Agentic AI is rapidly transforming enterprise operations by enabling autonomous decision-making, workflow orchestration, and intelligent process automation. However, organizations in regulated industries face significant challenges in balancing AI autonomy with governance, compliance, transparency, and accountability. This session presents a practical framework for building governance-aware agentic AI systems that can safely operate in high-stakes environments. Drawing from real-world enterprise architecture experience, the talk explores how validation-driven workflows, human oversight, explainability mechanisms, evidence capture, and policy-based controls can be embedded directly into agent architectures. Attendees will learn how to move from isolated AI experiments to production-ready agentic systems while maintaining auditability, operational control, and regulatory alignment. The session provides actionable architectural patterns and lessons learned for deploying trustworthy AI agents that deliver business value without compromising governance. Participants will leave with a blueprint for scaling responsible AI adoption across enterprise environments.