AI agents are often talked about as if the ceiling keeps moving: more autonomy, more decisions, more work taken off people’s plates. But in finance, the more realistic opportunity may be a little more boring. The work worth handing off to AI might be recurring admin around decisions: work that follows rules, creates a record, and can be reviewed before anything important happens.
In our recent study, we examined how professionals actually use and perceive AI agents. When respondents were asked what they wanted agents to handle, finance was among the responses. More specifically, respondents wanted agents to draft invoice templates, flag invoices for review, and send payment reminders.
The Invoice Draft Is the Obvious Place to Start
Invoice drafting is definitely not the most strategic part of finance work. It is also not the part that teams can afford to get wrong. The client name, billing terms, purchase order, and line items all have to land in the right place before anyone can approve what goes out.
The research backs this: invoice templates were among the finance tasks respondents said they wanted agents to handle. Much of the work depends on information that already exists somewhere in the business, which then needs to be pulled into a format that a human can review.
The point is not to hand the invoice over completely. It is to get the draft into a reviewable shape before the human step begins. If an agent can assemble the first version and leave the finance lead or account owner to check the judgment calls, it has already done useful work.
A Second Set of Eyes Before the Invoice Goes Out
Invoice review is the last internal opportunity to catch anything that does not belong before it reaches the client. A missing detail, an unusual total, an inconsistent term, an unbilled item, or a duplicate-looking entry can raise questions later.
Finance teams are already treating AI as a way to catch exceptions. Gartner’s 2025 AI in Finance Survey found that 59% of finance leaders reported using AI in their finance function, while error and anomaly detection had been adopted by 34% of respondents who had implemented AI.
The same idea appeared in Productive’s research, but in a narrower form. Respondents did not ask agents to take over invoice review. They wanted agents to flag invoices for review, which could mean surfacing unusual details, rule mismatches, or anything else that deserves a human check.
Finance leads should not have to inspect every invoice as if every line is equally suspicious. Early flags point them to the details worth checking and keep problems inside the business while there is still time to fix them.
Someone Still Has to Chase the Payment
Late payments won’t chase themselves. Someone still has to notice what is overdue, decide whether a reminder is appropriate, and make sure the follow-up does not create a bigger client issue than the late payment.
Respondents were specific here. They wanted agents to send payment reminders in accordance with predefined rules. The comfort comes from having clear boundaries around the work.
Payment follow-up sits close to the relationship, so those boundaries matter. A useful agent can keep routine reminders moving, but when the situation calls for context, judgment, or care, a person should still step in.
AI Agents May Earn Their Place in the Work Around the Work
The finance tasks people named all sit in the same uncomfortable place: close enough to money to matter, but structured enough to check. They help a team invoice cleanly, review confidently, and follow up without letting administration pile up.
Productive’s AI Agents point in that direction. Teams will be able to configure a Finance agent to help catch operational finance issues that often go unnoticed, such as missing timesheets, un-invoiced hours, and budget overruns, before they turn into margin surprises.
The message is clear enough: AI agents may earn their place in work teams that can define, check, and control. Not the final judgment. The work around the work.