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Give the agent its own stable identity, then authorize each request according to the principal it represents. Use delegated, user-context permissions when a signed-in person is asking the agent to access that person’s data; use a dedicated service identity with narrowly scoped application permissions for autonomous work. Enforce those rights at the downstream resource or policy layer, preserve both identities in the audit trail, and make every grant short-lived or revocable where the platform allows it.
Start with the principal, not the model
An AI model does not become an authorized user merely because a prompt names one. Authorization begins by answering a business question: whose data or capability is being used, and who is accountable for the action?
When a person is present
If a signed-in employee asks an agent to search their mailbox, update their files, or submit a request for them, the employee remains the data principal. The agent is a separate actor operating with delegated authority. The request should carry verifiable user context so the downstream service can apply that person’s existing rights, consent, policy restrictions, and tenant boundaries.
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A scheduled report, event-triggered workflow, monitoring task, or background remediation has no interactive user to delegate from. Give it a dedicated application or service identity. That identity should have only the permissions needed for the defined workflow, not the broad role of an administrator or an employee account.
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When both are involved
Many production workflows mix the two modes. A user may start a job, while a worker continues it later against organization-owned data. Decide explicitly which operations remain user-delegated and which are performed by the service identity. Do not silently convert a user request into an unrestricted background grant.
Choose the authorization pattern that matches the work
Delegated access, on-behalf-of exchange, and machine-to-machine access are complementary patterns. An agent can use different patterns for different resources, provided each call has a clear principal and audience.
| Pattern | Use it when | Permission basis | Design check |
|---|---|---|---|
| User-delegated access | A signed-in person requests work on user-specific data and can provide consent. | User-approved delegated scopes, limited to the required operations. | The downstream service must enforce the user’s actual rights; the agent must not receive a broader role than the person. |
| On-behalf-of token exchange | The person has already authenticated to the agent and a downstream API needs that person’s identity context. | An inbound token is exchanged for an audience-specific token carrying user and agent context. | Validate the audience and downstream policy. The agent is acting for the user, not becoming the user. |
| Machine-to-machine or application access | The agent runs autonomously or accesses organization-owned resources without an interactive user. | Pre-approved application permissions attached to the agent’s dedicated identity. | Use minimum application permissions and avoid broad tenant-wide write or control rights. |
AWS documentation describes user-delegated authorization-code access, client-credentials access for machine-to-machine calls, and on-behalf-of token exchange as distinct choices. The right choice depends on data ownership, whether a user is present, how long the task runs, and whether the next service needs the already-authenticated user’s context.
Represent the user and the agent as different identities
Use a stable identity for the agent even when every action is initiated by a person. That identity can be a workload identity, service principal, or equivalent non-human principal in the identity platform. It should have its own credentials, lifecycle, owner, and disablement path.
For delegated calls, carry the user context as signed claims rather than giving the agent the user’s password, refresh token, or reusable secret. The AWS Agentic AI Lens describes this model as propagating user context through signed token claims without the agent assuming the user’s credentials. The downstream service can then evaluate both the represented user and the calling agent.
What the token should make distinguishable
- Agent identity: which workload or application made the call.
- Represented user: the signed-in person, when the operation is delegated.
- Audience: the specific API or resource for which the token was issued.
- Granted scope or role: the operations the token allows.
- Tenant or organizational context: the boundary in which the request is valid.
- Lifetime and issuance data: when the credential becomes invalid and which authorization event produced it.
In Microsoft token terminology, delegated permissions are represented in the scp claim, while application permissions appear in the roles claim. Treat those claims as input to authorization, not as a replacement for resource-level policy checks.
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Define a task boundary before granting a scope
Write down the task the agent is allowed to perform before selecting permissions. A useful boundary specifies all of the following:
- Actions: read, create, update, send, delete, approve, or administer.
- Resources: named mailboxes, sites, queues, repositories, teams, databases, or API routes.
- Data classes: for example, support tickets but not payroll records.
- Tenant and ownership limits: which organization, customer, project, or account can be touched.
- Time window: one interactive request, a scheduled run, or a defined expiration date.
- Human checkpoints: actions that require confirmation or a separate approval.
- Rate and volume limits: caps that reduce the effect of a loop, prompt injection, or coding error.
Translate the boundary into the narrowest available permission. “Manage Microsoft 365” is not a task boundary; “read messages in the support mailbox and create draft replies” is. If the platform cannot express a required restriction, add a policy enforcement point in front of the resource rather than relying on instructions in the prompt.
Enforce permissions where the resource is protected
The model’s system prompt, tool description, and orchestration code are useful safeguards, but none is an authorization boundary. A compromised tool call, prompt injection, workflow bug, or chained action can bypass conversational intent. The downstream API, gateway, database policy, or resource server must make the final allow-or-deny decision.
Apply role assignments at the smallest resource scope
Microsoft guidance recommends assigning Azure roles at the narrowest relevant scope instead of at the tenant or subscription level by default. Prefer a resource, resource group, project, or operation-specific assignment when that is sufficient. A role that permits write access to one storage account is materially safer than the same role at an entire subscription.
