SAML SSO enforcement vs OAuth Client Credentials for Genesys Cloud Analytics API

Is it possible to maintain programmatic API access via OAuth Client Credentials after enforcing SAML SSO for all user logins in our Genesys Cloud organization?

We are migrating our authentication flow to enforce SAML SSO for human users to comply with new security policies. However, our Python-based sentiment analysis pipeline relies heavily on the /api/v2/analytics/conversations/details/query endpoint to ingest transcript data for model retraining. Currently, we use the standard OAuth Client Credentials grant type to obtain access tokens for our service account.

Here is the current token acquisition logic using the genesyscloud Python SDK:

from genesyscloud.auth import get_default_auth_client

auth_client = get_default_auth_client()
auth_client.set_auth_flow(
 client_id='our_service_client_id',
 client_secret='our_service_secret',
 token_url='https://api.mypurecloud.com/oauth/token'
)
token = auth_client.get_access_token()

After enabling ‘Enforce SAML for all users’ in the Genesys Cloud admin console, our automated jobs started failing with 401 Unauthorized. The error response indicates that the token is invalid, even though the client credentials have not changed. We suspect that SAML enforcement might be invalidating standard OAuth grants for users, or that the service account requires specific SAML mapping.

We need to ensure that our non-interactive service accounts can still authenticate via OAuth without requiring a human user to log in via SAML first. Is there a specific configuration for the OAuth client or the service account role that bypasses SAML enforcement for machine-to-machine communication?

How do we configure Genesys Cloud to allow OAuth Client Credentials authentication for service accounts while enforcing SAML SSO for human users?

This is caused by conflating user authentication with machine-to-machine authorization. Enforcing SAML SSO impacts interactive login flows but does not invalidate OAuth Client Credentials grants, provided the application retains the correct permissions in the Genesys Cloud Admin Console. Your Python pipeline should continue using the urn:ietf:params:oauth:client-credentials grant type. Ensure the application is assigned the analytics:conversation:view scope. The token endpoint remains https://api.mypurecloud.com/oauth/token, and you simply pass the client ID and secret. SSO enforcement is orthogonal to this flow as long as no user context is required for the analytics query.

In my Electron desktop app, I handle similar separation by isolating service accounts from user sessions. When querying /api/v2/analytics/conversations/details/query, the payload structure remains identical regardless of the authentication method for the caller. If you encounter 401 Unauthorized errors, verify that the application’s OAuth permissions were not inadvertently stripped during the SAML migration in the Admin UI. The client credentials flow bypasses the identity provider entirely, relying solely on the application’s registered secrets. Double-check that the client secret has not been rotated or that the application status is still Active. This architectural separation ensures your sentiment analysis pipeline remains stable while human users transition to SSO.