An assistant that drafts a response and an agent that changes a business system have different risk profiles. Adding a tool is not just an integration decision: it changes what the solution can affect. Governance needs to make that change explicit.

Begin with purpose and an owner.

Record what the use case is meant to accomplish, who is accountable, and which systems or information it needs. Include a clear statement of what it must not do. An inventory becomes useful when it supports decisions about access, changes, and retirement.

Define the permitted action.

Specify the tool, input boundaries, target environment, and permitted effect. Reading a record, proposing an update, and executing an update should not be treated as equivalent permissions. A tool contract should be narrow enough to test and understandable enough to review.

Evaluate more than successful examples.

Test normal tasks, ambiguous requests, denied access, sensitive information, and untrusted content that attempts to redirect the system. Include failure and recovery behavior. Evaluate whether the solution stops safely when its assumptions or permissions are not satisfied.

Keep approvals independent.

Use explicit approval for actions that cross an agreed consequence threshold. A system should not be able to widen its own privileges or treat its own recommendation as authorization. Put enforcement in the identity and tool-access layers, not only in a prompt.

Make change observable.

Record relevant decisions, actions, and outcomes without indiscriminately retaining sensitive prompts. Reevaluate the use case when its model, knowledge, permissions, or tools change. The path to greater autonomy should depend on evidence and an accountable decision.

These are design principles. Actual controls depend on the platform, supported integrations, configuration, and a tested implementation.

Further reading

Security for AI
Microsoft's agent adoption guidance