Once a small team starts using an AI workflow, the next question is whether it still works well enough to keep. This weekly review is for an existing process: drafting customer replies, summarizing requests, or preparing internal notes. It produces a short decision log rather than another list of tools to buy. For choosing your first project, use our small-business AI adoption guide.

Prepare one page before the meeting

Record the workflow name, owner, review period, and approved scope. Add the number of attempted tasks, completed tasks, rejected outputs, manual fallbacks, and unresolved items. Keep the original task reference so an apparent success can be checked against the actual result. A green automation run can mean the software finished, even when its answer was wrong.

Choose examples that show normal work as well as exceptions. Include a rejected draft, a missed request, and a repeated task if those occurred. Avoid selecting only the best outputs. If you have very few tasks, inspect them all and describe the sample size rather than presenting a confident percentage.

Separate completion from correctness

Check	Question	Evidence
Coverage	Did every expected request arrive?	Source queue compared with output queue
Accuracy	Does the result match approved information?	Sample and source document
Review	Did a person approve the required step?	Approval record
Delivery	Did the right destination receive it once?	Destination record
Recovery	Were failures handled manually?	Exception log and owner

For example, a summary that lists three customer requests when the source contains four is incomplete even if the writing is fluent. A draft that invents a delivery date is inaccurate even if the recipient address is correct. Keep these findings separate so the fix addresses the problem.

Use a fictional delivery-inquiry example

Imagine a shop uses AI to draft replies from an approved delivery policy. In one week, 40 requests arrive. The workflow produces 38 drafts, while two fail because an attachment cannot be read. Staff reject three drafts that promise dates absent from the policy. One request is processed twice.

The team should not report “38 successful replies.” It should record 40 incoming requests, two missing drafts, three inaccurate drafts, and one duplicate output, then reconcile which requests actually received a reviewed response. Counts may overlap: the duplicate could also be one of the rejected drafts. Use request references to avoid double-counting failures.

The next actions are concrete: route unreadable attachments to the manual queue, remove unsupported delivery promises from the drafting instructions, and check whether a completed request can be triggered again. These are illustrative findings, not results from a measured business deployment.

Count the time spent fixing the workflow

Ask reviewers to log drafting, checking, correction, and maintenance time separately. Compare equivalent tasks with the earlier manual process. If a draft saves two minutes but takes four minutes to verify, its speed is not a productivity gain for that task. Note whether time is released for other work or translates into an actual spending reduction.

Read the usage dashboard alongside the task log. Repeated retries can consume credits without producing additional useful work. Investigate a cost increase before raising the spending limit. Keep the provider’s billed period visible because a calendar-week task log may not line up with a monthly invoice.

Check changes to the source information

Ask whether policies, product names, opening hours, or staff responsibilities changed. Assign one person to update the approved source and record its revision date. Then test old and new examples before letting revised instructions handle normal work. A correct answer from last month may be wrong after a policy change.

Also check whether access still belongs to the right people and whether the team knows how to stop the process. Use non-sensitive test inputs when possible. If the workflow unexpectedly exposes information or performs an action outside its approved scope, pause that part and investigate before resuming it.

End with one decision and an owner

• Continue: the evidence meets the team’s criteria; keep the same scope until the next review.
• Adjust: name one change, a tester, and the examples that must pass.
• Pause: name the manual fallback owner and the condition required before restarting.

Do not expand to another department just because the meeting found no complaints. Confirm the results, sample limits, and unresolved issues first. A short log that a colleague can understand is more useful than an optimistic score without supporting examples.

Copyable weekly decision log

Workflow and period:
Owner and backup:
Incoming / completed / unresolved tasks:
Examples checked and findings:
Review and maintenance time:
Usage cost and billing period:
Decision: continue / adjust / pause:
Next action, owner, due date:
Next review date:

Keep the completed log with the workflow instructions so the next reviewer can see what changed and why. The aim is a process that remains understandable and correctable as the business changes.