An AI agent should receive only the actions and data access needed for a defined business task, with separate control over consequential changes. Start by writing an action boundary before connecting tools: what may be read, what may be drafted, what may be changed and what needs a person’s decision. That boundary is part of the product specification, not something a persuasive prompt can replace.
Why this changes the operator’s decision
A system that recommends an answer and a system that can change a customer record create different operating questions. The relevant issue is the effect of the action in the connected business, even when both systems use a similar model. An impressive demonstration should therefore be followed by a review of the actions the product is actually allowed to perform.
OWASP’s Excessive Agency guidance identifies excessive functionality, permissions and autonomy as root causes of damaging actions. The framework below is my practical way to turn that concern into a small delivery decision. It is not a certification, a guarantee of security or a substitute for reviewing the specific system.
Write four action categories
For a hypothetical customer-support agent, reading a permitted ticket is one category. Drafting a reply is another. Sending the reply or changing the account is a third. Issuing a refund or expanding access creates further consequences. Do not grant all those capabilities simply because they are available through the same integration.
Record the smallest useful permission for the intended task. If the product only prepares replies, it may not need the ability to send them. If it needs a limited set of customer fields, investigate whether the connection can expose those fields without broader account access. Ask engineering to demonstrate the actual boundary, not merely describe what the agent has been told to do.
Name the responsible business owner for each action. That person should understand the conditions, limits and escalation path. An action with no accountable owner is a poor candidate for autonomous execution, even if the tool call itself is easy to implement.
Define what approval means
Approval should cover a concrete proposed action: the record, recipient, amount or change, and the relevant context. A person clicking a generic “continue” button without seeing the consequence is not the operating control I would want. Show enough information for a meaningful decision and keep the proposed action stable between review and execution.
Suppose an agent drafts a customer refund for a hypothetical 50 units. The reviewer should see the intended customer, transaction reference, reason and amount. If the destination or amount changes after review, the system should treat that as a different proposal. This example defines a control question; it is not instructions to perform a financial transaction.
Test the limits, including refusal and escalation
Use synthetic data to test what happens when a ticket contains misleading instructions, the requested account is outside scope or a necessary field is missing. The desired result may be a draft, a request for clarification or a stop. A successful test is not always a completed action.
Check that the underlying connection enforces the intended permissions. A prompt saying “never delete” does not establish that deletion is unavailable. Also test failures between steps: a proposal might be created successfully while execution fails. The product needs a way to explain the actual state without inventing completion or repeating a consequential action blindly.
Keep an understandable record of proposals, approvals, attempts and results. Avoid storing unnecessary sensitive content just to make the log more detailed. Agree access, retention and incident responsibilities for the actual customer arrangement.
Expand autonomy only with evidence
Begin with the narrowest workflow that produces useful value. Measure completed work, exceptions, review effort and incorrect or blocked proposals. If every useful result requires extensive correction, increasing permissions is unlikely to solve the underlying product problem. Change the workflow or improve the evidence first.
The paid-pilot rollout scorecard helps place these findings alongside customer value and delivery effort. For Benelux B2B teams and Pakistani founders serving international business customers, the commercial test remains the same: can the product do a defined job reliably within an agreed boundary? If you are building an early-stage B2B or fintech product with that discipline, share the workflow, evidence and next milestone.