AI agents are no longer science fiction, they browse the web, call APIs, write code, and take actions on behalf of users. But who are they, from an IAM perspective? And how do we govern them?

What is identity agentic?

The term identity agentic refers to the discipline of assigning, managing, and governing digital identities for autonomous AI agents. AI Agents are software entities that act independently, make decisions, and interact with systems and data without direct human intervention at every step.

Traditional IAM was designed for humans and, later, service accounts. AI agents break both models: they behave like humans (reason, adapt, and chain tasks) but operate like machines (always-on, massively parallel, non-human). This gap is the identity agentic challenge.

Traditional IAM was designed for humans and, later, service accounts. AI agents break both models: they behave like humans (reason, adapt, and chain tasks) but operate like machines (always-on, massively parallel, non-human). This gap is the identity agentic challenge.

Why it matters for IAM professionals

Consider an Okta-integrated enterprise deploying an AI assistant that can read tickets, query HR systems, and send Slack messages. Each of those actions involves an identity decision:

  • Who authorized this agent to act?
  • What scopes were it granted and for how long?
  • Can it delegate that authority to a sub-agent?
  • What audit trail exists for its actions?

Without an identity agentic framework, organizations are flying blind. Agents accumulate permissions, persist beyond their task, and create non-human identities that fall outside normal provisioning and de-provisioning workflows.

Identity for Agents: Core Principles

  1. Least Privilege (Always)
    Grant agents only the permissions required for the task, using scoped, short-lived tokens instead of standing access.
  2. NHI-Agent Classification
    Treat agents as a distinct identity type (Non-Human Identity – Agent) with defined attributes like owner, purpose, and lifecycle.
  3. Delegation Traceability
    Maintain full visibility of agent-to-agent delegation chains, logging every action back to the originating human identity.
  4. Continuous Authentication
    Enforce real-time trust evaluation, triggering step-up authentication for high-risk actions—even during active execution.
  5. Automatic De-provisioning
    Decommission agents immediately after task completion, tying lifecycle to workflows rather than periodic reviews.

Key takeaways

  • Classify agents as NHI: Create a dedicated identity class — not a shared service account.
  • Short-lived credentials: Token exchange over standing access. Always scope to the task.
  • Trace delegation chains: Every sub-agent must be traceable to a human owner.
  • Auto de-provision Tie agent lifecycle to task state, not annual reviews.

Key distinction: A human user logs in once and acts. An AI agent may spawn dozens of sub-agents, each needing its own scoped identity, and none of them should carry more privilege than the task requires.

Gabriel Magarino – Senior Security Manager | IAM Evangelist - Experienced leader with over 20 years in the IT and cybersecurity industry, specializing in Identity & Access Management. Expert in Okta, One Identity, SailPoint (IdentityIQ & IdentityNow), OneLogin, Delinea, and CyberArk. Passionate about exploring IAM and emerging technologies, coaching, and training IAM teams. Holds a Master’s in Computer Science and multiple certifications, including Okta Professional & Administration, One Identity Architect & Instructor, SailPoint Identity Now, ITIL, Scrum Master, among others. Currently pursuing a PhD with a focus on Computer Science and Artificial Intelligence.

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