Field note · Customer education
AI procurement checklist: what to put in a supplier trial
Turn an AI supplier demonstration into a reviewable purchase: define the workflow, test set, data boundary, acceptance criteria, full costs and exit handover.
- Source
- Editorial guidance with 1 retrieved source documents for context. Recommendations are our judgement.
- Evidence
- none on this page — it links to the pages that hold it
By Is There an AI for This? · Editorial guidance · Reviewed · How we use evidence
01Buy a defined trial with a decision at the end
Give every supplier the same brief: the trigger, the inputs, the output, the system receiving it and the person who approves it. Describe the exception as carefully as the happy path. For example, “prepare an invoice record and send any unmatched supplier to finance” is reviewable. “Automate accounts payable with AI” leaves the important work undecided.
Ask for a fixed trial scope and a list of exclusions. Separate application configuration, data preparation, integration, user training and ongoing support. If an item is excluded, assign it internally or price it separately. A supplier’s trial can appear inexpensive because your staff are expected to finish the difficult parts.
02Put the evidence request next to each requirement
- 01What precisely will the system do?WhyAn attractive demo can hide missing steps between an answer and an approved business record.A usable answerA workflow diagram, named inputs and outputs, review gates and an example exception handled end to end.
- 02Which data goes where?WhyYour data owner needs to review the proposed processing path rather than a general claim that the product is secure.A usable answerNamed services, processing and storage locations, retention settings, support access and the documents applicable to the quoted plan.
- 03How will we know whether it worked?WhyEvaluation designed after delivery can drift toward whatever the tool happens to do well.A usable answerAgreed examples, a reserved test set, a scoring rubric, quality thresholds and the time needed for human review.
- 04What happens when it fails or we leave?WhyProcurement includes recovery and exit, even when the trial is small.A usable answerA fallback process, operator runbook, export demonstration, deletion procedure and ownership of configuration and credentials.
03Use a scored demonstration with difficult examples
Include damaged scans, missing fields and a document outside the intended category. Require the supplier to explain an uncertainty instead of guessing. Have the department owner attend the review because procurement alone cannot determine whether a plausible output is usable in that department.
04Keep commercial terms tied to the actual workflow
- State the trial fee, included volume, user count, usage ceiling, support hours and any charge for failed or repeated processing.
- Identify the person who approves scope changes. Require a written effect on cost and acceptance before adding another system or document type.
- List supplier dependencies and customer responsibilities. Include access configuration, sample preparation, source cleanup and the time reviewers must provide.
- Record the export and handover format. Ask to see an export during the trial, including enough information to reconstruct why an output was accepted.
- Set a decision date and name the decision makers. Separate approval of the trial from approval of wider access, additional departments or a long-term renewal.
05Write the acceptance and stop criteria before access begins
- RECOMMENDATION
For a first departmental AI purchase, we recommend attaching the test method, data-flow review and exit demonstration to the trial’s acceptance record.
BasisThis depends on a defined workflow and a buyer who needs comparable evidence. The linked enterprise privacy document illustrates a source to review; its publication does not prove a supplier meets your requirements.
An illustrative acceptance record requires at least 90% of reserved tasks to meet the agreed quality rubric, every designated critical-error test to route to a reviewer, the cost ceiling to hold and the export drill to succeed. The exact threshold should follow the harm from an error. Passing twenty reserved examples is limited pilot evidence, not proof of a universal accuracy rate.
Stop if the supplier changes the model or processing location without the agreed review, cannot show where sensitive inputs went, or hides failed tasks from the scorecard. Also stop if your own team cannot supply an owner or usable examples. Mark the reason clearly so a failed trial produces a better purchasing brief.
06Related
Use cases
Stacks
More field notes
07Evidence
- 01Tier 2official vendor legal documentationVendor legal and technical documentation
Enterprise privacy at OpenAI | OpenAI
https://openai.com/enterprise-privacy
FreshRetrieved 19 Sep 2026sha256:925098213d771 record
08Primary-source reading
Consult these primary documents when checking a proposed product. Reading links remain available when evidence has not been verified; they do not establish that your planned use is approved or that a recommendation has been proven.