Topic starter
09/07/2026 3:16 pm
TL;DR: Autonomous AI agents already operate inside enterprise systems with real credentials, but identity controls still only confirm who signed in, not whether behaviour has been manipulated, drifted, or turned toward data exfiltration, according to Gurucul research. Behavioural monitoring becomes the missing control layer once agents can act at machine speed and use legitimate access to do the wrong thing.
Editorial analysis by NHI Mgmt Group, based on content published by Gurucul: “Why Behavioral AI Is the Key to Securing Your Agentic Workforce”.
Key questions
Q: How do security teams know if an AI agent is operating outside its approved role?
A: Teams should compare actual workflow behaviour against the approved use case.
Q: Why do traditional IAM and PAM controls struggle with autonomous AI agents?
A: Traditional IAM and PAM controls assume access can be granted, reviewed, and removed around a stable identity.
Q: What are the signs that an AI agent is being manipulated into unauthorized actions?
A: Warning signs include unexpected data retrieval, unusual tool calls, changes in agent decisions after hostile or extreme inputs, and outputs that reflect hidden instructions rather than the user’s request.
Practitioner guidance
- Define per-agent behavioural baselines Track normal query volume, destination patterns, workflow sequence, and timing for each autonomous agent so deviations can be detected in-session rather than only after a login event.
- Correlate document, query, and export activity Link the data source an agent reads, the systems it queries, and the destinations it sends to so indirect prompt injection shows up as one attack path instead of isolated low-signal events.
- Isolate agents when behaviour shifts materially Use live risk scoring to step up controls or cut off access when an agent begins bulk access, touches a new destination, or combines actions outside its established task profile.
Bottom line: Autonomous agents can use legitimate credentials to perform harmful actions, so identity validation alone is no longer enough to protect enterprise workflows.
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09/07/2026 3:33 pm
Behavioural control is now a governance requirement for autonomous workers: identity checks answer who the agent is, but they do not answer whether the agent is still acting as intended once the session begins. That gap matters because autonomous actors can preserve valid authentication while losing behavioural integrity. The implication is that identity programmes must treat runtime behaviour as a first-class control surface, not a secondary alerting signal.
A question worth separating out:
Q: How should organisations govern autonomous agents that act on behalf of users?
A: They should require clear delegation, task-scoped permission, and continuous traceability back to a human creator. The goal is not to impersonate the user more perfectly, but to narrow what the agent can do, preserve auditability, and separate ordinary automation from high-risk action.
👉 Read our full editorial: Behavioral AI is reshaping control for agentic workforce identities