Topic starter
16/04/2026 6:35 pm
TL;DR: AI agents are being deployed with real credentials, broad permissions, and limited governance, making them non-human identities that inherit cloud IAM weaknesses, according to Sonrai Security's analysis. Least privilege and just-in-time access remain the practical baseline, but the real shift is treating agent behaviour as an identity governance problem rather than a tooling problem.
Editorial analysis by NHI Mgmt Group, based on content published by Sonrai Security: “How Treating AI Agents as Identities Can Reduce Enterprise AI Risk”.
By the numbers:
- 92% of cloud identities are overprivileged, which shows how quickly AI agents inherit an already weak permission baseline.
Key questions
Q: What breaks when AI systems are governed like static applications?
A: Lifecycle drift breaks the model.
Q: Why do over-privileged AI agents create higher business risk than ordinary users?
A: Over-privileged agents can execute many more actions than the task actually requires, so one bad decision can cascade into wrong approvals, refunds, data movement, or API calls.
Q: Should security teams require just-in-time access for AI agents?
A: Yes, when the agent's task is time-bound and the environment can enforce short-lived entitlements.
Practitioner guidance
- Inventory AI agents as non-human identities Create a complete list of agents, service accounts, roles, and API keys across cloud accounts, and assign a human owner to each identity so governance does not depend on tribal knowledge.
- Right-size permissions before first use Compare granted access to actual permission usage, remove unused rights, and set default permission boundaries when agents are created rather than after they are already operating.
- Replace standing privilege with task-scoped elevation Use approval-based just-in-time access for sensitive actions, then revoke elevated rights automatically at task completion so privilege does not persist between agent runs.
Bottom line: AI agents are now operating as non-human identities inside cloud environments, which means their access needs lifecycle, ownership, and entitlement controls rather than ad hoc exception handling.
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This topic was modified 1 day ago by NHI Mgmt Group
11/10/2026 2:37 am
AI agents are non-human identities, not a separate governance class: The article's strongest implication is that cloud teams do not need a new identity taxonomy for agents. They need to apply non-human identity governance to a new workload shape whose behaviour is more dynamic than traditional service accounts. That means the core problem is lifecycle and privilege control, not branding. The practitioner conclusion is that AI agents should enter the identity model through the same inventory, ownership, and entitlement disciplines as other machine identities.
A few things that frame the scale:
- 97% of NHIs carry excessive privileges, increasing unauthorised access and broadening the attack surface, according to the Ultimate Guide to NHIs.
A question worth separating out:
Q: Should organisations use continuous authorization instead of traditional PAM for AI agents?
A: They should use continuous authorization for agent actions and keep PAM as part of the wider identity stack. PAM controls standing privilege and escalation, but AI agents need per-action decisions because their risk changes within the session. The two controls are complementary, not interchangeable.
👉 Read our full editorial: AI agent identities expose cloud IAM limits in enterprise environments