AI Vendor Evaluation Prompts: Pick Tools Wisely

Someone sends you a Slack message: "Hey, we're evaluating three AI vendors. Can you help pull together a recommendation by Friday?" It's Tuesday. You have a half-finished spreadsheet, four browser tabs with marketing copy, and a demo recording you haven't watched yet.

This is where AI vendor evaluation prompts actually earn their keep. Not because AI can do the procurement work for you. But because it can help you organize the chaos fast enough that you actually have time to do the thinking that matters.

The ten templates below cover the full evaluation arc: from defining what you actually need, through scoring vendors and reviewing their security docs, to writing the recommendation memo your stakeholders will read. Each one is copy-paste ready. Each one has a boundary clearly marked: where the AI assistant stops and where your legal, security, or finance team takes over.

What a good AI vendor evaluation prompt actually does

Most people approach vendor evaluation like they're shopping for a laptop. Compare the spec sheet, check the price, pick the one with the best-looking demo. Then they're surprised when the integration breaks three months later or the contract auto-renews at twice the price.

A well-built prompt doesn't fix that problem by being cleverer. It fixes it by forcing you to be specific about what you actually need before you talk to anyone. The formula is simple:

Role + Context + Task + Constraint + Output format

"You are a procurement analyst. We are evaluating [tool type] for [use case] in a [company size/industry] organization. Here are our requirements: [list]. Here are our constraints: [budget, timeline, compliance needs]. Generate [scorecard / question list / comparison summary] in [format]."

That's it. The specificity is the work. Vague inputs produce confident-sounding outputs that mean nothing.

One more thing before the templates: do not paste customer PII, employee records, contract terms under NDA, private financial data, credentials, unreleased product plans, or anything your security team would wince at into a public AI tool. Use anonymized or synthetic data for vendor evaluation work. If your organization has an approved internal AI environment, use that.

Prompt 1: Define the actual business need

Half of bad vendor decisions start before the first demo, because nobody wrote down what problem they were solving.

"Help me write a one-page business requirements document for evaluating [tool category, e.g., AI meeting transcription software]. Our team is [describe team: size, function, workflow]. The problem we're trying to solve is [describe pain point]. Our must-have requirements are [list]. Our nice-to-have requirements are [list]. Our constraints include [budget range, deployment timeline, compliance requirements like HIPAA/SOC2/GDPR, existing tech stack]. Format this as a structured requirements doc with sections for problem statement, requirements, constraints, and evaluation criteria."

Owner: The person signing the budget approval should sign off on this doc before you talk to a single vendor.

Prompt 2: Build a vendor scorecard

"Create a weighted scorecard for evaluating [tool type] vendors. Our highest-priority criteria are [list top 3]. Our secondary criteria are [list 3-5 more]. Include columns for: vendor name, score per criterion (1-5), weight per criterion, weighted score, and notes. Format as a table. Add a row for 'minimum threshold' so we can flag any vendor that scores below acceptable on a dealbreaker criterion."

Safety note: The weights you assign to criteria are a judgment call. AI can suggest criteria; you and your stakeholders decide what matters. Don't let a generated scorecard become a rubber stamp.

This is a good moment to link to the broader AI decision-making prompts guide if you want to structure the decision logic before you build the scorecard.

Prompt 3: Compare vendor claims side by side

You've got three pitch decks and a set of follow-up emails. Here's how to make sense of them fast.

"I'm going to paste anonymized notes from three vendor presentations below. For each vendor, extract: (1) their stated key features, (2) any specific claims they made about performance, reliability, or ROI, (3) what they didn't answer when asked about [integration / security / pricing], and (4) any red flags or vague language. Format as a comparison table. Label unverified claims clearly."

Important: When AI flags a claim as "unverified," your job is to verify it, not to assume the AI did. Ask vendors for documentation, customer references, and third-party audits. AI can spot the gaps in the notes; it can't call the reference.

AI vendor evaluation prompts for the hard stuff

The easy part of vendor evaluation is building the scorecard. The hard part is the questions nobody wants to ask out loud: What happens to our data? What does the contract actually say? What's the exit plan if this doesn't work? These three prompts help you get there.

