Topic starter
25/06/2026 1:11 am
TL;DR: AI agents are runtime decision-makers that can initiate workflows, call APIs, and act on changing inputs, while NHIs are machine credentials built to authenticate systems in predictable ways, according to Silverfort. Treating them as interchangeable obscures different governance, monitoring, and lifecycle controls, and leaves both privilege and accountability gaps exposed.
Editorial analysis by NHI Mgmt Group, based on content published by Silverfort: “What’s the difference between NHI and AI agents—and why it matters”.
Key questions
Q: What breaks when AI agents are managed like ordinary machine identities?
A: What breaks is the assumption that access scope can be fully understood from provisioning data and quarterly review.
Q: Why do AI agents increase identity risk even when the login succeeds?
A: A successful login only proves that the agent reached the system.
Q: What signs show that an identity programme is misclassifying AI agents and NHIs?
A: A common sign is when the same access review, offboarding, and rotation process is used for both classes without asking whether the subject can make runtime decisions.
Practitioner guidance
- Separate agent governance from NHI governance Map AI agents, service accounts, API keys, and workload identities into distinct control sets so runtime decision-making is not reviewed with the same lens as machine authentication.
- Inventory where autonomous actions inherit machine credentials Trace every agent or AI-powered workflow that can call APIs, trigger jobs, or update data through a backing credential, then record the exact authority that credential confers.
- Redesign access reviews around runtime behaviour Review whether certification processes actually observe what an autonomous system does during execution, not just whether the underlying account still exists.
Bottom line: AI agents and NHIs should not be collapsed into one control model because one is about runtime decision-making and the other is about machine authentication.
Explore further
View Full Forum → | NHI Foundation Course → | Our Services → | Read the full analysis →
25/06/2026 10:27 am
AI agents and NHIs are different governance problems, not just different labels. The article's central distinction is operational, not semantic. NHIs authenticate systems; AI agents decide and act. Security programmes that merge them into one bucket create a false sense of coverage because the control objective changes from credential governance to runtime authority governance.
A few things that frame the scale:
- 19% of organisations give AI systems dramatically more access than human employees, nearly one in five granting unrestricted privilege, according to the 2026 Infrastructure Identity Survey.
- Only 44% of organisations have implemented any policies to manage their AI agents, despite 92% agreeing that governing AI agents is critical to enterprise security, according to the 2026 Infrastructure Identity Survey.
A question worth separating out:
Q: How should security teams govern AI agents that use existing NHI credentials?
A: Treat every AI agent as a non-human identity with its own owner, scope, and expiry. Assign the minimum permissions needed, issue short-lived credentials where possible, and log every action the agent takes. Governance should focus on both access and behavior, because a valid credential can still be used in an unsafe way.
👉 Read our full editorial: AI agents and NHIs are different identity problems