Semiconductor engineering is entering a new phase of AI adoption. Rather than acting as assistants that answer questions or generate snippets of code, agentic systems are beginning to coordinate multi-step engineering workflows. What does that mean for semiconductor engineering teams?

For chip design teams, the opportunity lies not in replacing established engineering processes, but in reducing the manual effort required to move information throughout the development lifecycle. As AI capabilities mature, the industry is beginning to explore what greater autonomy could realistically look like.

This report explores:

  • Why semiconductor development has been slower than many industries to adopt AI.
  • The difference between AI assistants and agentic systems, and why it matters for engineering teams.
  • Where agentic workflows can add value across requirements, design, verification, and sign-off activities.
  • Key considerations for data strategy, governance, IP protection, and sustainability.
  • A realistic view of how autonomy may evolve within chip development over the coming years.

The direction of this trend is unambiguous. Learn more about the potential of agentic AI in chip design, and how to maximize the benefits for your team.

Download the full report