Imagine an overdue invoice and an email from the customer saying they have already paid. An AI assistant can find the invoice, read the message and produce a polite reply in seconds. It can also be politely wrong.
If the payment is sitting unmatched in another system, an automatic chase would create a problem the finance team then has to repair. This is a hypothetical example, but it captures the question we care about when building finance workflows: what evidence would a person need before that message goes out?
Preparation is valuable on its own
A lot of finance time goes on gathering context. Which account is this? Which invoice? Was there a previous promise to pay, a dispute, or a reply from a colleague that has not reached the ledger? Bringing those pieces together and preparing a suggested response can remove real work without pretending the system knows everything.
In one of the completed projects shown in our case studies, workflow data, email analysis, reply preparation and debtor follow-up were brought together. The case study records the results. What matters for this article is the boundary: preparing the next step is different from authorising it.
The review should be worth doing
A human approval button is thin protection if the reviewer sees only a finished sentence. They need the invoice, the relevant account history and any uncertainty that changed the recommendation. They also need a quick way to correct the draft or stop it.
Routine enquiries may be straightforward. A disputed balance or proposed payment arrangement is not. Those cases should arrive with the supporting facts, not a confident answer that hides the gap in the records. We would rather have a system ask for help too often at first than quietly send an email it cannot justify.
The test is what happens to the awkward cases
When assessing a finance assistant, we would look beyond how many replies it drafts. How often does a reviewer change them? How many cases are held because records disagree? Can the team trace what was suggested, approved and eventually sent? If the assistant saves typing but creates avoidable customer conversations, the saving is overstated.
Real account data also brings data-protection duties into the design. The ICO’s AI guidance covers accountability and accuracy, among other issues, and notes that the guidance is under review. It is a useful source to check when planning a live process, alongside the business’s own legal and operational review.