To stop an AI agent from making unapproved changes, separate three controls: let it prepare a draft without committing it, require approval immediately before selected writes, or remove write capability. Audit logs help explain what happened afterward, but they do not prevent a write. Choose based on the action’s impact, who authorizes it, the identity and permissions it uses, and what evidence your platform retains.
What are the three ways to control an AI agent write?
“Agent writes” are not one control problem. A draft changes a preparation state; an approval gate pauses a particular action; and permission restrictions determine which actions the agent can perform at all. Audit records are a separate, after-the-fact control.
| Pattern | When it acts | What it helps answer | Important limitation |
|---|---|---|---|
| Draft first | Before external commitment | Can the agent prepare useful content without sending, submitting, deleting, or updating anything? | A draft is safe only if it cannot reach recipients or trigger downstream actions before review; not every connector or action has a draft state. |
| Approval gate | Immediately before a selected write runs | Who approves this action and its parameters? | Settings vary by app and action. A permissive configuration can allow writes without asking. |
| Restrict and audit | Permissions restrict actions before execution; logs record actions afterward | Which writes are unavailable, and can a later review identify the actor and event? | Logging does not block a write. Available controls and recorded fields differ across platforms. |
Assess actions by both impact and reversibility. Editing an internal work note is different from sending an external message, deleting a record, changing permissions, or provisioning infrastructure. The more consequential or difficult to reverse an action is, the stronger the case for withholding the capability or requiring a deliberate approval step.
Draft first: let the agent prepare, not commit
A draft-first design lets an agent create useful work while stopping short of changing externally visible state. Microsoft recommends allowing draft creation without external side effects, while treating actions such as send, submit, delete, or update as candidates for policy checks and often explicit user approval. Its guidance also describes a progression in which an agent can draft, summarize, classify, or recommend before it is permitted to write, send, delete, or provision: Microsoft’s access patterns and controls for AI agents.
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Do not assume “draft” is a universal platform feature. Check the specific connector and action. The practical test is whether the draft is isolated from recipients and downstream systems until a person, policy, or separate tool commits it. If saving a supposed draft triggers a workflow, publishes content, or notifies other people, it is not a harmless preparation step.
Approval gates: pause before a selected write executes
An approval gate lets the agent reach a write action but pauses execution so a person or policy can decide whether that action should run. The decision should apply to the actual operation and its parameters—not just the general idea of “allowing the agent.” Consider what content will be sent or changed, which record or destination is affected, and whether the action is reversible.
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How approval settings differ across apps
OpenAI’s Workspace Agents documentation says app and connector write actions default to “Always ask” during an agent run. Depending on the app, builders may also set write actions to “Never ask” or use a custom approval setting for particular writes. OpenAI cautions that write approvals deserve careful configuration for workflows that send, edit, post, or delete content: ChatGPT Workspace Agents for Enterprise and Business.
OpenAI’s admin guidance separates three layers: role controls who can use an app, Actions controls what it can do, and Permissions controls when ChatGPT asks before using it. Admins can enable supported read and write actions and set policy for new actions. Provider approval, OAuth scopes, and ChatGPT action settings are distinct checks; granting an OAuth scope alone does not enable a new action. Disabling new actions affects actions introduced later, not actions already enabled. Options vary across apps: OpenAI’s admin controls, security, and compliance guidance.
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Check policy before execution
Microsoft recommends checking the user, tenant, agent, tool, target resource, permissions, and approval requirement before a tool executes. For actions that change permissions or infrastructure, its guidance calls for a privileged workflow, audit logging, and human review. Approval is one layer of the control; it does not replace checking whether the agent and user are authorized to affect the target resource.
Restrict write capability and scope the agent’s identity
If a task only needs reading, drafting, or recommending, no write access is a valid configuration. Verify the actions actually enabled for the agent rather than relying on its natural-language instructions to avoid changes. A prompt asking an agent not to write is not the same as removing the capability to write.
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Identity determines whose authority the agent uses. Microsoft documents delegated permissions for an interactive agent acting on behalf of a signed-in user, and application permissions for an autonomous agent operating without a user present. These are different operating contexts, so assess which identity can reach the data and actions the agent needs. Microsoft also describes access packages whose grants can be revoked or expire, and recommends narrow resource scopes where possible: Microsoft’s guide to granting agents access to Microsoft 365 resources.
- Enable only the actions required for the agent’s task.
- Limit access to the relevant user, resources, or scope where the platform supports it.
- Distinguish user-delegated access from autonomous, application-level access.
- Use an expiry or revocation path for grants that should not persist indefinitely.
Use audit records and user-facing review to understand what happened
Auditability helps an administrator investigate an action; it does not prove that the action was approved or prevented. Check what the platform records, how long those records are available, and whether the record identifies the actor, session, target, and action in enough detail for your review process.
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What GitHub documents in its agent audit events
GitHub’s agentic audit event documentation identifies fields such as the action performed, whether the actor is an AI agent, an agent session identifier when an event results from a session, and the user who initiated it. Its streamed Copilot API usage records include a timestamp and event ID among other fields. GitHub documents this streamed feature as a public preview available to enterprises using Enterprise Managed Users and to GitHub Enterprise Cloud enterprises with data residency; that availability is not universal. See GitHub’s audit log events for agents.
Make actions legible to users
Slack’s developer guidance says identity-based agent actions should be visible and reviewable. It recommends labeling actions as “on behalf of [user],” clearly identifying autonomous content that has not been reviewed, and providing a review surface for people to inspect what the agent has done—particularly for asynchronous or bulk actions: Slack’s agent design guidance.
Inspect the administrative views you actually have
Microsoft 365 admin center documentation describes separate Data & tools, Permissions, Security, and Activity views. Tool listings may include actions that write data and merit closer review. The metadata shown varies by agent type and platform, and licensing conditions apply to the Security tab in the documented experience. Do not assume every administrator sees the same panels: Microsoft’s guide to agent details in the Microsoft 365 admin center.
How to choose a control for each action
- Classify the side effect. Decide whether the action only prepares a private draft, changes internal data, communicates externally, deletes information, changes access, or provisions infrastructure.
- Choose the execution boundary. Keep the work in a draft if the platform can isolate it. Require approval before high-impact writes. Remove write actions entirely when the task does not need them.
- Verify identity and scope. Establish whether the agent acts as a signed-in user or through autonomous application permissions, and narrow the resources it can affect.
- Confirm approval behavior. Check the setting for the specific app and write action, including any custom or “Never ask” configuration. Do not treat OAuth consent as equivalent to enabling an action or setting its approval policy.
- Plan the review trail. Confirm what events are logged, which identities and action details appear, and whether users have a way to review the agent’s activity.
These controls work best in combination: a narrow set of permissions limits the possible damage, an approval gate can stop selected writes before they run, and audit records and user-facing attribution help explain activity afterward. None should be mistaken for another.
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