AI Vendor Selection Checklist: 7 Questions Before You Sign

By Scott Hay, Microsoft Certified Trainer | February 17, 2026 | 6 min read

Every AI vendor claims they're "cutting-edge," "enterprise-grade," and "easy to use."

After evaluating dozens of AI tools for clients, I can tell you that most of these claims are marketing. The real difference between AI vendors that deliver results and ones that waste your budget comes down to how they answer seven specific questions.

This is the checklist I use with every client before they spend a dollar on AI tools. Print it out. Bring it to your next vendor meeting. It will save you time, money, and frustration.

The 7-Question Vendor Evaluation

1. Can You Demo with MY Data?

Not a canned demo. Not a pre-built showcase with perfect sample data.

Your workflows. Your terminology. Your edge cases.

If a vendor can't show their product working with YOUR actual business data, they're selling a brochure, not a solution. Every business has quirks — naming conventions, exception handling, industry-specific terminology. A good AI solution handles those quirks. A bad one falls apart the moment it encounters something outside its demo script.

Red flag: "We'll customize it during implementation." Translation: they haven't solved your problem yet and want you to pay them while they figure it out.

2. Who Owns the Data After Deployment?

This is the question most buyers forget to ask — and the one that costs the most when they don't.

If the vendor dodges this question or buries the answer in page 47 of their Terms of Service, that tells you everything you need to know.

Red flag: "Your data helps improve our models for all customers." That means your proprietary business data is training their product for your competitors.

3. What Happens When Your Service Goes Down?

Every service goes down. The question isn't whether — it's when, and what happens to your business in the meantime.

If they say "99.9% uptime" without explaining what the 0.1% looks like for your operations, press harder. That 0.1% is 8.7 hours per year. If those hours happen during your busiest period, the impact could be significant.

Red flag: No SLA document available, or SLA with no financial penalties for missed targets.

4. How Fast Will We See ROI?

If a vendor says "6-12 months before you see value," that's too slow for most SMBs.

A well-implemented AI solution should show measurable impact in 30-60 days. Not full ROI — but clear, measurable improvement in the specific metric you're targeting.

The key word is measurable. Before signing, both you and the vendor should agree on:

If the vendor can't define ROI metrics specific to your business, they don't understand your business well enough to solve your problem.

Red flag: "ROI varies by implementation." True, but they should still be able to give you a range based on similar clients.

5. What Does It Cost When We Scale?

Today's price is just the starting point. The real question is what happens when your usage grows.

Subscription traps live here. A tool that costs $500/month for 5 users might cost $5,000/month for 50 users. That math changes your ROI calculation entirely.

Red flag: "Contact us for enterprise pricing." Budget for sticker shock.

6. Can We Customize Without Calling You Every Time?

Your business changes. Your AI tools need to change with it.

If every minor change requires a support ticket, a professional services engagement, or a new contract, you're not buying a tool — you're renting a dependency.

Red flag: "Our professional services team handles all customization." That's a recurring revenue model for them, not a solution for you.

7. Who Else in Our Industry Uses This?

Not "we work with Fortune 500 companies." That tells you nothing about whether it works for a 25-person HVAC company or a dental office with 3 locations.

You want:

If the vendor can't share similar client references, you're the guinea pig. That's fine if you're getting a significant discount for being an early adopter. It's not fine if you're paying full price.

Red flag: "We can't share client names due to NDAs." Some NDAs are real. But if they can't share ANY reference, that's a pattern.

The Red Flags Summary

If you see three or more of these during your evaluation, walk away:

What Good Vendors Look Like

The best AI vendors I've worked with share common traits:

These vendors exist. You just need to know what questions to ask to find them.

Before You Evaluate Vendors: Start Here

Here's the thing most businesses get wrong: they start evaluating AI vendors before they know what they actually need.

The right sequence is:

  1. Assess readiness — Are your processes documented? Is your data clean? Is your team ready for change? (See our AI Readiness Assessment)
  2. Define the problem — What specific metric are you trying to improve? By how much? (See 5 Questions Before Buying AI)
  3. Evaluate vendors — Use the 7 questions above
  4. Implement and measure — Track the metrics you defined in step 2

Skip steps 1 and 2, and even the best vendor will struggle to deliver results. Because AI doesn't fix broken operations — it amplifies what you already do. (More on that in Why Most AI Projects Fail.)

Not Sure What AI Tools You Actually Need?

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