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Key Takeaway: Profitability is not defined by the cost of installing charging
Co-authors: Christoph Giannoulis (Senior Consultant, Autonomous Mobility), Adrian Grimm (Consultant, Autonomous Mobility)
AI capabilities are advancing at unprecedented speed, yet their adoption in vehicles lags behind – the Automotive AI Paradox. The Software-Defined Vehicle (SDV) provides the necessary foundation, but adding individual AI features does not create an AI-Defined Vehicle (AIDV). Today’s vehicles have intelligent features, but they are not yet intelligent systems: intelligence remains fragmented across separate domains, data and functions, while customers think in needs and goals rather than functions.
This contribution presents first results of the P3 Automotive AI Benchmark, scoring AI integration depth across 45 functions in five domains for European and Chinese OEMs. Mapped onto our P3 maturity model, from AI features to the agentic vehicle, the results reveal whether the gaps are a feature or a foundation problem, and how SDV architecture, AI-first versus AI-retrofit approaches and organizational setup explain them. We conclude with key constraints such as safety, data protection and regulation, and derive implications for European OEMs, Tier 1s and start-ups.
infrastructure, but by the ability to keep chargers reliably operational throughout their lifecycle.
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