Medical devices now live across a continuum from hospital theatre to the patient sofa. Safety files still rely on manual complaint review, static PMCF plans and delayed PSUR updates. At the same time AI is entering clinical trials, registries and home monitoring. The challenge is simple. How do we use AI to strengthen safety without losing traceability or control

In this session I will walk through real world AI use cases that are already supporting MedTech safety in post market activities. We will look at AI assisted complaint coding and vigilance trend analysis mapped to MedDRA and ISO 14971, AI enabled PMCF and real world evidence that keep CER and PSUR live, and AI supported trial and registry data capture that reduces errors and missing data while improving patient follow up from clinic to home

For each use case I will link the AI workflow to concrete safety outputs. Signal detection, benefit risk updates, design changes and field safety actions. I will also share simple governance patterns that sponsors, CROs and hospitals can adopt today. Human in the loop review, validation in context, audit trails, and alignment with MDR, ISO 14155 and emerging AI guidance from EU, UK and US regulators

Attendees will leave with a practical checklist to decide when and how to introduce AI into their own PMS and PMCF systems so that AI becomes a trusted part of proactive safety from clinic to home rather than a black box risk.