Topic starter
23/10/2026 12:46 am
TL;DR: AI agents belong in insider risk discussions when they hold delegated authority, persistent sessions or access that can cross user boundaries, according to DTEX. Identity-aware controls have to preserve the requester's authorization boundary as the agent acts.
Editorial analysis by NHI Mgmt Group, based on content published by DTEX: “CISA’s Insider Risk Guidance Must Extend to AI Agents”.
Key questions
Q: Why do agentic AI systems create a malicious-insider risk?
A: Because they can hold delegated authority across a workflow and use it faster than a human can intervene.
Q: What signs show an AI agent is crossing its intended authority?
A: Look for tool calls outside the expected workflow, repeated access to systems not required for the stated task, and logs that cannot clearly distinguish agent actions from human or service-account activity.
Q: What fails when AI agents are treated as ordinary tools in insider risk programmes?
A: The control model fails because tools are assumed to be passive, while agents can hold delegated access, choose alternate execution paths and cross authorization boundaries on their own.
Practitioner guidance
- Define which agents qualify as insider-equivalent identities Classify agents that hold delegated authority, persistent sessions or cross-system access as governed identities, not generic tooling.
- Enforce user-bound entitlement checks at response time Verify that an agent can only retrieve and return data the requesting user is entitled to receive, even when the agent itself has broader access.
- Record the agent decision path, not just the final action Capture prompts, tool calls, fallback routes and identity context so investigators can reconstruct how an outcome was reached.
Bottom line: AI agents belong in insider risk discussions when they hold delegated authority, persistent sessions or access that can cross user boundaries.
Glossary terms: Insider-equivalent identity, Authorization Boundary, Delegated Authority Model, Agent observability
Explore further
View Full Forum → | NHI Foundation Course → | Our Services → | Read the full analysis →
This topic was modified 6 days ago by NHI Mgmt Group
23/10/2026 9:49 am
AI agents should now be governed as insider-equivalent identities when they hold delegated authority. The defining characteristics of an insider are access, agency and accountability, and AI agents can possess the first two even when they lack human intent. That means the control model must shift from assuming tools are passive to treating some agents as trusted entities with their own access footprint. Practitioners should therefore map agents into identity governance, NHI and PAM workflows rather than leaving them inside a generic AI operations bucket.
A few things that frame the scale:
- 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.
- 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.
A question worth separating out:
Q: How should security teams govern AI agents that can access enterprise systems?
A: Security teams should govern AI agents as non-human identities with explicit ownership, scoped privileges, and continuous monitoring. The control set should include inventory, task-bound credentials, audit trails, and revocation paths. If an agent can call tools or touch production systems, it belongs in the same governance model as service accounts and other machine identities.
👉 Read our full editorial: AI agents now belong inside insider risk governance
This post was modified 6 days ago by NHI Mgmt Group