Deploying health AI is not an endpoint, it's a transition into an ongoing cycle of verification, impact assessment, and trust-building. "Trust but verify" must operate continuously across the AI lifecycle.

• Hear how leading health systems translate trust principles into practice: from pre-deployment validation through post-deployment monitoring and real-world impact assessment
• Explore the critical distinction between technical performance metrics and actual clinical impact
• Understand the role of independent evaluation in sustaining trust: why third-party verification, transparent reporting, and stakeholder feedback loops are essential to responsible AI deployment
• Discover how partnerships between health systems, governance platforms, and privacy-preserving data infrastructure are scaling AI governance.