Prompt 4: Review security and privacy documentation

"I'm going to paste anonymized excerpts from a vendor's security whitepaper and privacy policy. Summarize: (1) what data they collect and retain, (2) how long they retain it, (3) what subprocessors they use, (4) what certifications they claim (SOC 2, ISO 27001, HIPAA, GDPR, etc.), and (5) what's missing or unclear. Flag anything that contradicts standard data minimization practices. Format as a bulleted summary."

Non-negotiable: This output is a starting checklist for your security and legal team, not a clearance. AI cannot verify whether a vendor's SOC 2 certification is current, what it covers, or whether their subprocessors are acceptable under your agreements. Your security and privacy teams make those calls. If you don't have those teams, get the vendor's security report and have a lawyer read the data processing agreement.

Prompt 5: Map data exposure risk

Before you sign, you need to know exactly what data would touch this tool. This prompt is paired well with the AI risk assessment prompts for mapping the wider blast radius.

"We are considering using [tool type] for [use case]. The data types that would flow through this system include [list: e.g., employee names, customer emails, financial records, internal documents]. For each data type, help me assess: (1) sensitivity level (public / internal / confidential / restricted), (2) relevant compliance requirements (GDPR, HIPAA, CCPA, etc.), (3) whether this data type should be excluded from the tool entirely, and (4) questions to ask the vendor about handling this data type. Format as a table."

Owner: Legal and compliance sign off on the data classification. You're using AI to organize the conversation, not to approve the risk.

Prompt 6: Prepare demo questions

Vendor demos are theater. Everyone knows it. The demo shows you the three features that work perfectly, in a controlled environment, with no messy edge cases and no real user data. Your job is to break it.

"We are attending a demo for [tool type] from [vendor name or 'Vendor A']. Our use case is [describe]. Generate 15 specific demo questions designed to: reveal integration complexity, expose gaps in claimed features, pressure-test performance claims, clarify pricing and contract terms, and surface support and escalation processes. Include at least three questions that start with 'What happens when...' to probe failure modes."

Dmitry Kargaev covers this exact instinct in Don't Replace Me: knowing which demos are theater and which tradeoffs will hurt later is one of the genuinely human skills AI can't replicate. Speed is not due diligence.

Prompt 7: Check integration and workflow fit

A tool that doesn't connect to your existing systems is just an expensive extra tab. Before you get excited about features, check the pipes.

"We use the following tools in our current workflow: [list your stack, e.g., Salesforce, Slack, Google Workspace, Jira]. We are evaluating [new tool] for [use case]. Help me create a list of integration questions to ask the vendor, covering: native integrations vs. API-only, authentication and SSO requirements, data sync frequency and limitations, workflow steps that would need to change, and what manual workarounds would be required if an integration breaks. Also list the internal teams who would need to be involved in integration work."

For a deeper look at mapping your workflows before adding new tools, the AI workflow audit prompts are worth running first.

Prompt 8: Design a pilot

A pilot without success criteria is a vibe check with a contract attached. Don't do that.

"Help me design a 30-day pilot program for [tool type] with [vendor name or 'Vendor A']. The pilot group would be [number] users from [team/function]. Define: pilot objectives tied to our business requirements, three to five measurable success criteria with specific thresholds, a week-by-week milestone structure, what data we'll collect, who owns evaluation, and what a failed pilot looks like. Include a go/no-go decision framework at the end of 30 days."

Named owner: Someone specific is accountable for running this pilot and making the recommendation. If everyone owns it, nobody owns it.

Prompt 9: Summarize stakeholder feedback

You ran the demo, collected feedback from five people, and now you have a mix of Slack messages, a voice note, and two emails. Here's how to make that usable.

"I'm going to paste anonymized feedback from [number] stakeholders who attended the [vendor] demo or pilot. Summarize: (1) common themes in positive feedback, (2) common concerns or objections, (3) any dealbreaker comments that would block adoption, (4) which stakeholder groups had the most friction (e.g., technical vs. non-technical users), and (5) open questions that need answers before a decision. Format as a structured summary with a section for 'what we still need to know.'"

