Agentic AI governance framework: six controls to have in place before an agent goes live

In short: An agentic AI governance framework is the set of controls an organization puts in place before an AI system can act with delegated access to tools, data and accounts. Public sources point to six: a named owner, limits on delegated access, adversarial testing, a component record, honest disclosure and claims, and monitoring with a tested response path. The OWASP GenAI Security Project, whose community has passed 30,000 members, has published an Agent Control Standard and tracked agent-related exploits each quarter through September 30, 2026.

Agents differ from chat assistants in one way that matters for governance: they act. They call tools, move data and use credentials on someone’s behalf. OWASP’s case for its Agent Control Standard starts from this point. It says that widescale adoption of AI agents depends on trust, and that trust requires transparency and control. This briefing sets out the controls to have in place before an agent leaves the pilot, the public sources behind each one, and the regulatory exposure that makes them more than good practice. Whether a product is really an agent is a separate question, covered in our briefing on what makes an AI agent an agent.