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15/05/2026 8:23 pm
TL;DR: AI agents run as cloud identities through service accounts, IAM roles, and API keys, and Sonrai Security says 92% of cloud identities are already overprivileged, making autonomous access a bigger blast-radius problem than a new identity type. Least privilege and JIT controls now define whether agent behaviour stays contained or becomes breach material.
NHIMG editorial — based on content published by Sonrai Security: Why AI Agents Need Least Privilege Too, and How to Enforce It Automatically
By the numbers:
- Sonrai computed 92% of cloud identities are overprivileged, and the proliferation of agents only further exacerbates that.
- Organisations failing to scope AI access properly are 4.5x more likely to experience a security incident, with 17% incident rates for least-privileged AI access versus 76% for over-privileged systems.
- 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.
Questions worth separating out
Q: How should security teams enforce least privilege for AI agent identities?
A: Start by treating every agent as an NHI with a dedicated identity, a tight permission boundary, and a named owner.
Q: Why do AI agents create more risk than other non-human identities?
A: AI agents create more risk because they act continuously, can make many decisions quickly, and often receive broader access than static automation scripts.
Q: What is the difference between JIT access and standing privilege for AI agents?
A: JIT access exists only for a specific task and is revoked when the task ends, while standing privilege stays available all the time.
Practitioner guidance
- Map every AI agent to a distinct cloud identity Inventory service accounts, IAM roles, and API keys used by agents, then tie each one to a business owner and workload.
- Enforce least privilege at the policy layer Remove unused permissions, define an Accepted State for each agent, and block privileges outside that boundary rather than only flagging them.
- Use JIT elevation for rare agent tasks Grant elevated permissions only for specific jobs and revoke them automatically when the task ends.
Practitioners should align agent access reviews with the NIST AI Risk Management Framework and the OWASP Agentic AI Top 10?
👉 Read Sonrai Security's analysis of least privilege for AI agent identities →
Explore further
15/05/2026 8:24 pm
AI agents are not a new identity class, but they are a new governance stress test. The security failure is not authentication itself, it is the assumption that an identity with broad access can be safely allowed to act at machine speed. That makes existing IAM hygiene more urgent, not less. Practitioners should stop treating agent deployment as an application feature and start treating it as an NHI governance event.
A few things that frame the scale:
- Only 44% of organisations have implemented any policies to manage their AI agents, according to the 2026 Infrastructure Identity Survey.
- 69% of security leaders agree identity management must fundamentally shift to address agentic AI systems.
A question worth separating out:
Q: When does least privilege matter most for AI agent governance?
A: Least privilege matters most when agents can call APIs, touch sensitive data, or trigger downstream changes without a human in the loop. Those are the moments where speed turns a minor mistake into a broader incident. If the agent cannot perform high-risk actions, the impact of compromise or prompt abuse drops sharply.
👉 Read our full editorial: Why least privilege is now mandatory for AI agent identities
