Why AI tools without SSO are ungovernable
When employees authenticate to AI tools with personal credentials, you have no visibility into who is using what, no ability to enforce conditional access policies, and no way to instantly revoke access when someone leaves the organization. Shadow AI starts the moment a tool isn't in your IdP.
SSO as the prerequisite for everything else
Every downstream control — DLP, audit logging, access policy enforcement, anomaly detection — depends on knowing who is making each AI request. Without SSO-enforced identity, your telemetry is anonymous and your controls are porous. SSO is not a nice-to-have; it is the prerequisite for AI governance.
Implementing SSO for AI tools: the practical steps
Audit your current AI tool inventory against your IdP app catalog. For each tool not in the catalog, either add it via SAML or OIDC, or classify it as unsanctioned and enforce blocking. Prioritize tools that access sensitive data first — that is where the risk concentrates.
Conditional access policies for AI
Once tools are in your IdP, apply conditional access policies that go beyond basic authentication: require MFA for AI tools that can access sensitive data, enforce device compliance for tools used in regulated industries, and apply session time limits for high-risk applications. These controls are invisible to users but dramatically reduce your risk surface.
The identity signals that power AI security
With SSO in place, you can correlate AI activity with the rest of your security telemetry: is this the same user who just failed three MFA attempts? Is this access happening from an unusual location? Are they accessing AI tools outside their normal working hours? These signals catch compromised accounts that policy controls alone would miss.