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Clear out junk files and repair common Windows errorsFree Scan →Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →Repair Windows errors before they cause bigger problemsFix Now →Use delegated OAuth when an AI agent needs to act with a particular user’s authority; use a distinct workload or agent identity when it acts autonomously. These are not mutually exclusive: a workload identity can establish which agent is running, while OAuth or another supported authorization method controls what it may do at a target service. The right design depends on whose authority is needed, where the agent runs, and which flows the target supports.
How do OAuth and workload identity differ?
OAuth 2.0 is an authorization framework. It lets a client obtain credentials, commonly access tokens, to access a protected resource under defined authority. A user-delegated OAuth flow can carry a user’s consent and permitted scopes. A machine-to-machine OAuth flow can instead authorize a client acting under its own authority.
Workload identity is the identity assigned to running software: a service, job, or agent. Its proof may come from the cloud runtime or an external identity provider. The target system must still authorize that principal, for example through IAM permissions or a supported token-based flow. Workload identity answers “which workload is this?”; it does not, by itself, define what that workload is allowed to do.
| Decision axis | Delegated OAuth | Workload or agent identity |
|---|---|---|
| Whose authority? | A named user’s consent and permitted scope | The running workload or agent’s own principal |
| Typical task | Reading or changing resources for a user | Autonomous service-to-service work |
| Identity source | Authorization server and user consent | Runtime, cloud platform, or external identity-provider assertion |
| Credential handling | Access and possibly refresh tokens must be protected, scoped, and refreshed | Prefer platform-managed or federated short-lived credentials over static keys where supported |
| Attribution | Actions are associated with the delegated user and client context | Actions can be associated with the distinct workload or agent principal |
| Dependencies | The target API must support the appropriate OAuth flow and scopes | Runtime, federation trust, target IAM, and API support must align |
These are complementary design dimensions, not competing labels for the same mechanism. Google’s Agent Identity overview describes OAuth 3-legged and 2-legged flows, cloud identity, and OIDC federation as options for different authorities and targets.
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When should an AI agent use OAuth?
When it acts on behalf of a user
If the agent needs access to a specific user’s files, messages, or other resources under that person’s permissions, use a user-delegated flow. Google documents three-legged OAuth for external tools used with user authority; Microsoft documents an on-behalf-of pattern for agents. Grant only the scopes the task needs, and protect the resulting tokens as credentials. See Google’s Agent Identity guidance and Microsoft’s agent authentication protocols.
When it calls an external service using its own authority
Use the target service’s supported machine-to-machine mechanism. If the external service supports OAuth, Google recommends two-legged OAuth for this case; OIDC federation is another option for external backends in its guidance. Do not use a user-delegated token merely because it is available if the agent is meant to act independently.
Should an autonomous AI agent use a service account?
An autonomous production agent should have its own narrowly permissioned principal, rather than borrowing a developer’s broad identity. That principal might be a service account attached to a cloud workload, a managed identity on a supported runtime, or an agent-specific identity tied to the agent lifecycle. The available option depends on the platform and target. Google’s workload identity documentation describes workload identity patterns, while its Agent Identity overview covers agent identity options.
A service account is one possible workload identity, not a requirement for every agent. Prefer runtime-managed credentials where available, restrict permissions to the tasks and resources needed, and ensure logs identify the agent principal. Avoid sharing one identity across unrelated agents if that would make permissions or audit records difficult to separate.
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How can an agent access Google Cloud from an external or cross-cloud workload?
Where supported, use Workload Identity Federation to exchange credentials from an external identity provider for short-lived Google Cloud credentials. This can avoid distributing and managing service-account keys. Google calls federation “the preferred way to configure identities for external workloads” in its workload identity guidance. The trust configuration must match the external identity provider, and the resulting principal still needs appropriate permissions on the Google Cloud resources it accesses.
Static service-account keys carry additional handling risk. Google warns that keys can be a security risk if not managed correctly and advises choosing a more secure alternative whenever possible. If a key is unavoidable, its storage, access, rotation, and revocation need explicit controls.
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How do OAuth and workload identity work together?
A common design separates proof of the agent from authorization to a resource:
- Establish the agent principal. Give the running agent a distinct managed or federated identity so the platform or external identity provider can verify which workload is making the request.
- Choose authority for the action. If the task is user-specific, obtain user delegation through the target’s supported OAuth flow. If it is autonomous, authorize the workload’s own principal using the target’s supported machine-to-machine method or IAM.
- Grant only the needed access. Limit OAuth scopes or workload permissions to the required resources and actions.
- Make operations attributable and revocable. Confirm logs show the relevant user, client, or workload context, and establish how credentials, consent, trust, and permissions can be revoked when no longer needed.
The exact combination is target-specific: some APIs accept OAuth access tokens, some use cloud IAM, and some support federation or a combination. An identity mechanism that works for the agent runtime does not guarantee that every tool or API can consume it.
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What security controls should an agent’s OAuth flow use?
The IETF’s RFC 9700, Best Current Practice for OAuth 2.0 Security, was published in January 2025. It states that public clients must use PKCE, recommends PKCE for confidential clients, and recommends asymmetric client authentication, such as mutual TLS or signed JWTs, where feasible. It also recommends sender-constrained access tokens, such as those using mutual TLS or DPoP, to reduce misuse of stolen tokens.
These controls address different risks: PKCE protects authorization-code flows from code interception, asymmetric authentication avoids relying on a shared secret in applicable client setups, and sender-constraining can make a stolen token harder to use elsewhere. Which controls are available depends on the client, authorization server, and resource server; verify support rather than assuming every target implements them.
What should you check before choosing an agent identity pattern?
- Authority: Does this action need a particular user’s consent and access, or should it be performed under the agent’s own permissions?
- Target support: Which OAuth grant or machine-to-machine flow, scopes, IAM roles, federation methods, and token types does the API actually accept?
- Runtime and trust: Can the agent obtain a managed identity or federated assertion from its environment, and is the trust relationship limited to the intended workload?
- Least privilege and separation: Are production agent permissions distinct from a developer’s, and are separate agents isolated where their jobs require different access?
- Credential lifecycle: How are tokens renewed, identities rotated or replaced, and access revoked after a user disconnects or an agent is retired?
- Auditability: Do logs preserve enough context to determine whether an action came from a user-delegated session or the agent’s own principal?
Platform documentation illustrates patterns rather than guaranteeing universal compatibility. Google notes that MCP credential methods vary by client application; its remote servers do not support Dynamic Client Registration or OAuth Client ID Metadata Documents. Check the specific MCP client and server behavior in Google’s MCP authentication documentation before designing around either capability.
For broader identity-federation context, NIST’s SP 800-63C-4, Digital Identity Guidelines—Federation and Assertions, published August 1, 2025, covers federation and assertions generally; it is not an AI-agent-specific comparison of OAuth and workload identity.
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