An impressive AI demonstration can make an ordinary workflow look effortless. The harder question is whether the system will work with your documents, exceptions and staff responsibilities after the demonstration ends. Begin with that operating reality.
This is an original buyer checklist for planning a small pilot. It does not claim that AI is suitable for every process or that a particular provider has passed an independent assessment.
Choose One Workflow With a Clear Boundary
Pick a task that has an identifiable beginning, end and owner. An internal assistant that locates approved product information is easier to scope than an instruction to automate customer service. Write down where the information comes from and who confirms the final answer.
List the cases the pilot should not handle. For example, a product-information assistant might route custom pricing or contractual questions to a person. A boundary like this makes the acceptance test clearer for both the buyer and the supplier.
Use a Small Pilot to Test the Difficult Cases
Prepare examples before the supplier tunes the system. Include ordinary requests, incomplete information, contradictory documents and questions with no answer in the approved material. Keep a second set of examples for checking the finished pilot.
| Pilot Question | What to Observe |
|---|---|
| Can the system answer a supported question? | Accuracy and the evidence shown |
| What if a document is outdated? | Version handling and escalation |
| What if the request is outside scope? | A clear refusal or human handoff |
| What if an integration fails? | Recovery, logging and ownership |
These are suggested procurement checks, not a certification test. Adapt them to the workflow and the consequences of a mistake.
Ask Who Controls the Data and Accounts
Request a plain-language account of where information is stored, which services receive it and who can access it. Ask what can be exported if you change suppliers. Keep an inventory of the accounts, subscriptions and integrations created for the project.
The NIST Generative AI Profile, published on 26 July 2024, is a companion to its voluntary AI Risk Management Framework. It provides a useful reference for structuring a risk discussion; it does not certify a supplier.
Price the Work After Launch
A proposal should distinguish setup, usage charges, ongoing support and changes. Ask who checks whether an updated document still produces an appropriate answer. Establish how the supplier will investigate an error and when it will be escalated to your team.
For a hypothetical purchasing team, a useful pilot might save time gathering supplier information while leaving approval with a manager. The desired result is a dependable task with clear accountability, not the largest possible number of automated steps.
Choose a Partner You Can Continue Working With
Look for explanations your team can repeat in its own words. Request the runbook, test results and handover materials as deliverables. Before signing a longer agreement, compare companies using the same workflow, example set and support expectations.
You can post your requirement with the chosen workflow and its limits. A precise request gives a potential partner a better chance of explaining the work and gives you a fairer basis for comparing responses.
