How to manage multi-user AI agent authentication and authorization in 2026 (OAuth 2.1, OIDC, and delegated access)

In 2026, deploying multi-user AI agents in enterprise production necessitates robust authorization mechanisms to prevent security breaches like prompt injection and excessive agency. The central tenet is treating every agent action as delegated user access, requiring a two-identity model combining the agent's and the user's permissions, evaluated per action at runtime. This approach involves using protocols like OpenID Connect for user authentication and OAuth 2.1 for agent authorization, ensuring that tokens are short-lived, scoped, and audience-bound. The Model Context Protocol (MCP) runtime facilitates secure interactions by handling token management, just-in-time consent, and enforcing policy rules, while generating immutable audit logs for compliance. Effective authorization prevents issues such as the "confused deputy" problem, where agents could misuse authority, and emphasizes that only actions explicitly authorized by the intersection of user and agent permissions are executed. This setup aims to secure AI agents by ensuring actions are tightly controlled, with step-up approvals required for high-impact actions and a runtime that unifies the necessary capabilities for secure operations.