability. This will help to transform vehicles from a mere transportation mean into a "super agent" or a "smart mobility lifeform".
1. AI-defined Vehicles rely on deep coupling of three key elements: data, computing power, and model.
Data refers to various types of information collected when the vehicle travels and interacts with the external environment. It serves as the "fuel" for AI-defined vehicles, providing the basic materials for algorithm training and optimization. Computing power includes cloud computing centers and vehicle AI chips, which process data and execute computing tasks. It acts as the "engine" of intelligent vehicles, determining the upper limit of system performance. Model refers to a range of computing steps and rules based on AI theory and mathematical models, used to process and analyze data and achieve specific intelligent functions. It serves as the "brain" of vehicles, determining the level of intelligence.OEMs need to simultaneously deploy all the three elements: In terms of data, they need to establish all-scenario coverage capabilities; in terms of computing power, they need to break the energy efficiency bottleneck of chips; and in terms of model, they need to achieve vehicle-cloud cooperative reasoning. The ultimate form of AI-defined vehicles relies on the deep coupling of the three elements, forming a self-evolving system where "data becomes more refined with use, computing power becomes higher and more efficient, and models improve with training".
2. In rapid iteration of intelligent driving AI, competition over VLA models starts in 2025.
AI technology in intelligent driving evolves and iterates at an exceptionally fast pace, from traditional CNNs to BEV+Transformer (2023), end-to-end (2024), end-to-end+VLM (late 2024), and VLA (2025). VLA marks a paradigm leap in intelligent driving technology from "separation of perception and decision" to "integration of perception, reasoning, and execution".As an advanced form of traditional end-to-end intelligent driving, VLA (Vision-Language-Action) model addresses three core challenges of current intelligent driving systems through multimodal fusion (vision + language + execution) and chain-of-thought reasoning: global decision capability, breakthroughs in interpretability, and a leap in generalization performance.
Li Auto, Xpeng, Geely, and Xiaomi have all announced plans to gradually introduce VLA in their vehicles starting in 2025. Other OEMs, while adopting different (or similar) technology paths, are not lagging in integrating AI.
2025 may become the "singularity moment" for VLA-based intelligent driving solutions. The adoption of VLA is not just a technological upgrade but a transformation of intelligent vehicles from a mere "tool" into an "agent". In this race, companies with data bases, computing power advantages, and popular vehicle models will have a say in the automotive industry in the next decade. For consumers, more humanized mobility experience and fiercer market competition will be dual background colors in China's intelligent vehicle industry in 2025.
3. OEMs are quickening their pace of deploying AI and applying AI in vehicles.
Seen from Li Auto’s layout in AI-defined vehicles, since 2024, the company has entered a boom period of vehicle intelligence. It has rolled out industry’s first end-to-end + VLM dual-system intelligent driving, and "parking space to parking space" intelligent driving, and plans to mass-produce and implement its next-generation autonomous driving architecture, Mind VLA, in Q3 2025.Li Auto initiated its vehicle operating system R&D project in 2021. It input a 200-person team and over 1 billion yuan in R&D expense, and has completed solution selection, architecture design and implementation. The first version was mass-produced and used in vehicles in 2024. At the 2025 ZGC Forum Annual Conference in March 2025, Li Xiang, Chairman of Li Auto, announced that the company would open-source its vehicle OS. By Li Auto’s estimates, the open-source Halo OS could save the automotive industry 10-20 billion yuan annually by eliminating redundant R&D investments, further accelerating the development of AI-defined vehicles in China.
Since the beginning of 2025, Geely has fully embraced AI, positioning itself as a popularizer of intelligent vehicle AI technology. At CES 2025, Geely unveiled its “Full-Domain AI for Smart Vehicles” technology system. The company believes that true intelligent driving is not just about stacking features but AI enablement.
In the run-up to its product launch in March 2025, Geely partnered with Lifan Technology to establish a joint venture, Chongqing Qianli Intelligent Driving Technology Co., Ltd. Yin Qi, Chairman of Qianli Technology, is also a co-founder of Megvii, one of China’s "Four AI Dragons".
According to Yin Qi, AI technology is transitioning from L2 "reasoner" to L3 "agent", and it is the widespread belief in the industry that 2025 is the year of AI application explosion. This trend will first ignite "AI + vehicle".
How will AI define vehicles? Clues may be found in cooperation between Geely and Qianli Technology in three key areas: Ultra-Natural User Interface (NUl), Autonomous Driving & Execution (ADE), and Scaling Law for Al on EV.
Table of Contents
1 Overview of AI-Defined Vehicles
2 OEMs’ AI Infrastructure Layer Layout: Data + Computing Power
3 OEMs’ AI Model Layer Layout
4 How OEMs Apply AI in R&D, Production, Sales, Service, and Other Fields
5 OEMs’ Progress and Layout in AI-Defined Vehicles
Companies Mentioned
- Li Auto
- NIO
- Xpeng
- Xiaomi Auto
- Geely
- BYD
- Changan
- BAIC
- Great Wall Motor
- Chery
- SAIC
Methodology
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