An AI demonstration can look convincing in a few minutes. Deciding whether it belongs in your business takes a different kind of conversation.
Before comparing tools, try writing the test they would have to pass. Pick one workflow. Describe what a useful result looks like, which mistakes would matter and who will review the outcome. That gives the demonstration a job: show whether the proposed system can meet your requirements.
You can start with one page. I call it a pass-bar card.
Start with a piece of work you can describe
“We need AI in operations” leaves too much open. “Turn an incoming service request into a draft work order for an operator to review” is easier to examine.
Write the starting input and the intended output. Name the person who receives it. Mark where the workflow ends. A draft work order, for example, does not include sending a price, promising an appointment or changing the job schedule. Each additional action needs its own decision and test.
For a first exercise, use fictional information. You can work out the process before deciding what real information a provider should be allowed to handle.
Put the ordinary case beside the difficult ones
Imagine a fictional maintenance company, Harbor Service Desk. It receives this request:
“The storeroom door will not close. Please call tomorrow after 10. Site: Harbor Annex.”
The proposed output is a draft work order that preserves the site and request, records the callback preference and leaves the appointment unconfirmed.
Now change the input. Remove the site. Give two different callback times. Add a second message that corrects the location. Say that the requester does not know whether the problem is urgent.
These are different tests. Agree the expected behavior for each. A missing site might require a question. Conflicting instructions might require operator review. Unclear urgency might require the company's existing escalation procedure. A polished paragraph does not make those decisions correct.
Define failure in observable terms
“It should be accurate” is hard to review consistently. “The system must not invent a site, price or confirmed appointment” is clearer.
Your card can include requirements such as:
- Preserve the requested task and the source information needed to check it.
- Identify missing required information rather than filling it in.
- Flag contradictory instructions for review.
- Keep externally consequential actions behind an authorized human decision.
- Make the next operator step visible.
Some requirements are stop conditions. If the fictional test produces an invented appointment confirmation, you may decide the workflow cannot proceed until that behavior is fixed. Other errors might be recorded for improvement. Make that distinction before reviewing the results.
Measure the work you already do
You need a baseline to judge whether a change helps. Record how the current process handles a comparable set of cases: operator time, corrections, unresolved items and any other measure that matters to the workflow.
Then compare the proposed process on the same basis. Include the time spent checking its output and resolving its exceptions. A fast draft can still create work for the reviewer.
If the baseline is missing, write “baseline not yet measured.” That is a useful open task. It should not turn into an assumed saving or a percentage improvement.
Give uncertainty somewhere to go
A human fallback should describe an actual handoff. Who sees an exception? What information do they receive? What can they decide? What happens if they are unavailable?
For Harbor Service Desk, the card might say: “Ambiguous site or conflicting instructions go to the operations reviewer with the original request and the reason for escalation. No appointment is promised while the case is unresolved.”
That is still a fictional proposal. The real owner would need to approve the operating rule, assign a person and agree a response expectation.
Agree how the pilot will be reviewed
Name a reviewer and a review date. List the cases and the pass criteria. Decide who has authority to continue, revise or stop the pilot.
A small practice set can expose problems and improve a design. It does not establish reliability across the entire business. Describe the cases actually tested, preserve the failures and avoid expanding the conclusion beyond that coverage.
The card is a beginning, not a certification. A live workflow can also require access controls, data-handling decisions, operational support and further testing appropriate to its use. NIST's voluntary AI Risk Management Framework provides broader context for considering trustworthiness throughout AI design, use and evaluation. NIST AI Risk Management Framework
Take the card into the buying conversation
Now ask a provider to demonstrate the workflow against your examples. Ask how missing information is handled, where exceptions appear and what remains for your team to do. Compare approaches against the same requirements.
The useful outcome may be a narrower pilot, a different implementation or a decision to improve the current process first. Writing the test helps make that choice concrete.
If you are still deciding which workflow to examine, start with Mallacore's Offer Matcher. Bring one ordinary business problem and use harmless example information. Once the workflow is clear, write the pass bar before choosing the tools.