10/29/2026
Small businesses are adopting AI fast, but there’s a meaningful share of them who have no idea what return they're getting on the AI they've already bought.
Sometimes the problem is the AI tool itself. Other times, it's a problem with what was in place before the purchase.
Does this sound familiar? Customer and operational data that's scattered across email threads, spreadsheets, and half a dozen disconnected platforms. Maybe your employees are quietly re-entering the same information on each of those systems.
If you layer an AI system on top of that kind of fragmentation, you probably won’t get much useful insight. What you will get is chaos that is harder to decipher.
The fix is better sequencing.
Before buying the next AI feature, small businesses need to know where data lives and whether there's a single, trustworthy source of truth for it.
They also need existing systems talking to each other instead of relying on someone's manual copy-paste to bridge the gap.
And critically, all this needs to define what "working" looks like. A specific, measurable outcome, before the purchase (not after), so there's something real to hold the investment against.
That last piece is the one most businesses skip, and it's the one that turns AI spending from a bet into a real business decision.