The use of AI is currently… China the furthest, and this is particularly evident in the automotive industry. The country is setting standards with intelligent vehicles, not only for its own market, but increasingly for the industry as a whole. If you want to keep up, you should understand where this advantage comes from. It lies less in resources or implementation than in a particular type of strategic thinking that is culturally embedded.
This thinking is already evident in the choice of terms. In Europe, the electric vehicle is called “BEV” (Battery Electric Vehicle), a purely technical description. China spoke early about the “NEV”, the new energy vehicle, and thus brought an entire era into focus.
This was followed by the “ICV”, the Intelligent Connected Vehicle. Such terms are more than labels there; they determine what role a vehicle should play in everyday life. While Western industry predominantly relies on the Software Defined Vehicle (SDV), China has coined the term AI Defined Vehicle (AIDV): AI not as an additional function, but as the basic principle of the vehicle. Even at this starting point, China and Europe differ.
The Chinese automotive industry took this position early and almost across the board. Unlike in Europe, where the phrase “Culture eats strategy for breakfast” is often quoted, in China strategy itself is considered part of the culture, shaped by the classic art of war, in which the starting position determines success. The examples are numerous.
Xpeng introduced the P7+ in November 2024, calling it the world’s first AIDV. With Xuanji, BYD introduced an architecture that the manufacturer describes as the brain and nervous system of the vehicle. Huawei called its driving system “Qiankun,” a term that stands for cosmos and totality. Geely works under the keyword “Full Domain AI”, and Li Auto explicitly describes itself as an AI company. The design differs, but the common denominator remains: AI is not intended to improve the vehicle in specific areas, but rather to shape it as a whole and make it part of the user’s mobility.
What the AI-defined automobile technically means
The AIDV is not the same as autonomous driving; autonomous driving is just part of it. The logic is similar to that of the electric car: a BEV is designed around the battery, an AIDV around the AI models. Anything that can be digitized, from bus signals to sensor and environmental data to speech, gestures or calendar data, becomes readable for large-scale multimodal models, similar to how a language model processes different languages. If such models of the vehicle architecture are based on a cross-domain basis, they can combine this data and translate it into concrete functions. The rest is essentially a question of engineering work.
This results in four consequences:
- Security: A data-based and context-aware assessment complements rule-based engineering and also covers situations that cannot be fully summarized in rules in advance.
- Experience: Routine tasks such as planning a trip, finding a parking space or reacting to unexpected situations can be delegated to the system. Unlike pure automation, in which humans dictate every step, here they only state the goal; The vehicle takes care of the planning and execution. This means relief for customers and an additional source of income for manufacturers.
- Business models: Intelligence becomes its own value dimension. The customer buys the mechanics once, but chooses the intelligence, its scope and depth as needed. This goes beyond classic software sales and affects variables such as token consumption, context and model sizes or training depth.
- Cost: AI makes it possible to combine previously separate functions. With fewer variants and easier operation, more personalization and customization can be achieved: contextual intelligence instead of configuration.
What the European automotive industry needs now
China has also not yet kept the promise of the AIDV. Questions of data sovereignty, regulation and the trust needed for people to relinquish control remain open. The difference lies less in the state of solutions than in who asks the right questions earlier. Those who clarify the direction first can use their technical strengths more specifically.
The most urgent task for European industry is therefore not the question of how, but rather the question of direction. Two points are crucial.
First task: a binding, industry-wide fundamental decision for the AIDV as a development direction. This is the only way to pool resources and the industry to work with developments rather than against them. The AIDV should not be another position on a roadmap, but a strategic determination that comes before the operational questions. It costs nothing initially and saves you having to take detours later. This means that Europe is catching up with China and can then play to its own strengths.
Second task: After deciding on the direction, manufacturers must educate customers. It is then no longer about individual models or functions or about narrowing AI down to one tool, but about what vehicle intelligence means for mobility, safety and everyday life. If Chinese brands show European customers what is possible with AI before local manufacturers do, there is a risk of a loss of trust that will be difficult to make up for later.
This article deliberately does not answer the question of how. This may be unusual in German industry, but the how is rarely the real problem. 70 years ago, China was one of the poorest agricultural countries in the world, with an illiteracy rate of over 80 percent. Where it has developed since then is known. At the beginning there was not the question of implementation, but rather a clear strategic position. This ability to determine position first is one of the strengths of Chinese strategic culture.
If the European automotive industry completes these two tasks, it can have a say in the competition. Then it is their substance that counts: the depth of engineering, the safety culture, the trust of customers and the regulatory credibility. China’s lead so far lies primarily in its clear position rather than its substance. Europe shaped the past era of automobiles and can also play a defining role in the AI era if it determines its position in time.
Recognizing this and translating it into decisions requires technical understanding of AI as well as strategic and cultural thinking. I am available to discuss this in industry, politics and science.
