Automotive development has become increasingly digitalized through the use of model-based development (MBD), CAE, simulation, optimization, and other technologies, enabling engineers to conduct more studies and evaluations in a virtual environment before building physical prototypes. As an extension of this trend, the use of AI is also expanding into various areas of engineering.

This presentation will introduce how AI is beginning to bring changes to analysis, design, evaluation, and decision-making in automotive development. Starting with CAE acceleration and design exploration using surrogate models, it will also cover AI-based generation of design candidates, evaluation support, and the use of generative AI and AI agents.

Rather than automating everything with AI, the key is for engineers to define objectives and constraints, while AI supports analysis, exploration, information organization, and the generation of proposals, with engineers ultimately responsible for evaluation and decision-making. This presentation will consider how engineering may evolve from development in which people use tools to development in which people and AI work collaboratively.