Finance teams live by a cycle: close the month, report it, update the forecast, support a decision, then do it all again. When people ask where AI fits, I start with that cycle, because it shows where the hours go and where a mistake would hurt.
Most of the effort sits in preparation. Someone collects files from several markets, aligns them to one structure, checks that they tie, and writes the first draft of what changed. That work matters, but it is also the part a well-supervised tool can speed up. The conversation with the business is where finance creates value, and it usually gets whatever time is left.
Three tests before you automate
I use three questions to decide whether a task is ready for AI.
- Is it repeatable? A task that follows the same steps every month, such as a first-draft variance commentary, is a strong candidate. A one-off restructuring analysis is not.
- Can the output be checked? If a reviewer can trace each statement back to a number in a report, the risk is manageable. If nobody can verify the answer, it should not reach a decision maker.
- Does it have a named owner? Someone must remain accountable for the final number and the final message. AI can draft. It cannot own a forecast.
Where I would start
Three uses tend to pass all three tests. The first is commentary drafting: turning a variance table into a first version of the story for a monthly review. The second is scenario preparation: laying out what a price, allowance or cost change would do to the P&L before the meeting starts. The third is exception screening: highlighting the lines that moved outside their normal range, so reviewers look in the right place first.
Where I would be careful
Forecast assumptions, accrual judgements and anything that goes into external reporting need a human decision. AI can bring the evidence together, but those calls depend on context a model does not have, such as what a customer said last week or a promotion that is about to change.
The aim is a better use of finance time. If AI gives a team two extra days each cycle, those days should go to the discussion with commercial leaders about what the numbers mean and what to do next.
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