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Give an AI agent a separate, attributable workload identity and narrowly delegated authority—not your password, session cookie, or a broad API key. The identity should identify the running agent, record which person or organization delegated the task, constrain what the agent may do, and produce evidence that can be revoked and audited. A user account identifies a principal; an agent identity identifies a workload acting under delegated authority.
This distinction matters because an agent can operate at machine speed, call several tools in sequence, and continue running after the person who started it has left the screen. If it uses a human’s credentials, every action looks like the human acted directly. If it uses an unscoped bearer secret, anyone who obtains that secret can reuse it. A proper design keeps the agent useful while preserving accountability and limiting damage.
What an AI agent identity actually represents
An agent identity is more than a username attached to a bot. It is a runtime identity plus a documented delegation and a set of constraints. At minimum, the record should bind five things:
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- Agent workload: a unique identifier and credential for the running agent or service.
- Runtime context: where it runs, which deployment and software build it uses, and—when available—attestation of that environment and its supply chain.
- Authority: the resources, actions, audience, purpose, spending or data limits, expiry time, and maximum delegation depth.
- Evidence: the policy decision, consent or approval, tool calls, outputs, provenance, and later revocation events.
The identity can be short-lived and tied to one job. A long-running assistant may receive a renewable workload credential, but each renewal should be subject to current policy rather than silently extending the original permission. If an agent creates a child agent, the child should have its own identifier linked to the parent and the original delegating principal, with no greater authority than the parent.
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“For organizations to have confidence in transactions, agents need to be treated like first-class entities with their own unique identifiers, credentials, and associated entitlements that are bound to and by the identity of the user or system operating the agent.”
Bill Fisher and Ryan Galluzzo, National Institute of Standards and Technology, 2026
Why sharing a user account fails
It erases non-repudiation
When an agent uses a person’s password, OAuth session, or browser cookie, the service sees the person’s principal. A later audit cannot reliably distinguish a human click from an automated decision. The user may be blamed for an action they did not understand, while the operator cannot prove which model, prompt, tool, or deployment produced it.
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It grants accidental power
Desktop sessions, repository accounts, and ordinary employee roles often include permissions accumulated for many unrelated tasks. An agent that can read the whole drive, modify every branch, or send mail as the user can discover and act on paths the user never intended to expose. Machine-speed iteration makes an overbroad permission materially more dangerous.
It makes containment difficult
Changing a user’s password or invalidating all sessions disrupts the human and may still miss copied keys. A separate agent credential can be disabled without resetting the person’s access. You can also stop one workload while leaving other agents operated by the same team intact.
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Identity and authorization are different layers
Identity answers “which workload is this?” Workload identity systems such as SPIFFE and SPIRE can issue cryptographically verifiable identities to services and jobs. The verifier can authenticate the workload without trusting a name supplied in a request.
Authorization answers “what may it do here and now?” OAuth 2.0, token exchange, and related delegation mechanisms can express that a particular agent is allowed to perform a particular action for a particular audience. A policy engine can further evaluate the resource, action, context, intent, risk, and approval state.
These layers should be joined, not substituted. A valid workload credential does not authorize deletion of a database. Conversely, a bearer token that grants an operation does not prove which workload possessed it when the operation occurred. Bind the authorization decision to the authenticated workload and to the delegating principal.
A practical identity and authority model
| Question | Record or control | Example constraint |
|---|---|---|
| Who is responsible? | Delegating principal and organizational scope | A finance team approves invoice reconciliation |
| Which agent is acting? | Unique workload identifier and credential | agent://finance/reconcile/prod/job-1842 |
| Where and what is running? | Deployment, version, attestation, and supply-chain metadata | Production cluster, signed build, approved tool list |
| What is allowed? | Resource, action, audience, purpose, limits, and expiry | Read invoices and prepare drafts; no payment submission |
| Can it delegate? | Delegation depth and child-scope rules | One child allowed, with read-only authority |
| What proves the decision? | Policy result, approval, tool calls, outputs, and receipts | Signed decision and immutable event chain |
This model lets a resource owner make a decision using more than a subject name. For a high-impact action, policy can require a specific intent, a fresh approval, a spending ceiling, a known deployment, and a sender-constrained credential. The same agent may be allowed to read data in one audience and denied access when it presents the credential to another.
