How to Validate AI Under FDA's Computer Software Assurance Guidance

FDA's Computer Software Assurance guidance already gave teams a more efficient path to validation by encouraging a risk-based approach. AI puts that framework to its hardest test yet. When a system's output can shift with every model update, scripted test cases alone stop being sufficient, and teams are left asking how to prove AI can be trusted in a regulated process. This session breaks down how to apply CSA's risk-based principles to AI, and what that looks like in practice, using a validated Requirement Conflict Detection AI agent as a real-world example.