Topic starter
11/11/2026 6:05 pm
TL;DR: Intent-based access control centres on whether the subject’s goal or the agent’s runtime behaviour should govern access, according to IndyKite. For practitioners, that means policy has to validate delegated tool use against a subject-defined request rather than against free-form prompts.
Editorial analysis by NHI Mgmt Group, based on content published by IndyKite: “Intent based access control: Whose Intent is it anyway?”.
Key questions
Q: What is the difference between subject intent and agent intent?
A: Subject intent is what the human user or accountable principal asked for.
Q: How does intent get normalized into policy decisions?
A: Intent is normalised by translating the request into policy inputs such as subject, action, resource, and context, then evaluating those inputs against access rules, risk signals, and delegation boundaries.
Q: How do I control what an AI agent is allowed to do based on policy intent?
A: Enforce intent-based access control by turning the initiating request into a policy object that includes the subject, action, resource, and context.
Practitioner guidance
- Define subject intent as the policy source Base delegated AI authorization on the subject’s request context, not on an inferred reading of the agent’s own objective.
- Normalize prompts into access requests Map agent requests into subject, action, resource, and context fields so policy can evaluate them deterministically.
- Restrict evaluation to the agent’s operating domain Reject prompts that fall outside the organization’s intended knowledge or task domain before they reach authorization logic.
Bottom line: Intent-based access control makes the subject’s request, not the agent’s inference, the basis for delegated authorization.
Glossary terms: Intent-Based Access Control, Subject Intent, Agent intent, OpenID AuthZEN
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11/11/2026 6:08 pm
Intent based access control is really an accountability model for delegated AI. The useful unit is not the prompt but the subject’s authorization context, because that is what ties action back to an accountable principal. Once an agent can take multiple steps after the initial request, the governance problem becomes whether every step still fits the original delegation. Practitioners should treat IBAC as a control over delegated authority, not as a language-plausibility filter.
A few things that frame the scale:
- Only about one-third of approximately 500 organizations surveyed by McKinsey in 2026 report maturity level three or higher across agentic AI governance controls.
A question worth separating out:
Q: What happens when an AI agent acts beyond the original request?
A: When an AI agent acts beyond the original request, it has exceeded delegated authority and may trigger a policy violation, escalation, or revocation. Common controls include action allowlists, scoped tool permissions, approval gates, and auditable logs that show the human accountable for the agent’s runtime decisions.
👉 Read our full editorial: Intent based access control turns agent goals into policy decisions