Strip any personally identifying information from the feedback before pasting. Use role labels instead of names.

Prompt 10: Write the recommendation memo

"Write a vendor recommendation memo for [tool type]. The recommendation is [proceed with Vendor X / do not proceed / request additional information]. The format should include: executive summary (3 sentences), problem we were solving, evaluation methodology, summary of vendors considered, scorecard results, key risks and mitigations, total cost of ownership over 12 months, integration requirements, pilot plan summary, and recommended next steps with owners and deadlines. Tone should be direct and factual. Mark any section where additional information is needed before the memo is final."

Before you send this: Every number in the TCO section needs to come from actual vendor quotes. Every compliance claim needs sign-off from legal or security. Every integration timeline needs validation from your IT team. AI drafted the structure; humans are accountable for every assertion in it.

This is also a good time to run the memo through the AI policy prompts framework if your organization needs to document how you'll govern the tool after adoption. And if you're still building out your automation thinking, the AI automation prompts cover what happens after you pick the tool.

What AI can't do in vendor evaluation

It can't verify that a SOC 2 certification covers what you think it covers. It can't tell you whether a vendor's pricing will hold after you sign. It can't read the contract and identify the auto-renewal clause buried in Section 14. It can't tell you whether a customer reference is real or curated. It can't approve a vendor for HIPAA compliance. It can't promise an ROI.

What it can do is help you organize your requirements, structure your questions, compare notes at speed, and write the first draft of a memo that would otherwise take you three hours on a Friday afternoon.

The rule is simple: AI does the organization. Humans make the decisions. Named humans, with actual authority, who can be held accountable if it goes wrong.

If you want the full framework for staying useful while everyone else mistakes a polished demo for a good decision, that's exactly what Don't Replace Me is built for. Rule #7 is about taste: knowing which promises matter and which ones are just a good slide deck. That's not a skill AI can do for you. It's the skill that justifies having you in the room.

Frequently asked questions

Can I use AI to evaluate AI vendors?

Yes, and it's one of the better uses of AI in procurement. Use it to build scorecards, organize notes, prepare demo questions, and draft recommendation memos. Don't use it to verify security certifications, approve compliance, or sign off on legal or financial terms. Those decisions need humans with real accountability.

What data should I never paste into an AI tool during vendor evaluation?

Don't paste customer PII, employee records, NDA-covered contract terms, credentials, private financial data, unreleased product plans, or anything your security policy classifies as confidential or restricted. Use anonymized or synthetic data in your prompts. If your organization has an approved internal AI environment, use that instead of a public tool.

What's the most common mistake in AI vendor evaluation?

Confusing a good demo with a good product. Vendor demos are controlled environments. The prompts in this guide are specifically designed to surface the questions that break demos: integration failure modes, data handling edge cases, pricing traps, and what happens when something goes wrong. See the broader guide to using AI at work for more on using AI to pressure-test instead of just validate.

How do I know if an AI-generated vendor recommendation is trustworthy?

It isn't, on its own. An AI-generated recommendation memo is a first draft and a structure. Every factual claim in it, including cost figures, compliance status, integration timelines, and customer references, needs to be verified by the people accountable for those domains: legal, security, finance, IT. The AI organizes the thinking. The humans sign off.

What should a pilot program always include?

Measurable success criteria with specific thresholds, a named owner who is accountable for the result, a defined timeline, a go/no-go decision framework, and a documented rollback plan if the pilot fails. A pilot without those elements is not a pilot. It's a slow path to an awkward contract renewal.

How do I handle lock-in risk when evaluating vendors?

Ask the vendor explicitly: what does data export look like, in what formats, and how long does it take? What happens to our data if we cancel? Is there an API? What's the migration path to a competitor? If they're vague on any of these, that's your answer. Also check contract terms for auto-renewal clauses, minimum commitment periods, and price escalation provisions. AI can help you build the question list; a lawyer should read what comes back.