Build a Simple Review Checklist for AI Output
Once a small business starts using AI for real work, like drafting customer emails, summarizing calls, or writing product descriptions, the same question comes up quickly: who checks the output, and how? "Someone looks it over" sounds fine until the volume grows and nobody is quite sure what looking it over means. A short, written review checklist fixes that.
The goal isn't to slow everything down. It's to make review fast, consistent, and the same no matter who does it.
Write the checklist for one task, not for "AI"
A checklist that tries to cover every possible use of AI ends up too vague to help. Start with the one task you're actually running, such as replies to common customer questions. Ask what a bad version of that output would look like. Wrong price? Promising something you don't offer? A tone that doesn't sound like you? Each of those becomes a line on the list.
Keep it to five or six checks
If the list is long, people skim it, and then it's not a checklist anymore. Pick the handful of things that would actually cause a problem if they slipped through. A good starting set for most customer-facing text looks something like this:
- Every fact, number, date, and price matches what we actually offer.
- Nothing is promised that we can't or won't do.
- Names, products, and order details belong to this customer.
- The tone sounds like us, not like a brochure.
- Nothing private or internal is included that shouldn't be.
- It answers the question that was asked.
Decide what happens when something fails
A checklist is only useful if everyone knows what to do with a "no." Write that down too. Small fixes, like a wrong name, the reviewer just corrects. Bigger problems, like a made-up policy, should go back to whoever set up the task so the instructions or source material can be fixed. If the same mistake shows up more than once, that's a sign the process needs adjusting, not just the individual output.
Give the AI the same rules
Most of what's on your checklist can also go into the instructions you give the tool. If your list says "never quote a price that isn't on the current price sheet," tell the AI that and give it the price sheet. This won't make the review step unnecessary, but it usually means fewer things fail it, and the review gets faster.
Know when review can loosen, and when it can't
Early on, check everything. After a few weeks of output passing review consistently, you might decide some low-risk items only need spot checks. That's a reasonable call, but make it on purpose and write it down. Anything that touches money, legal commitments, or a customer's personal information should keep a human looking at it every time.
Put the checklist where the work happens
A checklist in a forgotten document doesn't get used. Pin it next to the tool, add it to the template, or put it at the top of the shared queue. The easier it is to see while reviewing, the more likely it actually gets followed, especially by someone new or covering for a teammate.
None of this is complicated, and that's the point. A clear checklist turns "someone should probably look at this" into a habit your whole team can follow, which is what lets you trust AI with more of the work over time.
If you'd like help setting up a first AI project with review built in from the start, take a look at my consulting page. And for more practical lessons on building a business while you run it, there's my book, Flying and Building an Airplane at the Same Time.