I would not connect a promising AI demo straight to live actions. I would first give it a narrower job: propose what it would do, record the proposal and leave the existing process in charge.
That is the shadow-mode trial I have in mind. The assistant produces a candidate answer or recommendation, but it does not send, update, reserve or purchase anything. A person compares its work with a defined baseline and acceptance criteria.
This is a suggested testing method, not a claim that a particular product is safe or that a pilot will deliver savings. Tuesday's baseline worksheet gives the comparison a starting point.
Keep the action boundary real
Consider a fictional product-question workflow. A staff member normally checks an approved product sheet and writes an answer. During the trial, the assistant receives an authorized copy of the same permitted inputs and proposes its own draft.
The staff member's normal workflow remains the route to the customer. The assistant's draft goes to a review record, not the outgoing mailbox. Where possible, give the pilot no sending or write permissions at all. An instruction that says “do not send” is not the same as removing the ability to send.
If you cannot isolate the trial adequately, use fictional records in a separate test environment instead. Do not treat a live integration as a harmless experiment just because you call it shadow mode.
Compare matched work
Use the same task definition and review criteria as the baseline. Record the input version, the draft, the reviewer outcome and any correction effort. If the source changes between attempts, note it. Otherwise you may be comparing different jobs.
For the fictional product task, review these questions:
- Did the draft use the correct product information?
- Did it add a date, price or commitment the source did not contain?
- Did it identify missing or conflicting information?
- Could the reviewer understand why a correction was needed?
- What preparation, review and rework did this attempt require?
Do not tell the assistant which answer you hope to see and then call the agreement independent evidence. Preserve both the successful and unsuccessful attempts.
Include exceptions deliberately
Try an ordinary question, an incomplete question, an outdated source and a question the available material cannot answer. These are example test cases, not a complete test plan for every business.
Write the expected behavior before the run. An incomplete source should produce an explicit gap, not an invented fact. An out-of-scope question should go to the designated person. A failed connection should leave a visible failed attempt rather than a record that looks complete.
The goal is not to make every test produce an answer. It is to find out whether the workflow behaves predictably when an answer is unavailable.
Decide what would stop the trial
Choose a trial owner and stop conditions before connecting anything. In this example, an unexpected external message, access outside the permitted inputs or an unrecorded action would stop the trial for review.
Also decide how to preserve the evidence and return to the existing process. The normal workflow should not depend on the pilot being available. If the team has to improvise the fallback after a failure, that is a finding to address, not a detail to hide.
Make a bounded decision
At review time, compare the pilot with the baseline, including the effort to prepare inputs, review drafts and fix mistakes. Report the limits of the evidence. A small trial of routine product questions does not establish readiness for contracts, refunds or unusual customer situations.
Possible decisions include stopping, improving the inputs, continuing the trial or proposing one narrowly authorized live step. “The demo looked good” is not a release criterion.
Even a useful shadow-mode result does not grant permission to act. Moving into a live workflow requires a separate decision about the exact action, reviewer, account permissions and recovery path.
My preference is a modest result you can explain over an impressive claim you cannot trace. If you want help defining a shadow-mode trial for one business task, visit White Rabbit Advisory Group at https://wrag.ai. Bring the current process and its baseline, not a promised percentage improvement.