Use mailbox-level controls for Exchange access
If an autonomous agent needs Exchange data, constrain application access to the mailboxes required by the workflow. A tenant-wide mailbox grant can expose unrelated personal, legal, financial, or executive correspondence. Keep the mailbox set explicit and review it when ownership or workflow responsibility changes.
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For Teams automation, resource-specific consent can limit access to particular teams rather than granting access across the tenant. This is especially important for agents that summarize, post, or moderate conversations in only a subset of teams.
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Separate read, write, and high-impact operations
Do not bundle read, send, delete, approval, and administrative capabilities merely because one tool exposes them together. Create separate tools or policies where possible. A support agent may read a ticket and prepare a draft while a human must approve sending it. A deployment agent may inspect a release but require a separate, time-limited permission to promote it.
Request consent without turning consent into a blank check
Delegated authorization normally requires the appropriate user or administrator consent. Ask for only the scopes required for the current feature, explain the data and actions they enable, and avoid requesting a future-proof bundle “just in case.” A consent screen is not a substitute for resource-level authorization: a user can approve a scope that still must be narrowed by policy, ownership, or tenant rules.
For organization-wide background work, obtain administrator approval for the application identity through the organization’s normal change process. Record the business owner, purpose, resources, expiry or review date, and rollback procedure. If a permission is temporary for a pilot, make its expiration explicit rather than relying on someone to remember to remove it.
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Interactive delegated authorization
Use an authorization-code-style flow when a person is present and the agent needs access to that person’s data. The authorization server authenticates the user, obtains the required consent, and issues a token for the intended API. The agent should pass that token or a securely exchanged derivative to the downstream service without collecting the user’s password.
On-behalf-of exchange
Use token exchange when the user has authenticated to an intermediate agent or API and a second service must receive a token for its own audience. Validate the incoming token, exchange it only for the downstream audience, and preserve claims that identify both the user and the calling agent. Do not forward a token intended for one API to another API.
Client credentials or equivalent application access
Use an application flow for an autonomous worker. The token represents the agent’s application identity and its approved roles, not an employee. Give the worker a dedicated credential or workload identity, keep tokens short-lived where supported, and rotate or disable the identity independently of human accounts.
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Mixed workflows
A single workflow may legitimately use an interactive token to read a user’s private document and an application token to write an organization-owned audit record. Keep those calls separate, make the change of principal visible in logs, and never assume that permission in one token carries over to the other.
Implementation procedure
- Classify the trigger. Record whether a signed-in person initiated the action, whether the action continues after the session ends, and whether a service event can trigger it independently.
- Name the principals. Assign the agent a stable identity. For delegated work, identify the user separately; for autonomous work, identify the service owner and business purpose.
- Map the data owner. Mark each target as user-owned, team-owned, tenant-owned, or customer-owned. Ownership determines whether delegated or application access is appropriate.
- List operations individually. Separate read, create, update, send, delete, approval, and administration. Remove any operation the task does not require.
- Choose the token pattern. Select delegated access, on-behalf-of exchange, application access, or a combination. Define the expected audience for every downstream call.
- Set the narrowest resource scope. Apply resource-level roles, mailbox restrictions, per-team consent, project policies, or equivalent controls. Avoid tenant-wide grants unless the task genuinely requires them and the business owner accepts the exposure.
- Put authorization in the resource path. Require the API, gateway, database, or policy engine to validate identity, audience, scope, tenant, ownership, and action before execution.
- Record consent and ownership. Store who approved the grant, its purpose, affected resources, review date, and escalation contact.
- Test denial paths. Attempt access to a different user’s data, an unlisted mailbox, an unapproved team, a disallowed operation, and an expired token. Each should fail before the action reaches the resource.
- Deploy with monitoring. Start with conservative quotas and alerts for unusual volume, new resources, privilege changes, failed authorization, or a sudden switch from delegated to application access.
Make every action attributable
An audit record should answer “which agent did what, for whom, against which resource, under which permission?” At minimum, capture the agent identity, represented user when applicable, action, resource identifier, effective scope or role, result, timestamp, and correlation identifier. Keep the original request or job identifier when policy permits, but do not place sensitive prompt content in logs by default.
For a delegated action, the log should not collapse the identities into a single username. A useful event distinguishes the actor that called the API from the person whose authority or data was used. For an autonomous action, record the service identity and the scheduled job, event, or change ticket that authorized the run.
{"agent":"support-summary-worker","represented_user":"user-4721","action":"create_draft","resource":"mailbox/support","scope":"mail.readwrite.draft","audience":"mail-api","correlation_id":"job-8f31"}The exact field names depend on the platform. The important property is that an investigator can distinguish the agent, the represented principal, the permission used, and the resource affected.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Design revocation and credential hygiene from the beginning
Least privilege is not a one-time configuration. AWS guidance recommends minimum task permissions, short-lived credentials, and regular review. Microsoft guidance likewise calls for reviewing effective permissions, testing revocation, and reassessing access when tools or workflows materially change.
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- Disable the agent identity: verify that new calls fail and that queued work cannot obtain fresh tokens.
- Invalidate issued tokens: test token revocation or expiry behavior for both delegated and application flows.