Where current standards fit
There is no finished, universal “AI agent identity” standard. NIST’s 2026 public-comment summary describes an emerging compositional standards stack, with different pieces at different maturity levels. Treat protocol integrations as parts of that stack rather than as a complete identity system.
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| Layer | Mechanisms | What to verify |
|---|---|---|
| Workload identity | SPIFFE/SPIRE; WIMSE drafts | Is the identity cryptographically bound to the workload and portable across environments? |
| Delegated authorization | OAuth 2.0, token exchange, identity chaining | Can authority be delegated and attenuated without inheriting all user rights? |
| Fine-grained policy | Rich Authorization Requests, AuthZEN, Cedar, OPA, NGAC | Can decisions include resource, action, context, intent, and risk? |
| Runtime authentication | mTLS, HTTP signatures, attestation, DPoP | Are credentials sender-constrained and resistant to replay? |
| Revocation and signals | OpenID Shared Signals, CAEP, RISC | Can a long-running agent lose authority quickly after compromise or policy change? |
| Evidence and provenance | SCITT, tamper-evident logs, cryptographic receipts | Can an auditor reconstruct delegation, purpose, decision, and execution? |
| Interoperability | MCP for tools and resources; A2A for agent collaboration | Are integrations carrying identity and policy rather than pretending to replace them? |
How to implement an agent identity safely
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Inventory the agent’s real work
List every tool, data store, API, irreversible operation, and external party. Separate reading, drafting, changing, deleting, sending, and spending. Mark actions that create legal, financial, safety, privacy, or reputational impact. Decide which actions can be automatic and which require a transaction-specific approval.
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Create a distinct workload identity
Register the agent as a workload, not as a human. Issue a unique identifier and a key or certificate that the runtime can prove it controls. Bind the identity to its deployment and environment where your platform supports that binding. Do not copy a user’s password, browser cookie, SSH key, or personal access token into the agent.
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Bind it to the delegating principal
Record who authorized the job, for which purpose, and under which organizational policy. The delegation should be machine-readable so a downstream service can verify the chain instead of trusting a free-text claim in a prompt. If a team delegates, retain both the team identity and the approving person or workflow.
-
Issue short-lived, audience-restricted authority
Use token exchange or an equivalent mechanism to mint a credential for the specific resource audience. Limit actions, objects, purpose, time, spend, data volume, and delegation depth. Prefer a credential that expires after the job or a short interval and must be renewed under current policy. Static API keys and long-lived bearer tokens are poor defaults because possession is enough to reuse them and they are easily exposed in files, environment dumps, tickets, or logs.
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Enforce policy at every tool boundary
Do not rely on the agent’s planner to obey a system prompt. Each tool or resource should authenticate the workload, evaluate the delegation chain, and make its own allow, deny, or approval-required decision. Include transaction context such as the target object, requested operation, stated purpose, risk signals, and whether the action is reversible. A tool server should reject an agent that presents a valid identity but an audience, scope, or intent outside policy.
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Add attestation and sender constraints where possible
When the platform supports it, require evidence about the image, host, runtime, or software build. Use mutual TLS, proof-of-possession, HTTP signatures, or DPoP-style mechanisms so a stolen token cannot be replayed from an unrelated process. Attestation is an additional signal, not a replacement for authorization: an approved build can still request an unapproved action.
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Capture the complete authority chain
Log the original request, delegating principal, agent and child identities, policy inputs and result, approvals, credential issuance, each tool call, returned data, model or software version, and execution outcome. Use tamper-evident storage and cryptographic receipts where the action requires non-repudiation. An entry containing only a timestamp and final API call cannot explain why the call was allowed or what the agent was trying to accomplish.
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Build rapid revocation and continuous evaluation
Provide an operator control that revokes the agent, its children, and outstanding delegated credentials without waiting for their normal expiry. Subscribe to security and account-change signals when available. Re-evaluate long-running jobs after policy changes, unusual behavior, loss of approval, or a change in the user’s status. Test that revocation reaches every tool, queue, and worker, not just the identity issuer.
