Topic starter
06/07/2026 9:35 am
TL;DR: Gartner’s IAM Adapts to Secure and Enable AI Agents says authentication and monitoring are relatively ready, but identity registration, credential management, and authorization lag as organisations deploy more AI agents, according to Descope’s summary of the report. Human credential sharing, not just tool integration, is the control pattern that breaks first when agents operate at machine speed.
Editorial analysis by NHI Mgmt Group, based on content published by Descope: “Gartner® Report: IAM Adapts to Secure and Enable AI Agents”.
Key questions
Q: What is the biggest governance failure when organisations let AI agents use human credentials?
A: The main failure is that the organisation loses a clean identity boundary.
Q: Why do AI agents and machine identities complicate authorization decisions?
A: They complicate authorization because they can act continuously, delegate authority, and chain tool use faster than human review cycles can intervene.
Q: How should organizations approach the governance of AI agents?
A: Organizations should adopt a governance framework that incorporates continuous visibility, adaptive IAM practices, and stringent policy-based controls.
Practitioner guidance
- Establish agent registration as a mandatory intake step Record owner, business purpose, tenant, tool scope, and lifecycle state before any AI agent receives production access.
- Eliminate human credential sharing with agents Issue agent-specific credentials or delegated tokens so the agent can be revoked independently without disabling the human user.
- Apply context-aware authorization to agent actions Evaluate the agent identity, delegating user, tenant, and requested tool scope at the moment of access rather than relying on a static role.
Bottom line: AI agents expose a governance gap when organisations try to fit machine actors into human credential models.
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06/07/2026 9:49 am
Identity registration is the control that separates an AI agent from anonymous automation: Gartner’s report, as summarised by Descope, shows that discovery alone is not enough because a visible agent is not yet a governed one. The governance problem is ownership, scope, and accountability, and those elements only exist when the agent is formally registered. Practitioners should treat registration as the start of lifecycle control, not the end of inventory.
A few things that frame the scale:
- 70% of organisations grant AI systems more access than they would give a human employee performing the exact same job, according to the 2026 Infrastructure Identity Survey.
- 53% of security leaders expect AI to run major portions of their infrastructure autonomously within the next three years, according to the 2026 Infrastructure Identity Survey.
A question worth separating out:
Q: When does shared access between humans and AI agents become unacceptable?
A: It becomes unacceptable when the shared credential prevents independent scoping or revocation of the agent. If the agent can act under the same identity as the human, the organisation cannot separate legitimate human use from machine actions. That creates compliance, audit, and containment problems even when the underlying task is routine.
👉 Read our full editorial: IAM for AI agents is exposing identity governance gaps