Should organisations prioritise intent-based authorisation over broader access reviews for AI agents?

Why intent-based authorisation fits agentic execution better than access reviews

Intent-based authorisation answers the question the moment the agent tries to act: should this specific action be allowed for this task, right now? That is a better fit for autonomous execution than after-the-fact review, because agent risk is created at the point of tool use, data access, or administrative change. Access reviews still have value, but they are governance evidence, not execution control.

For AI agents, the practical issue is not whether the organisation once approved broad access, but whether the current intent justifies the exact operation. A task-scoped decision can stop a harmless-sounding workflow from becoming a broadly privileged agent that can create users, modify groups, or delete infrastructure without a second check. That is why intent-based controls belong in the runtime path, not only in periodic governance cycles.

This is also where human approval can be misused. A single review of an agent’s standing permissions cannot reliably predict every downstream action in a multi-step workflow, especially when the agent chooses tools dynamically. The better control is per-action policy evaluation, with standing access reduced to the minimum needed to reach the decision point. In practice, that means separating task approval from durable privilege.

What broader access reviews still do well

Access reviews remain important, but they solve a different problem. They help organisations find drift, stale assignments, and ownership gaps, and they provide auditability for who was expected to have access. That makes them valuable for governance, recertification, and periodic cleanup, especially where agents are created, retired, or handed between teams.

For AI agents, reviews are especially useful for detecting accumulated overreach, such as an agent that has kept permissions long after the workflow changed. They also expose control failures in registration, ownership, and offboarding. The limitation is that they are retrospective: by the time a review catches a bad grant, the agent may already have executed risky actions for weeks or months.

Review programs therefore work best as a backstop. They confirm whether the access model is still sane, but they do not enforce whether a particular API call, admin change, or data export should proceed at the moment of execution. That is why intent-based authorisation and access reviews should be paired, not treated as substitutes.

How to combine them without losing control at runtime

The cleanest operating model is to treat access reviews as lifecycle governance and intent-based authorisation as the runtime enforcement layer. The review asks whether the agent should continue to exist with a given baseline of access; the runtime policy asks whether the current request matches the approved purpose, scope, and context. Both are needed when agents can act across systems, but they are not interchangeable.

For agentic systems, the most important design choice is where the policy decision happens. If approval is checked only when the agent is onboarded, the organisation is relying on a static snapshot of risk. If approval is checked on each sensitive action, the organisation can distinguish routine retrieval from privileged change. That distinction matters when an agent has the ability to touch identities, groups, secrets, or infrastructure.

At scale, this usually means a task-scoped access model with short-lived delegation, explicit action boundaries, and clear escalation for exceptional requests. When the request exceeds the intended scope, the agent should fail closed and ask for human confirmation rather than silently continue under broad standing access.

Risk and Threat Considerations

Broad access reviews can create a false sense of safety when the actual exposure is execution-time abuse. An over-privileged agent does not need to be permanently compromised to cause harm, it only needs a valid task and a path to a dangerous action. That makes standing privileges, reused credentials, and weak per-action checks especially attractive for abuse.

Failure mechanism: the organisation approves or retains access at a coarse level, but the agent later uses that access for an unanticipated administrative action during a live task. The control gap is between governance approval and runtime authorisation, so the harmful action is no longer prevented.

Impact: the agent can create accounts, expand group membership, alter security settings, move data, or delete resources before any review process notices the excess. The consequence is not just policy noncompliance, it is direct blast-radius expansion during an active workflow.

Practitioner Guidance

What to prioritise: put intent-based checks in front of any action that can change state, expose data, or expand privilege. Keep access reviews for ownership, recertification, and cleanup, but do not rely on them to stop live misuse.

Decision rule: if the agent can perform an action that would be risky if copied by a human admin, require a per-action decision boundary, not just a prior access grant. If the access is only read-only and low impact, broader governance may be sufficient until the workflow matures.

What to verify: confirm that the policy engine can see the requested action, the agent’s current task, the target resource, and any escalation path before the action executes. If those inputs are missing, the authorisation control is too weak to trust.

Practitioner takeaway: access reviews tell you whether the agent should still be trusted in general; intent-based authorisation tells you whether this exact action should happen now. For AI agents, the second question is the one that prevents real damage.

Related resources from NHI Mgmt Group

• When should organisations prioritise just-in-time access for AI agents over standing credentials?
• When should organisations prioritise intent-aware access over traditional least privilege for agents?
• When should organisations prioritise fine-grained scopes and consent over broad API access for AI agents?
• Should organisations prioritise policy-based identity over secret rotation for AI agents?