Healthcare organizations are adopting artificial intelligence faster than traditional governance can evolve, creating new risks around patient safety, security, compliance and operational resilience. This session will explore how to build an AI governance framework that balances innovation with accountability through executive oversight, risk-based governance, technical security controls and continuous monitoring. It will also examine why trust, education and human oversight remain essential as AI becomes more autonomous and increasingly embedded in clinical workflows.

In this session, led by Daniel Dopsovic and Krista Arndt of St. Luke's University Health Network, you will learn:

• How risk-based AI governance supports innovation while reducing security, privacy and compliance risks;
• Why shadow AI, human oversight and staff education are critical to responsible AI adoption;
• How layered technical controls, identity governance and continuous monitoring strengthen AI security.