Improve compliance, accuracy and efficiency through responsible AI deployment
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This is a technical guide for Quality and Regulatory Affairs (QARA) teams looking to use AI tools to reduce manual workload, improve traceability, and strengthen compliance workflows — without compromising validation, control, or audit readiness.
AI can provide significant value when implemented appropriately across a range of sectors. In MedTech, issues can arise when QARA teams are handed tools after the fact, with unclear value and unclear risk. This can AI adoption can create risk through:
Shadow systems (unvalidated tools outside QMS control).
Data leakage (sensitive info in public platforms).
Audit gaps (missing traceability for AI-driven decisions).
Whether you're tasked with preparing for audit, generating CERs, managing PMS, maintaining your QMS, or supporting new product submissions, this guide helps you:
Assess where AI can genuinely reduce burden without loss of oversight
Ensure AI outputs are traceable, verifiable, and scalable across teams
Avoid AI hype cycles and shadow systems that add risk, not value
Enabling QARA teams to help lead AI adoption could help ensure that outputs are traceable, verifiable, and scalable while maintaining audit readiness.
Author: Michael Kipping
Michael is RegNav’s Director of Strategic Partnerships. He has over 17 years of experience working at companies like Boston Scientific and BIOTRONIK and has spent ~7 years helping start-ups launch safe medical devices as part of MHRA and Innovate UK.
Author: James Pink
James is RegNav’s Director of R&D. He is an accomplished technical expert with a 25-year career in medical technology product safety and market access and has audited hundreds of medical device companies as part of the European CE marking requirements.
