AI Reshapes Automotive Software Development: Use Cases, Risks & Future Trends
This article analyzes how AI technologies like LLMs, knowledge graphs, and reinforcement learning are applied across automotive software development stages—requirements, design, coding, testing, and verification—while highlighting risks such as batch design defects and data leaks, and outlining a phased adoption path toward multi-agent AI collaboration and new engineering roles.
