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Ping Identity and Google Cloud both document ways to give AI agents identifiable, controlled access, but they solve the problem from different platform centers. PingOne focuses on OAuth agent identities and delegated user access; Google Cloud focuses on SPIFFE-based agent identities for supported runtimes, IAM access to Google Cloud resources, and credential brokering for external tools. The better fit depends on where agents run, whose authority they need, and how you want to constrain and audit access—not on a universal winner.
What is the main difference?
PingOne treats an agent as a first-class OAuth 2.0 identity that administrators can manage and that can exchange tokens to act for a consenting user. Google Cloud’s Agent Identity is a cryptographic, SPIFFE-based identity associated with the resource hosting an agent; Google pairs it with IAM for cloud resources and an auth manager for credentials used with external tools.
These are related capabilities, not identical product architectures. Ping’s materials emphasize identity lifecycle, delegated authority, and gateway controls. Google’s emphasize runtime-bound identity, IAM principals, and credential handling for outbound calls. The documentation reviewed on October 4, 2026 supports a capability comparison, not an independent security or performance ranking.
How does Ping Identity’s agent approach work?
Agent identity and administration
PingOne defines AI agents as non-human identities and documents registering them as OAuth 2.0 identities. Administrators can onboard, enable, update, or disable identities and manage their owners, authentication, and resource access. Ping’s AI Agents documentation says these capabilities require the Agent IAM Core solution package.
Delegating a user’s authority
Ping describes delegation as distinct from impersonation. The agent presents the user’s access token as a subject token and its own client credentials as an actor token. PingOne evaluates the agent, user consent, and requested scopes, then issues a downscoped token. The user’s credentials are not handed to the agent in this documented flow.
A downstream service can use the token’s act claim to identify the acting agent, but Ping says this claim is not included by default; it must be enabled through attribute mapping. That distinction matters if an organization expects logs or services to distinguish the agent from the user automatically.
Constraining actions and adding approval
Ping describes short-lived delegation tokens, audience restrictions, and resource and scope mappings for APIs and MCP servers as least-privilege controls. Its materials also describe pausing high-risk requests for real-time human approval, including with CIBA. These are configurable patterns, not guarantees that a deployment will enforce them without policy and integration work.
Ping’s management documentation lists OAuth/OIDC grant types including Authorization Code, Client Credentials, CIBA, Device Authorization, Refresh Token, and Token Exchange. It also describes optional PingFederate integration for workforce MFA through a PingID adapter. Available capabilities depend on the product package, environment, and configuration.
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Related Ping products and MCP integration
PingOne Advanced Identity Cloud has a separate agent identity and privilege API path, with its own feature enablement, token-exchange prerequisites, and API scopes. Do not assume that its API and schema model matches the PingOne console and Agent IAM Core package model; identify which Ping product your organization uses.
Ping’s Identity for AI solution guide describes PingGateway filters for protecting MCP endpoints, validating requests, and recording audit trails, as well as reference integrations with external AI platforms and MCP servers. These examples show integration patterns; they do not establish that every integration is turnkey or included in every license. A Ping release note dates Identity for AI general availability to March 31, 2026; that date applies to the release note, not necessarily every related feature.
How do Google Cloud’s native agent identity tools work?
Runtime-bound identity and Google Cloud IAM
Google describes Agent Identity as a strongly attested cryptographic identity based on SPIFFE and associated with the resource hosting the agent. Its overview names Gemini Enterprise Agent Platform Runtime (Agent Runtime), Gemini Enterprise, and Cloud Run as supporting services. Because support can depend on the current runtime and feature matrix, verify that the exact service and deployment you plan to use are covered.
An agent identity can be granted access to Google Cloud resources through IAM principal identifiers. For a Vertex AI Agent Engine deployment, Google documents configuring identity_type=AGENT_IDENTITY and assigning appropriate roles to the agent principal. This provides a direct IAM route for resources the agent should access; the roles you grant determine its effective permissions.
