You Cannot Govern Agents You Cannot Find
Once an organization moves from talking about agents to actually building them, a new problem appears quickly. A leader builds one agent to understand how agents work. A team builds another to summarize customer calls. Someone creates one to monitor exceptions. Progress begins — and so does proliferation.
Each agent may be useful. Each may solve a local problem. But if the organization has no way to track them, a new form of sprawl begins.
Agent Sprawl Comes Fast
Most companies already know what SaaS sprawl feels like. Different teams buy tools for local needs. Over time, the organization accumulates overlapping systems, unclear ownership, inconsistent permissions, duplicate data, hidden costs, and security risk.
Agent sprawl can happen even faster. Agents are easier to create than software applications. They can be built by smaller teams, configured in low-code tools, connected to existing systems, and modified quickly. That flexibility is powerful, but it also creates risk.
Without a shared management surface, the organization may not know even basic information about which agents have been created, who owns them, what they are doing, or whether they are still behaving as intended.
This is not a theoretical governance problem. It is an operating problem. If agents are going to participate in real work, they must be visible.
You cannot govern agents you cannot find.
Start With a Registry, Not a Bureaucracy
The answer is not to create a heavy governance committee before anyone has learned how agents work. But the answer is also not to let every team build whatever it wants in isolation. The starting point should be simple: every agent needs a place to live.
That can be a lightweight repository or registry. It should stay simple enough for teams to use, while still answering basic questions:
what the agent is called
who owns it
what its role is
what systems it accesses
what permissions it has
what version is deployed
where it is running
what events or activities it logs
when it should escalate to a human
whether it is experimental, active, deprecated, or retired
This kind of registry is not paperwork. It is the first management surface for the agent workforce. If an organization wants agents to become part of how work gets done, it needs a way to see them, compare them, reuse them, update them, and retire them.
This is what progressive governance looks like at the beginning. It is not airtight governance, and it should not try to be. It is enough structure to prevent chaos without creating paralysis.
Some Governance Can Be Agentic
Visibility also creates a second opportunity: some governance can itself be agentic. If agents are part of the workforce, some of the governance around them can also be performed by agents.
An observer agent can monitor the registry and look for missing or unusual patterns. It can flag agents without owners, agents with unclear permissions, agents that have not been updated, agents that appear duplicative, agents that are producing repeated exceptions, or agents whose access no longer matches their role.
The observer agent does not replace human accountability. It makes accountability easier. It can escalate potential issues to a human owner or to the person responsible for the organization’s emerging agent workforce. The human still decides what matters, what should be approved, what should be fixed, and what should be retired.
This is a useful pattern. Agents can help govern agents, but humans must remain accountable for the governance system.
Governance Is Also How Organizations Learn
A registry is not only a control mechanism. It is also a learning mechanism.
When agents are visible, the organization can see patterns:
which agents are being reused
which teams are solving the same problem independently
which agent roles are becoming common
which permissions are repeatedly needed
where exceptions are occurring
which agents should become shared components
This matters because agent-native organizations should not build every agent from scratch. Over time, they should learn which capabilities are reusable and which behaviors need to remain local.
The goal is not to eliminate local experimentation. The goal is to prevent local experimentation from disappearing into shadow systems.
Good governance turns local learning into organizational learning.
Organizations do not need airtight agent governance on day one. They do need a starting point.
That starting point is visibility. If an agent performs work, it should be known. If it is known, it can be owned. If it is owned, it can be governed. If it is governed, it can be improved, reused, or retired.
The first rule is simple:
You cannot govern agents you cannot find.
