Operationalizing Agentic AI: Governance, Observability, and Human Control at Scale

​Agentic AI is no longer theoretical. Systems that can reason, plan, and take action across workflows are entering production environments—and with them comes a new operational reality. The question is no longer can AI act autonomously, but how do we stay in control when it does?

This webinar focuses on the practical mechanics of deploying agentic AI responsibly. We’ll examine how to design governance frameworks that go beyond static guardrails, implement observability that surfaces intent and intermediate reasoning, and maintain meaningful human-in-the-loop oversight without slowing down innovation. From dynamic policy enforcement to real-time monitoring and escalation paths, we’ll explore how enterprises can operationalize autonomy without sacrificing accountability.

If your organization is experimenting with AI agents—or preparing to move from pilots to production—this session will help you build systems that are not only capable, but controllable.

What You'll Learn:

​1️⃣ Governance for Autonomous Systems: How to design policy layers, permissioning models, and approval workflows that align agent behavior with organizational risk tolerance and regulatory requirements.

​2️⃣ Observability Beyond Outputs: Why logging final responses isn’t enough—and how to instrument reasoning traces, tool usage, and memory state to create transparency in agent decision-making.

​3️⃣ Human-in-the-Loop by Design: Practical patterns for escalation, intervention, and override that preserve human authority while enabling agents to operate efficiently across complex workflows.

​4️⃣ From Pilot to Production Control: The architectural considerations—modular workflows, sandboxing, audit trails, and feedback loops—that make agentic systems safe and sustainable at enterprise scale. 

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