Seminar 2026

Deploying AI in clinical setting is just the first hurdle; maintaining performance, compliance and trust over time has to be successful. This complexity is showing up in model drift, unclear re-validation triggers, and gaps in documentation and oversight as systems evolve. Attendees will learn: What post-approval AI lifecycle management looks like in practice, including monitoring, drift detection, and controlled updates How organizations are defining re-validation triggers and maintaining inspection-ready documentation as models change Where governance frameworks are succeeding (or falling short) in supporting adaptive AI within regulated environments How to operationalize ongoing oversight without slowing innovation or compromising compliance