As organizations accelerate the adoption of generative and agentic AI, the nature of AI risk is fundamentally changing. Autonomous systems, model orchestration, and AI‑driven decisioning introduce new challenges related to accountability, transparency, security, and regulatory exposure that traditional governance approaches were not designed to manage.

This session explores how organizations can establish a Trusted AI program that enables innovation while protecting trust. Drawing on real‑world implementation experience and a practical Trusted AI framework, the session focuses on moving from principles to execution across the AI lifecycle. Topics include defining accountability, creating visibility into AI usage, embedding security and risk controls, and preparing for evolving regulatory expectations in an increasingly agentic environment.

Participants will leave with a clear understanding of what effective Trusted AI looks like in practice, the foundational building blocks required to operationalize it, and concrete actions that can be taken now to strengthen AI governance and resilience.