AI in Quality Systems: What FDA & EMA Expect Now

Artificial Intelligence is rapidly moving from experimentation to operational use within regulated quality environments. At the same time, global regulators, including the U.S. FDA and European Medicines Agency (EMA), are clarifying expectations for how AI should be governed, validated, and monitored within quality systems.

This session translates evolving regulatory principles into practical guidance for quality and compliance leaders. Attendees will learn how regulatory expectations around transparency, oversight, data integrity, and lifecycle management apply when AI is embedded into quality processes such as deviations, CAPA, risk management, and supplier oversight.

Rather than focusing on theory, the discussion will show how organizations can operationalize AI responsibly, aligning innovation with compliance while strengthening risk visibility, decision-making, and continuous improvement across the quality system.

Participants will leave with a clear understanding of what regulators expect today and how to design AI-enabled quality workflows that are both compliant and future-ready.

Key Takeaways:

• Translate FDA & EMA AI expectations into practical quality workflows
• Apply GxP principles (validation, ALCOA+, auditability) to AI-driven processes
• Establish governance frameworks for AI oversight, risk classification, and lifecycle management
• Enable AI-assisted deviations, CAPA, and risk management with traceability and control
• Improve decision-making speed and risk visibility without compromising compliance
• Build a future-ready, always audit-ready quality system with embedded AI controls