AI vendor RFP checklist template: questions to pin down, with working examples

A manufacturing company came to us recently with an RFP they'd written for three AI vendors. Fourteen pages, carefully drafted. But it was filled with vague language: "must possess leading-edge artificial intelligence capabilities" and "support flexible scaling." When we asked whether the three responses could be compared line by line, the answer was no. Each vendor had answered a different question.

A poorly written RFP creates problems after you sign, not before. Vague fields let vendors interpret them loosely. You launch and discover that "enterprise system integration" doesn't include your twenty-year-old ERP. This article provides a fillable RFP template for AI projects. The focus isn't formatting. It's making sure every field draws out answers you can verify, compare, and write into a contract.

Why AI project RFPs differ from standard software procurement

Traditional software procurement focuses on features: Do you have this module? Does it support that format? AI projects are different. Their success depends on questions that traditional RFPs rarely address: data source, responsibility for hallucinations, and whether adoption actually happens after launch.

We've seen projects where demo accuracy reached 98%, but accuracy on real customer data dropped to 60%. Demos use clean sample datasets, but contracts rarely require vendors to validate against your actual data. This template follows one principle: move problems that typically surface after launch into procurement, where they're still manageable.

The RFP checklist

Each row is a field. The left column shows what to ask. The middle column explains the risk you prevent. The right column gives an example you can adapt.

Complete the first six fields before sending the RFP. That subset alone distinguishes vendors who discuss capabilities well from those who can execute them.

Three fields commonly overlooked

Three fields deserve close attention. Inclusion of "Acceptance Test Data Set" changes how vendors respond; they can't rely on clean sample data. "Users & Adoption Goals" matters equally: put weekly active rate in numbers, and vendors face the question most avoid, will people actually use this after launch? Finally, "Pricing Model & Hidden Costs" is critical because usage fees scale with volume in RAG and Agentic workflows. Looking only at license fees during procurement hides costs that appear later.

Final check before sending

After filling the checklist, review it once more. Can each answer be compared directly with other vendors' responses? Can each answer be written into acceptance criteria? If an answer relies on trust rather than verification, that field is incomplete. An RFP's value doesn't come from the number of questions you ask. It comes from whether every answer received can actually be verified.

When we help customers identify AI requirements, we don't start with tool selection. We start by filling this checklist until every field can be verified. One principle guides this approach: a polished demo doesn't determine success. What matters is whether people use the system after launch. Use this checklist to test both your vendors and yourself. It will help you avoid most of the problems that emerge during implementation.