The definition
An AI agent is software that uses AI to take actions, not only to write text. It can send an email, update a customer record, post a message or call another tool. Agentic AI means AI that works this way, with some independence.
Governing agents is the part of AI governance that deals with action. The question changes from "is the answer right?" to "should it have done that, and who allowed it?"
Why agents need their own governance
82%
of surveyed enterprises reported AI agents running in their environment that they did not know about.
Source: Cloud Security Alliance survey, commissioned by a security vendor, April 2026. 418 IT and security professionals
40%+
of agentic AI projects predicted to be canceled by the end of 2027, citing cost, unclear value and weak risk controls.
Source: Gartner, June 2025
An agent differs from a chatbot in three ways. It can act without a person copying its output. It can run many times, fast. And it can spend money on every step. Each of these needs a control that a chat policy does not give.
How to govern AI agents: five steps
- Register every agent. Keep one list of the agents your business uses, with an owner, a purpose and the systems each can reach. An agent with no owner is the first thing to fix.
- Set what each agent may do. Decide the access, the actions and the spend limit for each one. Start with less and widen as trust grows.
- Require approval for high-risk actions. Anything that reaches a customer, changes a record or spends above a set amount waits for a named person. Routine, low-risk work can run on its own.
- Keep a record. Log every action: which agent, what it did, who approved it, when and what it cost. The record should not be editable after the fact.
- Review and adjust. Look at the record on a schedule. Tighten limits where agents ask too often or act wrongly. Retire agents nobody uses.
Which actions need a person
Not every action needs approval. Asking for it everywhere makes agents slow and trains people to click yes. A common split:
| Risk | Example | Control |
|---|---|---|
| Low | Summarizing a document, drafting text for a person | Runs on its own, logged |
| Medium | Updating an internal record | Runs within limits, logged, reviewed later |
| High | Emailing a customer, changing a customer record, spending above a limit | Waits for a named approver |
| Stop | Anything unexpected or runaway | A person can pause all agent work |
See human approval for how MFDIO does this.
Who is responsible
- The owner of each agent answers for what it does.
- The approver decides the high-risk actions. This should be a named role, not "the team".
- A business or risk leader sets the limits and reviews the record.
- IT and security protect the systems and the access. Governance and security work together.
Agent governance and agent security
Security defends agents and systems from attack and misuse. Governance decides what agents are allowed to do and keeps the evidence. If an agent is tricked, security reduces the chance and governance limits the damage and shows what happened. Neither replaces the other.
What to look for in a tool
Ask whether it can:
- list every agent and its owner
- set access, actions and spend per agent
- hold high-risk actions for a named approver
- show a record of each action and its cost
- stop all agent work quickly
- say plainly what works today and what does not
The buyer's checklist turns these into ten questions.
How MFDIO applies this today
MFDIO is the AI governance platform. It follows four steps: Know, Authorize, Operate, Prove.
- Today: a register of agents and workflows built in MFDIO, policy controls (approval by default for risky actions, spend limits that warn, ask or stop, and roles), approvals before risky actions, an Emergency Stop, and an append-only audit log.
- Roadmap: registering agents built outside MFDIO, per-agent access and action policy, an assignable owner for each agent, and one-click connections to common business tools.
See the full list at what works today.
Questions people ask
What is agentic AI governance? The same thing as AI agent governance. "Agentic" describes AI that acts.
Can a company govern agents it did not build? Yes in principle: the controls apply to any agent. In MFDIO, agents built outside the platform are on the roadmap.
How do we stop an agent from taking an unauthorized action? Give it only the access it needs, hold high-risk actions for approval, and keep a way to pause everything.
Where do we start? List every agent already running, name an owner for each, and set a spend limit.
Limits of this guide
This guide is general information and not legal advice. MFDIO is in invite-only early access and is pre-revenue. MFDIO does not hold SOC 2 or ISO 27001 today. Market figures are analyst or survey estimates and vary between sources.
Sources
- Cloud Security Alliance, "Autonomous but Not Controlled: AI Agent Incidents Now Common in Enterprises", 21 April 2026 (418 IT and security professionals; commissioned by a security vendor)
- Gartner, June 2025: over 40% of agentic AI projects predicted to be canceled by the end of 2027; a third of enterprise software to include agentic AI by 2028
- MFDIO product facts: checked against the Today list at /status on 5 October 2026
Published . Last updated . Written by the MFDIO team.