What you'll learn:
- Understand why AI agents create a new category of operational risk that traditional IT governance frameworks are not designed to handle
- Build a complete agent inventory so your organization knows which autonomous systems are running, what they do, and who is accountable
- Define autonomy levels and behavioral boundaries specifying exactly what agents can do, what they must never do, and when to escalate
- Assess agent risk across financial, compliance, reputational, and operational dimensions combined with realistic failure likelihood
- Design guardrails and controls proportional to each agent's risk tier, applying strict governance where it matters most
- Establish a governance operating model with clear roles, review cadences, and escalation paths that keep agents accountable
- Monitor agents in production, identify metrics that signal unsafe behavior, and evaluate performance continuously after deployment
- Navigate the global AI regulatory landscape and identify where regulation leaves gaps that your internal policies must fill
- Apply enhanced governance to high-stakes scenarios in finance, HR, healthcare, and regulated industries where failure consequences are severe
- Design a complete 30-day governance implementation plan for a real agent with defined controls, ownership, and monitoring metrics
AI agents are no longer experimental. Organizations are deploying them across sales, operations, finance, and customer service, giving them access to real systems and the autonomy to take real actions. And most organizations are doing it without adequate governance.
That's the problem this course solves.
When an agent approves a transaction, sends a customer communication, or updates a critical record, something can go wrong in ways traditional IT governance was never designed to catch. Agents fail subtly, cascade errors across systems, and create accountability gaps that only become visible after damage is done.
This course gives you a complete, practical framework for governing AI agents responsibly. You will learn how to build an agent inventory, assess risk across financial, compliance, reputational, and operational dimensions, and design behavioral boundaries and oversight models proportional to each agent's risk level.
You will establish a governance operating model with clear roles, escalation paths, and review cadences. You will learn what to monitor in production and which signals indicate an agent is drifting from safe behavior. You will navigate the global regulatory landscape, understand where regulation leaves gaps, and build internal policies to fill them.
The course closes with a hands-on workshop where you design a complete 30-day governance implementation plan for a real agent in your organization.
No technical background required. If you work with AI agents or are planning to, this course gives you the frameworks and tools to deploy them with confidence, accountability, and control.
