LTR 161: AI Governance by Design

Summary

“Let’s treat AI governance by design as the connective tissue of a product lifecycle ecosystem.”

AI governance is often introduced as another layer of oversight—more procedures, approvals, documentation, and checklists. Ankita Mishra offers a different way to think about it: governance should be designed into the digital health product lifecycle from the beginning.

In this episode of the Let’s Talk Risk! conversation, host Naveen Agarwal and Ankita Mishra explore how systems thinking and risk-based decision-making can help organizations innovate responsibly without applying the same level of rigor to every product or use case. They discuss flexible quality systems, the importance of defensible rationale, third-party AI solutions, supplier dependencies, privacy and security, model performance, and the need to monitor AI after deployment.

The conversation also addresses what AI means for quality, regulatory, and risk professionals. Rather than making human expertise less relevant, Ankita argues that AI increases the need for critical thinking, judgment, collaboration, and continuous learning.

Listen to the full 25-minute podcast or jump to a section of interest listed below.

Chapters

00:00 – Introduction and Welcome01:04 – Ankita Mishra’s Career Journey04:36 – Reframing AI Governance by Design06:40 – Shifting Critical Thinking Upstream09:11 – Matching Development Rigor to Risk12:20 – Building Defensible Risk-Based Rationales14:17 – AI Governance Across the Product Lifecycle16:03 – Evaluating Third-Party AI and eQMS Solutions18:22 – Preparing Quality and Regulatory Professionals for AI23:00 – Closing Takeaways on Responsible AI

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Suggested links:

LTR: Proactive AI Governance in MedTech.

LTR: Building Trustworthy AI and MedTech Readiness.