Short answer. Teams that keep control without slowing adoption put a few checkpoints on every agent. They find agents where they turn up, record who is responsible for each agent before access is granted, keep the ability to shut off one agent alone and record who each action was for. Business teams keep building, and security can answer who acted and for whom.
Agents built by business teams often reach production before security knows
There are usually more agents than anyone has listed. Most turn up in a few places: apps people approved with their work sign-in, the agent lists inside tools like Copilot Studio, keys stored in code or password vaults, and network calls to AI services. That gives a starting list. Keeping it current means routing new agents through one access point, so each one shows up the first time it calls a tool.
Each agent needs two contacts before it gets access
Many agents are tied to the one person who set them up. If that person leaves or changes roles, the agent keeps its access, and it's unclear who should review it or turn it off. Before an agent gets access, record two contacts: someone on the team that runs it, and a business lead who can say whether it's still needed. For agents already running, find the ones without these contacts and either add contacts or turn them off.
Shutting off one agent can stop everything that shares its account
It helps to know how to stop an agent before it goes live. On a shared service account or API key, stopping one agent breaks everything else on that key, so teams hesitate and the agent keeps running. With its own identity and a check on each request, revoking it stops that agent at its next request and nothing else.
Auditors expect each agent action to trace back to a person
The audit question is simple: who did this, and for whom? A service account log answers with an account name. A record from the check on each request, naming the agent, the person, the tool and the decision, answers it and belongs in the SIEM with everything else.
Frequently Asked Questions
What is AI agent governance?
AI agent governance is the set of checkpoints that decide which agents can run, who is responsible for each and what each one may do. In practice, it covers finding agents, recording who is responsible, shutting one off and keeping records auditors accept.
Do we need a separate governance program for AI agents?
Usually not. Agents can sit in the identity and access reviews teams already run. What those reviews typically miss is a check on each request and a record of who each action was for, which teams add as a layer between agents and their tools.