Set AI tool permissions, review and autonomy

Define autonomy as specific permitted actions

An AI agent can produce text without changing a business record. To take an action, it needs an available tool and the authority to use that tool in the current context. The configuration identifies allowed tool codes and required or delegated permissions; runtime checks consider the executing identity and provider policy.

Use a concrete description such as “draft a post for review” or “use the configured ticket-intake tool.” Avoid a vague instruction to manage everything. There is no universal autonomy switch that proves every module, record and external destination is accessible.

Separate preparation from execution

For publishing, distinguish generation, editing, correction, submission for review, approval, scheduling and external delivery. AI correction after rejection is not reviewer approval. A publishing time is also not evidence that a destination has accepted the content.

For support, distinguish an answer, captured request information, a created ticket and an actual human reply. For internal marketing work, distinguish a private task from a customer conversation or public campaign. The same well-written response can be appropriate in one of these contexts and inappropriate in another.

Configure knowledge, tools and execution limits together

1. Describe the agent’s allowed task and the cases that require staff.
2. Bind only the knowledge needed for that task.
3. Enable the tools required for the permitted actions, with the appropriate identity and permissions.
4. Keep the relevant publishing approval or ticket-routing rules in place.
5. Choose suitable timeout, output and tool-iteration limits for the configured runtime.

Limits help bound execution; they are not a published commercial AI allowance. Actual trial or plan entitlements must come from the offer provisioned for your workspace.

Test both allowed and denied actions

Verify a normal request against the resulting record, not only the agent’s description. Then test a request that should be refused, such as accessing unrelated protected context or taking an action outside the configured tool set. A successful test includes an understandable failure state and a route to staff where the workflow supplies one.

Test with the type of identity that will actually use the feature. An internal sandbox session does not prove that a guest website conversation has the same access, and a staff administrator’s permissions do not describe an ordinary support agent.

Read failures before retrying an operation

A run may stop because a provider is unavailable, a tool is denied, a runtime limit is reached or an external operation fails. Where available, execution history records the stage and outcome. Preserve the distinction between a denied action and a retryable service problem.

Before repeating an action that may send a message or create a record, check the current application state. An interrupted response can leave the outcome uncertain. Follow the relevant publishing or ticket-reply recovery guidance instead of repeatedly submitting the same request.

Expand automation after a working review cycle

Start with a small, supervised workflow and record where people edit, approve or escalate the result. Broaden tool access only when it serves a specific task and its failure path is understood. Review instructions, sources and allowed actions together when a workflow changes.

The workflow guide explains how these agent controls fit alongside queues, schedules and Lifecycle approvals. Those business rules continue to matter even when AI prepares the content.