Agent Governance Conversation
Giving AI agents authority? Let's talk about the boundary.
Your agents are moving from generating answers to taking action — updating systems, committing resources, initiating processes that used to require a person's sign-off. That shift changes what “governance” has to mean.
This conversation is where we work through a real action an agent is trying to take, and what it would mean to govern it — what should be allowed automatically, where a human needs to approve, and what should never happen without review.
Bring us the actions you are trying to govern — the systems they touch, the resources at stake, the approvals you already require. We'll help you think through the boundary.
Free · Exploratory · No obligation
Agent action
procurement.release_po
Amount
$185,000
Resource
PO-84721
Authority question
Can this agent commit this action?
Bring the action. We'll examine the boundary.
When This Conversation Is Useful
If any of this sounds familiar, it's worth talking about the boundary now.
01
Agents can change enterprise systems
Agents are being connected to ERP, CRM, finance and operational platforms — with the ability to create, update or close records directly, not just surface recommendations.
02
Agents can commit resources
Releasing a purchase order, issuing a credit, sending a payment — actions that used to require a person to click “approve” are increasingly initiated by an agent instead.
03
Human approval is becoming part of the workflow
Some actions should still stop for a person. The question is which ones, under what conditions, and how that approval step is enforced rather than assumed.
04
Different agents are appearing across the enterprise
Internally built agents, vendor agents embedded in software you already use, developer and customer-facing agents — each with its own access, and no single place governing all of them the same way.
If you recognize any of this, you don't need a finished governance model to start the conversation.
Most teams we talk to are still figuring out where their boundaries should be. That's a reasonable place to start.
Agent Governance Intake
Tell us about the action you're trying to govern.
There's no wrong level of detail here. If you're still working out where your agents can act, tell us that — it's useful context on its own.
The more specific you can be about the systems, resources and actions involved, the more useful the conversation will be.
What Happens Next
We'll review the governance problem before we talk.
01 — Review
We'll look at the context you submitted and identify the consequential actions, authority boundaries and governance questions worth discussing.
02 — Conversation
Together, we'll examine what the agent wants to do, what should be allowed automatically, where human approval belongs, what should be denied, and what evidence the enterprise needs afterward.
03 — Determine fit
If the problem fits Arbiter's action-governance model, we can discuss an appropriate next step. If the issue belongs somewhere else, we should be clear about that too.
This is a problem-definition conversation, not a commitment to buy or deploy Arbiter.
You don't need a complete governance architecture to have this conversation. You need one real action worth examining.
Should this agent be allowed to do this — under these conditions?
Governance becomes clearer when it is attached to a real action.
Request an Agent Governance Conversation