Topic starter
16/12/2025 5:40 pm
TL;DR: AI agents dominated Gartner IAM Summit conversations because they amplify the same service-account, secrets, and visibility problems IAM teams have long struggled to control, according to Astrix Security. The practical shift is clear: agent governance now depends on mapping accounts, entitlements, and activity to human and non-human ownership before production adoption widens the blast radius.
Editorial analysis by NHI Mgmt Group, based on content published by Astrix Security: “AI Agents and the Core of IAM: Key Takeaways from the Gartner IAM Summit 2025”.
Key questions
Q: What breaks when AI agents inherit access from users and service accounts?
A: The main failure is that inherited access can be broader than the agent’s actual task, so privilege becomes easier to reuse than to govern.
Q: How do AI agents change secrets governance for IAM teams?
A: AI agents increase the number of identities that need access and the frequency with which credentials are used.
Q: How can security teams tell whether agent access is actually under control?
A: Look for evidence that the team can trace every tool call, secret use, and cross-system action back to a named owner and a valid approval path.
Practitioner guidance
- Map AI agents to governed non-human identities Assign each agent a unique, inventory-backed identity and record who owns its lifecycle, privileges, and approval path.
- Inventory accounts, entitlements, and activity together Build a single view that connects agent accounts, granted entitlements, and observed activity so access can be traced end to end.
- Eliminate hard-coded and long-lived secrets Move agent credentials out of code and into managed secret workflows, then shorten lifetime wherever production use is planned.
Bottom line: AI agents are not introducing a brand-new identity problem so much as accelerating old NHI weaknesses that IAM teams have not fully closed.
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This topic was modified 1 week ago by NHI Mgmt Group
06/10/2026 4:27 pm
AI agents are exposing an identity governance debt that already existed. The article is right to treat AI agents as a force multiplier for old NHI problems rather than a brand-new category of risk. Service accounts, hard-coded keys, and poor visibility were always weak points; agents simply make their failure mode harder to ignore. The practical conclusion is that identity teams must govern the underlying machine identity estate before production adoption multiplies the exposure.
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: Should organisations treat AI agents as NHI or as application automation?
A: They should treat them as governed non-human identities with application behaviour. That framing captures the need for identity, scope, lifecycle, and audit controls while still recognising that agents operate through APIs, tools, and workflows. Pure automation language hides the governance gap.
👉 Read our full editorial: AI agents are forcing old IAM and NHI gaps back into view