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A controller closing the books used to spend the better part of a week matching bank feeds against invoices by hand, chasing down a $340 discrepancy that turned out to be a duplicate charge nobody caught in week one. That kind of work is where AI has made the most real difference in finance so far. Not in replacing judgment, but in cutting down the hours spent finding the thing that judgment then has to fix.

Diligence in 2026 takes longer than it used to, and investors are spending more of that time in different folders than they were two years ago. Customer contracts and usage data get more attention now than the pitch deck. A financial model that looked sufficient at Series A in 2022 gets picked apart line by line before a term sheet gets signed.

A founder came to us last spring with a pitch deck that looked ready for a Series A. The slides were clean, the market size slide had a big number on it, and the traction chart went up and to the right. When we asked for the underlying model, he sent over a spreadsheet with one tab. It had last month’s actuals and a growth rate typed into a formula. No cash view, no headcount plan, nothing that showed what happened if a big customer churned in month four. He wasn’t being careless. He’d just never been shown what a real model looks like, because most founders haven’t.

Early conversations about AI in finance centered almost entirely on automation and substitution. The vision that captured the most attention was “lights-out finance,” a close process running end to end with minimal human involvement, reconciliations clearing themselves, reports generating on schedule without anyone in the loop. It was a compelling picture, and for a while it shaped how a lot of finance leaders thought about AI investment.

Many SaaS companies set their pricing once, early, under pressure, and then never touch it again until growth stalls and someone finally asks why. The pricing page that made sense at $2M ARR often has no logical connection to the value the product delivers at $20M ARR. Nobody revisited it because nothing forced them to.

A CEO we worked with last year opened her Series B model three weeks before her first partner meeting and found that marketing spend had been booked under four different line items depending on which month you looked at. She spent the better part of a weekend just reconciling categories before she could even start building the forecast an investor would actually read.