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Test each deployment path separately
A cloud service, container, local desktop process, MCP-connected tool, and multi-agent workflow have different trust boundaries. Verify credential storage, identity propagation, audience checks, logging, and revocation on each path. A design that is safe in a managed cluster may expose a local agent’s token through a shared filesystem or an untrusted plug-in.
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Common failure modes and the corrective design
| Failure | Why it happens | Correction |
|---|---|---|
| Credential sharing | It is the fastest way to make an integration work, but every action impersonates the user. | Issue a workload credential and record explicit delegation. |
| Long-lived API key | Bearer possession is treated as proof of identity; the key is copied into code or logs. | Use short-lived, scoped, audience-bound and, where practical, sender-constrained credentials. |
| Local user account | The agent inherits desktop, repository, or cloud permissions that were never designed for automation. | Create a dedicated workload identity with separate data and action scopes. |
| Overbroad scope | “Read/write everything” avoids early integration work. | Split read, draft, approve, send, and delete permissions; add resource and volume limits. |
| Approval fatigue | Prompts appear for every low-risk action, so users click Allow without understanding the consequence. | Use policy for routine low-risk work and reserve clear, transaction-specific approvals for consequential actions. |
| Outcome-only logging | Teams log the final API response but not the authority chain or intent. | Store delegation, policy inputs, approval, tool sequence, outputs, and provenance in tamper-evident records. |
Agent identity versus a traditional service account
A service account is usually a non-human principal created for an application or scheduled process. It is a useful foundation, but it is not automatically an agent identity. Traditional service accounts often have a stable name and a standing role; they may not record which human delegated a particular run, what the agent intended, which model version made the decision, or whether a child agent was created.
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An agent identity adds per-run or per-workload attribution, delegated authority, runtime context, intent and risk conditions, and evidence of execution. You can implement this by layering delegation and short-lived credentials over an existing service-account system, or by using workload identity directly. The test is practical: can you answer which exact workload acted, on whose authority, under which policy, with which credential, and can you revoke that authority without disabling unrelated work?
Example: an invoice agent that cannot pay invoices
Suppose an employee asks an agent to reconcile invoices. The employee is the delegating principal. The running job receives a unique workload identity tied to the approved production deployment. Its exchanged credential is valid only for the invoice service, expires soon, and permits reading invoices, matching purchase orders, and writing a reconciliation draft. The payment endpoint is a different audience and is outside the token’s scope.
For an exception, the agent submits a structured intent containing the invoice, amount, reason, and proposed action. Policy may require a human approval for an amount above a threshold. The approval, policy result, tool calls, returned records, and final draft are recorded with the delegation chain. If the deployment is compromised, an operator revokes the workload and its outstanding tokens; the employee’s normal account remains usable.
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- Can every tool identify the workload cryptographically rather than trusting a caller-supplied name?
- Can a verifier see the delegating principal and the exact limits, audience, purpose, and expiry?
- Are high-impact operations separated from harmless reads and drafts?
- Would a leaked credential be unusable from another sender, audience, or environment?
- Can an auditor reconstruct the request, approval, policy decision, tool sequence, outputs, and software context?
- Can security staff revoke one agent, its child agents, and queued work quickly?
- Have local, cloud, container, tool-protocol, and multi-agent paths been tested independently?
Standards and implementation guidance are still developing. Core workload identity and OAuth mechanisms are operational foundations, while WIMSE and several agent-focused profiles continue to evolve. Revisit the profile as guidance for tool and agent protocols, continuous signals, and production evidence becomes more mature.
The bottom line
Do not make an AI agent “log in as you.” Give it a distinct workload identity, then delegate only the authority required for a defined task. Authenticate the workload, authorize each action at the resource boundary, constrain and expire its credentials, capture the full delegation and execution evidence, and make revocation routine. That architecture answers both questions a trustworthy system must satisfy: which agent acted? and why was it allowed to act?
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