Approve within limits, yes; reject on its own, rarely. An AI agent can approve low-value expense claims that meet every policy rule and carry a valid receipt, and it can send incomplete claims back for missing information. Final rejections, policy exceptions, claims above its limit and claims from senior staff or approvers themselves should go to a named approver.
Why treat approval and rejection differently?
An approval inside clear rules is low risk: the claim is small, the receipt matches, the category and amount are within policy, and the money is the employee's own outlay being repaid. If the agent gets one wrong, it is caught in sampling and recovered.
A rejection is different. It tells an employee they will not be repaid money they have spent, sometimes on the business's behalf and sometimes in good faith. It often turns on context the agent does not have: the client dinner that ran over budget because the client chose the restaurant, the taxi taken because a train was cancelled. That calls for a person who can ask. The agent's role is to find the problem and explain it; a person decides whether it is a reason to refuse.
What conditions decide whether the agent may approve?
All of these, every time:
- A valid receipt that matches the amount, date and merchant claimed.
- Category and amount within policy, read from the current expense policy.
- Under the agent's approval limit, set by finance per claim and per claimant per month.
- No duplicate: the same receipt or amount has not been claimed before.
- Claimant not excluded: claims from people who approve others' expenses, and from senior leaders, go to a named approver regardless of amount.
Whether an agent can apply the policy consistently at all is covered in whether an AI agent can enforce an expense policy.
What may the agent do, and where must a named approver sign off?
| Claim | The agent | Named approver |
|---|---|---|
| Small, in policy, receipt valid | Approves at depth 3 | Samples weekly |
| Receipt missing or unreadable | Returns the claim asking for the receipt | None |
| Over the per-claim or monthly limit | Reviews it against policy; holds with notes | Approves or rejects |
| Outside policy (category, amount, timing) | Holds with the rule breached and any explanation the claimant gave | Decides on the exception or rejection |
| Possible duplicate | Holds with both claims attached | Decides |
| Claim by an approver or senior leader | Reviews it; holds | A different named approver |
| Pattern across claims, such as frequent round amounts | Flags to finance | Investigates |
The agent's "no" is always a hold or a return, never a final rejection. That keeps an employee's pay decisions with a person, and it keeps the agent away from judgement calls it cannot make well. The reasoning is set out in expense agents enforce policy consistently; people handle the exceptions.
An illustrative example
Take a professional services firm with an approval limit for the agent of 75 per claim and 300 per claimant per month.
A consultant submits a 42 train fare with a ticket receipt. The category is allowed, the amount is under the limit, there is no duplicate. The agent approves it and it joins the next expenses payment.
Another consultant submits a 140 client dinner for two. The policy limit for client meals is 60 a head. The agent holds the claim, noting that it exceeds both its approval limit and the per-head meal limit, and attaches the consultant's comment: "client's choice of venue, agreed with partner in advance". The partner approves it as an exception. The agent did not reject a legitimate claim, and the exception is recorded with a named decision-maker.
Which controls make it safe?
- Limits in the expense system, not in the agent's instructions.
- Separation from payment: approving a claim does not pay it. Reimbursements go through the payment run, which has its own approver; see whether an AI agent can approve a payment run.
- Excluded claimants routed to named approvers automatically.
- Sampling of auto-approved claims weekly.
- Every verdict filed with the rule and receipt that supported it.
The setup is described in how to let an AI agent approve low-value expense claims, and the review side in how to review employee expense claims with an AI agent.
Where Pryme fits
In Pryme, approving an expense claim is a capability certified on your own past claims, with your limits in the minimum chain. The receipt image is external; the card transaction, where there is one, is sealed, and the agent matches the two. Final rejection is not a capability the agent holds. More is in AI agents for finance: books you can audit.
Questions people ask
Can the agent reject an obviously fraudulent claim?
It holds it and flags it. Suspected fraud by an employee is a matter for a person and possibly HR, not an automated rejection.
Should employees know an agent approved their claim?
Yes. Tell them, and tell them how to ask a person if they disagree with a hold or return.
Can the agent approve mileage claims?
If the policy rates and the distance can be checked, yes, within limits. Unusual journeys are held.