Ultimate Guide to Identity for AI
AI agents introduce a new identity and security challenge: they can access systems, trigger workflows, and act on behalf of users at machine speed. Identity and security teams need practical controls to authenticate, authorize, monitor, and govern these agents without relying on legacy IAM assumptions.
The Ultimate Guide to Identity for AI provides a practical framework for securing agentic AI across enterprise systems. It covers agent types, delegation models, lifecycle governance, authentication patterns, human-in-the-loop oversight, and protocols such as OAuth 2.0, Dynamic Client Registration, Model Context Protocol, and mTLS.
Key Takeaways
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How to classify AI agents by ownership, autonomy, and supervision model
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Why teams should delegate access instead of sharing credentials or impersonating users
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What controls help enforce least privilege, scoped access, auditability, and human oversight
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How IAM teams can use modern protocols to secure agent-tool and agent-to-agent interactions