Agentic AI in automotive product development: Building the future of intelligent engineering
Learn how autonomous AI agents help you accelerate vehicle development, reduce complexity and stay ahead of compliance, from requirements to release.
Automotive product development is reaching a breaking point. Increasing system complexity, software intensity, regulatory pressure and the need for faster innovation are making traditional engineering approaches unsustainable.
While AI is already used across many engineering tasks, most implementations are fragmented and isolated. They deliver local efficiency but fail to address end-to-end complexity. The real opportunity lies in moving to agentic AI: autonomous, goal-driven agents that orchestrate connected workflows across the lifecycle, adapt to changes in real time and connect data, tools and teams.
In this guide, you will find:
- Why automotive product development requires an agentic AI approach, and what makes it different from point solutions.
- The 8 highest-impact agentic workflows across your engineering lifecycle, from requirements to test cases to continuous compliance and data-driven engineering.
- How the NTT DATA Systems Engineering Copilot provides the foundation to orchestrate multiple AI agents with full traceability and Human-in-the-Loop governance.
- A practical transformation roadmap, from a focused value discovery workshop to a 3-month PoC and a scalable agentic AI factory.