IBM Agent Identity: Giving AI Agents Verifiable Identity and Access

B Tecky analysis · 2026-10-26 — An AI agent should not inherit a developer's broad credentials; it needs its own identity and narrowly scoped authorization.

Traditional applications authenticate users and services. Autonomous agents add a new actor: software that can plan and call tools on behalf of a person or organization. If an agent uses a shared API key or a human's session, it becomes difficult to determine which actions it performed and whether those actions were authorized.

An agent identity model assigns each agent a distinct identity, ties it to an owner and use case, and grants only the permissions needed for a task. Delegation should be explicit: a user may authorize an agent to read a folder without authorizing it to share the folder externally. Credentials should be short-lived, revocable and scoped to specific resources.

A secure design logs the initiating user, agent identity, tool, requested action, policy decision and outcome. When the task ends, temporary grants should expire. For sensitive actions, require step-up approval.

User approval -> agent identity -> policy check
      -> short-lived token -> scoped tool call -> audit event

Developers should avoid embedding long-lived secrets in prompts or agent memory. Use a secrets manager and service identity framework, and rotate credentials after suspected compromise.

Takeaway: identity is the foundation of agent security. Treat agents as first-class workloads with owners, permissions and audit trails.

Source: IBM News.

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