• Thomas Andersen, head of AI and ML solutions at Synopsys, is the guest on the latest Electronics Weekly CHIIPS podcast.
  • The episode focuses on AI-driven automation in semiconductor design, verification and workflows.
  • The conversation highlights opportunities for faster design cycles and practical risks teams must manage.
  • Engineers and product teams are urged to understand how AI tools integrate into existing EDA toolchains.

What the episode is about

The newest CHIIPS episode from Electronics Weekly features Thomas Andersen, who heads the AI and ML solutions group at Synopsys. The conversation centers on AI automation in the semiconductor space — how machine learning and automated flows are changing design, verification and toolchains used by chip teams.

Why this matters now

AI-driven tools promise to speed up tasks that have long been slow or manual in chip development: placement, routing, verification rule generation and design-space exploration are often cited as areas where automation yields time savings. Andersen’s appearance on CHIIPS signals that these capabilities are moving from research demos toward practical deployment inside major EDA vendors — a shift that could alter how engineering teams organize work.

For engineers and managers, the takeaway is twofold: there are clear efficiency gains to capture, and there are risks to manage when adopting AI components — from tool validation and reproducibility to workflow integration and IP protection.

Key themes covered

  • Adoption: How AI fits into existing electronic design automation (EDA) toolchains and the practical steps teams need to take to adopt automation without disrupting current projects.
  • Verification and trust: Why validating AI-driven outputs remains critical and how teams should approach verification of models and automated suggestions.
  • Workflow change: The organizational impact of automation, including new processes, skill requirements and the need for oversight.

Who should listen

The episode is relevant to semiconductor designers, verification engineers, EDA tool developers and product managers evaluating automation for their roadmaps. It’s also useful for technical leaders who must weigh productivity gains against the practical challenges of integrating machine learning into regulated or safety‑critical flows.

Impact and next steps

While the CHIIPS episode does not replace technical documentation or hands‑on evaluations, it provides a high‑level view from an industry practitioner at Synopsys. Listeners can expect a practical discussion about where AI helps most today, and what teams should watch for as automated capabilities mature.

If you work in chip development, this episode serves as an early warning and a roadmap: ignore AI automation at your own risk, but approach adoption deliberately — validating results, protecting IP and updating workflows. For full context and deeper examples, listen to the CHIIPS episode on Electronics Weekly and follow Synopsys’ announcements for detailed technical guidance.

Image Referance: https://www.electronicsweekly.com/blogs/electro-ramblings/site-update/chiips-26-ai-automation-from-thomas-andersen-of-synopsys-2026-02/