- Remove resource grants: confirm that a deleted mailbox, team, project, or role is no longer reachable.
- Rotate secrets: replace client credentials and signing keys without creating an overlapping, untracked identity.
- Review effective access: inspect the union of direct roles, group membership, inherited roles, tool permissions, and policy exceptions.
- Re-test after change: changing a tool, workflow branch, data connector, or model can create a new path to an old permission.
Run these tests during deployment and on a schedule. A grant that is narrow in isolation can become broad when combined with another role or tool.
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Common designs that fail
| Failure | Why it is dangerous | Better design |
|---|---|---|
| Reusing a human account | Actions are hard to attribute, employee changes can break the agent, and revocation may remove unrelated access. | Create a dedicated agent identity and retain user context through delegated claims when a person is represented. |
| Sharing a static key among agents | There is no reliable per-agent attribution, and one leak can expose every workflow using the key. | Use separate workload identities, short-lived credentials, and independent rotation. |
| Granting tenant-wide access to unblock a pilot | The temporary shortcut becomes persistent privilege creep and exposes resources unrelated to the task. | Start with named resources, an expiry or review date, and an explicit expansion process. |
| Treating the prompt as the security boundary | Prompt injection, a tool bug, or chained calls can request operations the model was told not to perform. | Enforce action and resource policy at the API, gateway, database, or service boundary. |
| Making the agent assume the user’s full role | The agent inherits unrelated permissions and the audit trail blurs the human and workload. | Carry signed user context and authorize the specific downstream operation. |
| Checking only direct grants | Inherited roles, group memberships, and multiple tools can create effective access wider than any single grant. | Review the complete effective permission set and test cross-resource combinations. |
Worked design examples
A personal inbox assistant
A user asks an interactive agent to find travel confirmations in their mailbox and draft a reply. The agent uses delegated access limited to the user’s mailbox and the operations needed to read messages and create drafts. Sending remains a separate operation requiring the user’s confirmation. The mail service checks the user’s rights and the token audience; the audit event records both the agent and the represented user.
A nightly compliance report
A scheduled worker reads records from a defined set of organization-owned repositories and writes a report to a controlled storage location. No employee is present, so the worker uses application permissions from its own identity. Repository access is limited to the named sources, write access is limited to the report location, and the job cannot delete source records. The schedule, service identity, and report destination are recorded for each run.
A support triage workflow
An employee starts a triage job, but a background worker continues processing tickets after the employee signs out. The initial ticket lookup can be delegated if it uses the employee’s permitted customer accounts. Queue processing that belongs to the support organization uses a separate application identity. The handoff is explicit: logs show when authority changes, and the worker cannot use the employee’s private data unless a new delegated authorization is obtained.
A multi-service approval chain
An agent receives a request through an internal API, calls a policy service, and then invokes a deployment service. The inbound user token is not blindly forwarded. The agent validates it, obtains an audience-specific token for each downstream service, and preserves the user and agent identities in the exchange. The deployment service performs its own authorization and requires a separate approval claim for production changes.
Verification checklist before production
- Is there a dedicated, named identity for every agent or materially different workload?
- Can you state whether each operation is user-delegated or application-owned?
- Are user and agent identities both present in downstream authorization and logs?
- Does every token target the correct audience and carry only the needed scope or role?
- Are permissions limited to named resources, teams, mailboxes, projects, or API operations?
- Can the resource deny a request even if the model asks for it?
- Have you tested another user’s data, an unlisted resource, a disallowed action, an expired token, and a revoked grant?
- Are short-lived credentials, rotation, disablement, and ownership documented?
- Do alerts detect unusual volume, privilege changes, failed checks, and unexpected resource access?
- Is there a review trigger when a tool, workflow, connector, model, or data class changes?
Standards and platform guidance to keep in view
Microsoft Learn guidance on granting agents access to Microsoft 365 resources distinguishes delegated permissions for interactive agents from application permissions for autonomous agents. Its least-privilege guidance also emphasizes dedicated agent identities, effective-permission review, downstream checks, audit fields, and revocation testing.
The AWS Agentic AI Lens covers separate identities, signed propagation of user context, minimum task permissions, short-lived credentials, and permission-drift review. AWS documentation for Bedrock AgentCore describes delegated, client-credentials, and on-behalf-of patterns and the conditions that favor each.
The IETF WIMSE material on AI-agent authentication and authorization provides standards-oriented context for OAuth-based delegation and token exchange, but it is interim working-group material rather than a finalized agent-authorization standard. Treat platform behavior as version- and service-specific, and verify the current token claims, resource scopes, consent model, and revocation behavior in the services you deploy.
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The practical decision
If a person owns the data and is actively asking for help, use delegated authorization that preserves the person’s identity while keeping the agent distinct. If a service, schedule, or event owns the work, use a dedicated application identity with the smallest possible permissions. In both cases, put the final decision at the resource boundary, log the agent and represented principal separately, and make grants reviewable and revocable. That combination limits what the agent can do, makes misuse diagnosable, and prevents a conversational tool from silently acquiring the authority of a human or an entire organization.
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