Topic starter
06/11/2026 6:37 pm
TL;DR: Agents can hold valid permissions yet still act outside task intent, so access control alone no longer contains risk, according to Onyx’s Gartner recognition in agentic AI security reflects a broader shift. Runtime policy enforcement, contextual action review, and automated least privilege become the governing layer when AI can plan and execute across multiple systems.
Editorial analysis by NHI Mgmt Group, based on content published by Onyx: “Onyx Named a Gartner Cool Vendor in Agentic AI Security”.
Key questions
Q: How should teams control AI agents that can act across multiple systems?
A: Control AI agents with a runtime policy layer that mediates every tool call, data query, and system action.
Q: Why do autonomous AI agents change least privilege requirements?
A: Autonomous agents change least privilege because their access cannot be assumed to stay fixed for the full life of a session.
A: Security teams should move enforcement into production controls that they own directly, so policy changes do not depend on full developer cycles.
Practitioner guidance
- Define task authority separately from access rights Map which agent actions are permitted because they support the task and which are merely reachable through standing permissions.
- Insert policy checks at action time Place an enforcement point where the agent proposes an external action, so the decision can use current context, not just provisioning-time entitlements.
- Reduce standing access for agent workflows Limit agents to the smallest capability set needed for the current run and remove broader permissions that are only convenient for implementation.
Bottom line: Agentic AI creates a governance problem that access management alone cannot solve, because a permitted action can still be outside task intent.
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06/11/2026 6:42 pm
Permission is no longer the governing unit in agentic AI. The useful control question is not whether an agent can reach a system, but whether its proposed action still fits the task the organisation meant to authorise. That is a different security problem from entitlement management because the same identity can be appropriate at one step and inappropriate at the next. Practitioners should treat task-aligned authority as the real boundary.
A few things that frame the scale:
- 69% of security leaders agree identity management must fundamentally shift to address agentic AI systems, according to the 2026 Infrastructure Identity Survey.
- 53% of security leaders expect AI to run major portions of their infrastructure autonomously within the next three years, according to the 2026 Infrastructure Identity Survey.
A question worth separating out:
Q: What is the difference between agent permissions and agent intent?
A: Agent permissions are the actual technical rights granted to an agent, such as API scopes, service account roles, or tool-specific access. Agent intent is the goal the agent is authorised to pursue, such as drafting, retrieving, or updating records. Good control keeps permissions narrower than intent, so the agent can decide within a bounded mission without gaining broader authority.
👉 Read our full editorial: Why agentic AI security needs runtime control beyond access