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Govern your AI agents before they act on their own

An AI agent doesn't just answer: it sends emails, changes records or triggers payments. If you don't know which agents you have, what they can do and who is accountable for them, the risk is yours even if nobody decided to take it.

The plan in three steps

  • 1Know which agents you have
  • 2Set limits on what they do
  • 3Be able to prove what they did
What changes

An agent is not a chatbot

An assistant that drafts text is like a copywriter: someone reviews what it writes. An agent is like an employee with access to your systems.

It acts

It doesn't stop at an answer: it sends, changes, buys or deletes. If it gets something wrong, the error has already happened.

It chains

It calls other tools and other agents. The final result belongs to the whole chain, not to one piece.

It remembers

It keeps memory between tasks, sometimes with personal data. You have to decide what it remembers and for how long.

3-step plan

Where to start with your agents

The same order regulators follow: know what you have, set limits and be able to prove it.

1

Know which agents you have

Build an inventory: which agents exist, who is accountable for each, which data and systems they access and whether the chain ends in a high-risk use.

TemplateAI Agent Inventory & Risk ClassificationOne record per agent, minimum fields and AI Act risk classification.
2

Set limits

Decide what each agent may do on its own, what needs human approval (payments, deletions, anything sent outside the company) and how it is stopped.

TemplateAI Agent Authorization & Boundaries PolicyPermissions, limits by amount or volume and actions that always need a person.
3

Be able to prove it

Record what each agent did, when and with which data, and make clear who is accountable when several agents work together.

TemplateAI Agent Audit Trail ChecklistWhat to log for each agent so you can reconstruct an operation.
Data first

An agent is only as reliable as the data it uses

An agent decides and acts with the information you give it access to. If the data is duplicated, out of date or has no owner, the agent repeats those errors, and faster than a person would.

That is why agent governance starts with data governance: knowing what data exists, who is accountable for it and how good it is.

See the Data Governance path → · Data quality →

Already using AI in your company?

Free AI Governance assessment: if you have agents, it tells you where to start.

Take the assessment

Frequently asked questions

Does the AI Act regulate AI agents?

It has no chapter of its own on them. An agent is classified like any AI system, by its use. If a chain of agents serves an Annex III high-risk use, those obligations apply, which in the EU start on 2 December 2027.

Is a chatbot an agent?

If it only answers, it is an assistant. If it also does things on its own (creates an order, sends an email, changes a record), treat it as an agent.

If I use a vendor's agent, is the vendor responsible?

Not entirely. The company that uses it decides which data and systems it can access and what it may do, and is accountable for that use. Review the vendor contract too.

Where do I start?

With the inventory: which agents exist, who is accountable for each and what they can do. Without it you can't set limits or prove anything.

Do you have agents running?

Start by knowing which ones. The templates follow the same order as this page.