How to Evaluate an AI Vendor in 30 Minutes

The AI vendor market is flooded.

Everyone has a platform, a solution, a copilot, an agent. The demos are polished, the case studies are cherry-picked, and the sales teams are well-trained.

And if you don't know what questions to ask, you'll make your decision based on whoever has the best presentation, which is a terrible way to spend six figures.

Most executives find themselves in the same situation: they sit through four or five demos, each one impressive, each vendor claiming they can solve the problem. By the end, everyone sounds good, everyone has Fortune 500 logos on their slides, and everyone promises transformation.

How do you know who and what is real?

You can cut through most of the noise in about 30 minutes if you know where to probe.

Start with the problem, not the technology.

Before you even take a vendor call, get clear on what problem you're solving. Not "we need AI" or "we need to be more innovative." The actual business problem. What process is broken? What decision is too slow? What's costing you money or customers?

Most vendor conversations go sideways because the buyer hasn't done this work. The vendor shows up with a solution looking for a problem, and the buyer nods along because it sounds impressive. Six months later, no one is using the tool because it didn't address any key issues.

Write down the problem in one sentence. If you can't, you're not ready to buy anything.

Ask what it can't do.

Every vendor will tell you what their product does well. That's the demo. The useful information is what it doesn't do: the limitations, the edge cases, the situations where it falls apart.

Ask directly: "Where does this struggle? What types of problems is this not a good fit for?"

A good vendor will answer honestly. They'll say something like, "We're not great for real-time applications" or "This works best with structured data; if your data is messy, you'll need to clean it first." That's a vendor who understands their product and respects your time.

A bad vendor will dodge. They'll say something like, "It's really flexible" or "We can customize it for any use case." That's a vendor who will say anything to close the deal.

Demand a real example with real numbers.

Case studies on websites are marketing. They're designed to sound good, not to inform your decision. When a vendor mentions a customer success story, push harder.

Ask: "Can you walk me through exactly what they implemented, how long it took, and what metrics changed?"

You want specifics. Not "they improved efficiency" but "they reduced processing time from 4 hours to 45 minutes." Not "they saw significant ROI" but "they saved $2.3 million annually in labor costs."

If the vendor can't provide specifics, the case study is either exaggerated or indicates they don't understand how their product delivers value. Either way, it's a red flag.

Ask about implementation.

The demo is the fun part. Implementation is where most AI projects die.

Ask: "What does a typical implementation look like? How long does it take? What do we need to provide? What are the common reasons projects stall or fail?"

Listen for honesty about complexity. If a vendor says implementation is "easy" or "just a few weeks," be skeptical. AI implementations are rarely easy. They involve data pipelines, integrations, user training, change management, and iteration. A vendor who glosses over this is either inexperienced or hiding something.

The best vendors will discuss failed implementations and what they learned. That's the kind of honesty that builds trust.

Find out what happens when it breaks.

AI systems fail, models degrade, and outputs change. This is normal. The question is what happens next.

Ask: "When something goes wrong—and it will—how do we know? What does your support look like? What's your response time? Do we have access to someone technical, or just a help desk?"

Also ask: "How do we monitor ongoing quality? What visibility do we have into whether the system is performing as expected?"

Many vendors sell a product and disappear. You want a vendor who treats the relationship as ongoing, not transactional. AI isn't something you deploy and forget; it requires continuous attention.

Understand the data requirements.

AI runs on data. If the data isn't ready, the AI won't work, no matter how good the vendor's technology is.

Ask: "What data do you need from us? What format? What volume? What happens if our data is incomplete or messy?"

This question exposes whether the vendor understands real-world conditions. If they assume your data is clean and well-organized, they've never worked with actual companies.

Every company has data problems. A good vendor has strategies for dealing with that. A bad vendor will blame you when the implementation fails because your data "wasn't what they expected."

Ask who's actually building this.

Many AI vendors resell other vendors' technology with a wrapper, which isn’t necessarily bad, but you should know what you're buying.

Ask: "What's your underlying technology? Are you building your own models or using third-party APIs? If OpenAI or Anthropic changes their pricing or terms, how does that affect us?"

This matters for cost predictability, for understanding where the real intellectual property lives, and for knowing who to blame when something breaks. If the vendor is a thin layer on top of someone else's infrastructure, you might be better off going directly to the source, or at least understanding what value the vendor is actually adding.

Watch how they handle questions they can't answer.

This is subtle but important. During the conversation, ask at least one question that's slightly outside the standard pitch. Something specific to your industry or use case.

Watch how they respond. Do they admit they don't know and offer to find out? Do they make something up? Do they redirect back to their script?

The response provides a clear indication of what working with them will be like.

Trust your gut on the people.

At the end of the day, you're not just buying software. You're entering a relationship with a company. You'll be working with these people for months, maybe years. If something feels off, if they're too pushy, too slick, too eager to close, pay attention to that.

The best vendor relationships are partnerships. The vendor is genuinely invested in the customer's success because their reputation depends on it. The worst relationships are transactional, where the vendor disappears after the check clears, and the customer is left holding a tool they can't implement.

The 30-minute filter.

You don't need hours of demos to evaluate an AI vendor. You need the right questions:

If a vendor can answer these questions clearly and honestly, they're worth continuing the conversation with. If they dodge, deflect, or default to buzzwords, move on. There are plenty of vendors out there. The job is to find one who will actually solve the problem, not just sell the idea of AI.

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