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07/06/2026 8:45 pm
TL;DR: AI agents are increasingly being authenticated with OAuth 2.0 and OpenID Connect, but the real issue is not login mechanics, it is whether scoped tokens, rotation, auditability, and tenant isolation can contain machine-speed behaviour, according to WorkOS. Access review processes assume access persists long enough to be reviewed; autonomous actors can chain actions faster than governance cycles can observe them.
NHIMG editorial — based on content published by WorkOS: The best providers for authenticating AI agents via OAuth and OIDC in 2025
By the numbers:
- 97% of NHIs carry excessive privileges, increasing unauthorised access and broadening the attack surface.
Questions worth separating out
Q: How should security teams govern AI agents that use OAuth and OIDC?
A: Security teams should govern AI agents as non-human identities with dedicated credentials, narrow scopes, tenant-bound permissions, and immediate revocation paths.
Q: Why do AI agents create more identity risk than standard service accounts?
A: AI agents create more identity risk because they can choose actions at runtime, chain API calls, and keep moving without human pacing.
Q: What should organisations look for in an OAuth provider for AI agents?
A: Organisations should look for tenant isolation, client credentials support, granular scopes, short-lived tokens, audit logs, and clear revocation.
Practitioner guidance
- Issue dedicated identities for each agent use case Map every AI agent to its own client credentials, scopes, and audit trail.
- Constrain tokens to one tenant and one task boundary Bind tokens to specific tenant context, approved APIs, and narrow scopes.
- Enforce short token lifetimes with immediate revocation Use short-lived access tokens and ensure a revocation path that can disable the agent before the next action completes.
What's in the full article
WorkOS's full guide covers the operational detail this post intentionally leaves for the source:
- Vendor-by-vendor comparison of OAuth and OIDC platform capabilities for AI agent authentication
- Implementation notes on client credentials, refresh flows, and token handling for production systems
- Pros and cons of each platform for SaaS teams supporting multi-tenant agent access
- Guidance on where enterprise readiness, audit logs, and SCIM provisioning matter most
👉 Read WorkOS's guide to OAuth and OIDC platforms for AI agent authentication →
AI agent authentication with OAuth and OIDC: are your controls ready?
Explore further
08/06/2026 8:26 am
Agent authentication is now an NHI governance problem, not a login feature. The article correctly frames OAuth and OIDC as the mechanism for giving AI agents a usable identity, but the deeper issue is that these systems are being asked to govern non-human actors with machine-speed behaviour. That shifts the control burden from user authentication to identity lifecycle, scope design, and delegated authority management. The practitioner conclusion is simple: if the identity can act without a human in the loop, it must be governed as an NHI from first issue to final revocation.
A few things that frame the scale:
- 97% of NHIs carry excessive privileges, increasing unauthorised access and broadening the attack surface, according to the Ultimate Guide to NHIs.
- 71% of NHIs are not rotated within recommended time frames, which keeps stale access alive long after it should have been removed.
A question worth separating out:
Q: How do you know if agent authentication is actually working?
A: Agent authentication is working when each agent has a unique identity, token scope matches the approved task, actions are fully attributable, and revocation stops further activity immediately. If investigators still need to guess which agent acted or why access persisted, the programme has identity visibility but not identity control.
👉 Read our full editorial: OAuth and OIDC for AI agents: identity controls that reduce risk
