The AI agent permissions checklist for SaaS apps (2026)

AI agent access in SaaS applications requires controls that clearly establish an agent’s identity, whom it represents, its permission limits, and how its actions can be audited and revoked. The checklist recommends giving agents separate identities rather than user tokens, using short-lived audience-bound delegated tokens, and limiting delegated agents to the intersection of their own permission ceilings and the user’s current access. Authorization should be evaluated on every tool call, at the resource and tenant level, while retrieval systems must filter unauthorized data before it enters a model’s context. Sensitive or irreversible actions such as sending messages, exporting data, changing permissions, or making payments should require out-of-band, action-specific human approval, particularly when untrusted content could influence the agent. Teams should maintain dual-identity logs that record the agent, represented user, organization, target, decision, policy, and intent; apply rate limits, budgets, circuit breakers, and anomaly alerts; and provide customers with visibility into agent activity. Effective offboarding includes immediate cascading revocation for users, agents, tokens, sessions, and sub-agents, tenant- and agent-level kill switches, and regularly tested revocation drills. The material also identifies WorkOS products that can support these practices, including Agent Auth, Fine-Grained Authorization, Pipes Relay, Audit Logs, and Directory Sync.

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