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Credentials for external tools
Google’s Agent Identity auth manager addresses outbound authentication that is separate from Google Cloud IAM. Google describes it as a centralized credential vault and authentication broker that can store API keys, OAuth client secrets, and user tokens; manage OAuth consent, authorization-code exchange, and refresh; and work with the Agent Development Kit to inject authentication headers into tool and MCP requests.
For Cloud Run, Google documents using agent identity credentials to reach Google Cloud APIs and the auth manager for external services and more involved OAuth or API-key flows. In practice, an agent may need both: an IAM principal for native cloud resources and separately managed credentials for third-party tools.
Choosing whose identity an MCP request uses
Google’s MCP guidance distinguishes user, workload, and agent identities. If a client uses a person’s identity, requests inherit that person’s permissions and are attributed to them. Google recommends a separate agent or workload identity for production when appropriate, so access can be limited and requests can be viewed in logs. The right option still depends on the runtime and target service; service accounts and workload identity federation remain relevant alternatives.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How do the documented approaches compare?
| Decision area | Ping Identity | Google Cloud |
|---|---|---|
| Identity model | First-class OAuth 2.0 agent identity managed in PingOne; AI agent capabilities require Agent IAM Core. | SPIFFE-based Agent Identity associated with a supported hosting resource. |
| Agent’s own access | OAuth authentication and configured resource and scope access; details depend on configuration. | Grant IAM roles to the agent principal for Google Cloud resources. |
| Acting for a user | Documented token exchange uses the user token as subject and agent credentials as actor, producing a downscoped token. | Auth manager supports user-token and OAuth flows; exact behavior depends on integration. |
| External tools and MCP | Resource and scope mapping, gateway protections, and reference MCP integrations are documented. | Auth manager brokers external credentials; Agent Development Kit integration can inject authentication headers. |
| Attribution and approval | The act claim can identify the agent when configured. CIBA-based approval patterns are documented. |
Identity and logging guidance is documented; a directly equivalent human-approval workflow is not established in the cited materials. |
| Pricing comparison | Not stated in the cited Ping product documentation. | Not stated in the cited Google Cloud documentation. |
How should you choose between them?
- Start with the runtime. Map where each agent runs: a Google-supported runtime, Cloud Run, another cloud, or on-premises. Google’s native Agent Identity is tied to supported Google-hosted services. Ping’s materials describe identity and gateway patterns across customer and workforce scenarios, including external platform integrations. Confirm exact architecture support with the vendors.
- Separate agent authority from user delegation. Decide whether a task should use the agent’s own service permissions or needs a specific user’s authority. For delegated actions, inspect how consent is obtained, which scopes are requested, how long tokens last, and how access is revoked in the actual integration.
- Match permissions to the target. Compare Ping’s audience, scope, and resource controls with the granularity of your APIs and MCP services. For Google Cloud resources, review the IAM roles granted to the agent principal and whether they can be limited to the required resources.
- Trace every external credential. For each API or MCP tool, identify where its secret or user token is stored, who can administer it, how it is refreshed or rotated, and what appears in logs. Cloud IAM access alone does not settle authentication to third-party services.
- Test attribution and approval requirements. Decide what downstream services and audit records must show about the agent and the user. If you use Ping’s
actclaim, configure and verify it. If a high-risk action requires human approval, confirm that the chosen workflow enforces approval at the point of action. - Check entitlement and availability. Confirm Ping package eligibility and Google runtime, region, and feature availability against your organization’s current contracts and deployment plans. The cited documentation does not provide comparable total-cost figures, so request current quotes rather than inferring a cost winner.
What should a production design verify?
- Every agent has a distinct identity rather than relying by default on a person’s broad credentials.
- Permissions are bounded to the resources, audiences, scopes, and tools needed for the task.
- User consent, delegation, token lifetime, and revocation work as intended in the deployed flow.
- External API credentials have a defined owner, storage location, rotation process, and access policy.
- Logs can distinguish the agent, the user when applicable, and the resource or tool accessed.
- Any required human approval is enforced and recorded, rather than treated as an optional operational convention.
These checks are implementation questions, not claims that either vendor automatically satisfies them in every deployment. The reviewed materials are vendor product and implementation documentation, not an independent assessment.
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