AI-Assisted Post-Market Surveillance and Signal Detection: What Regulators Will Still Expect Humans to Defend

Post-market surveillance programs are increasingly incorporating AI-assisted tools to support complaint analysis, signal detection, trend identification, adverse event review, and large-scale data evaluation. While these technologies may help organizations process growing volumes of information more efficiently, regulatory responsibility for safety decisions, escalation activities, risk assessments, MDR reporting, and post-market actions continues to remain firmly with the organization. Questions are increasingly emerging around how AI-supported outputs are interpreted, challenged, verified, and ultimately defended when product safety concerns arise within FDA, EU MDR, and other regulated post-market environments. This session examines the practical realities of using AI-assisted approaches within post-market surveillance activities while maintaining defensible regulatory oversight. The discussion will focus on signal evaluation, complaint review processes, documentation practices, escalation decisions, and the role of human judgment when automated tools contribute to safety-related assessments. Code: FDB1417