Agentic AI Governance: What to Know When Creating an Agent Harness

Overview AI agents are moving from concept to deployment faster than most governance frameworks can keep up. Organizations rolling out agents — whether in customer service, operations, or internal workflows — are running into real questions about risk, compliance, and accountability that don't have obvious answers yet. This session is built for the leaders making those decisions. _ We'll cover what makes agentic AI different from traditional AI deployments, where the governance gaps tend to show up, and what practical frameworks look like for managing agents responsibly. Whether you're already deploying agents or preparing to, this session will help you understand the risks, set appropriate guardrails, and build accountability into your approach from the start. Enroll Check back soon for enrollment details. Note Course content is subject to change to keep pace with the latest advancements and updates. Course Outline What Makes Agentic AI Different From Assistants to Agents — What Changed Autonomy, Decision-Making, and Multi-Step Execution Why Existing AI Policies May Not Be Enough Risk and Compliance Identifying Risk in Agentic Deployments Regulatory Considerations and Industry Standards Data Privacy and Security with Autonomous Agents Building Accountability Who Is Responsible When an Agent Acts? Human-in-the-Loop vs. Autonomous Decision-Making Audit Trails, Transparency, and Explainability Building the Agent Harness What an Agent Harness Is and Why It Matters Setting Guardrails Without Slowing Down Adoption Policies and Processes That Scale