The automotive industry is undergoing a profound transformation, shifting from handcrafted vehicles to software-defined cars and now moving rapidly toward AI-defined mobility. While software-defined architectures (SDV) have enabled modularity, OTA updates, and continuous feature evolution, the transition has not been seamless. OEMs underestimated the complexity of scalable software integration, zonal E/E architectures, and the need for robust cloud-to-car ecosystems. Legacy development models, siloed supplier strategies, and slow organizational adaptation have often delayed innovation. Now, as AI-native vehicles emerge—with perception-driven ADAS, predictive maintenance, personalized in-cabin experiences, and self-learning digital twins—the gap between traditional OEMs and tech-driven players is widening. To remain competitive, the industry must embrace data-centric engineering, end-to-end software platforms, and AI-first development pipelines. This presentation explores the lessons missed, strategic shifts required, and how AI-defined architectures will fundamentally reshape vehicle design, business models, and the global automotive value chain.
By engineers, for engineers: A technically grounded guide to the rapidly evolving in-cabin technology industry and companies.
