Every pitch sounds similar after a while
AI vendor pitches tend to blur together: faster, smarter, easier, built for businesses like yours. After a few demos, it gets hard to tell what actually separates one tool from another. A short, consistent evaluation process cuts through the sales language and gets to what actually matters for your business.
Start with the problem, not the product
Before evaluating any vendor, write down the specific task you’re trying to solve and what a good outcome looks like. A vendor demo is designed to make their product look impressive in general. Testing it against your actual problem, with your actual data or a close approximation, tells you far more than watching a polished walkthrough.
Questions worth asking every vendor
| Question | What it reveals |
|---|---|
| Does it integrate with what we already use? | Whether it fits your workflow or creates a second system |
| What happens to our data if we cancel? | Whether you’re locked in with no clean exit |
| Does it train on our submitted data? | Whether your inputs stay private |
| Who actually uses this day to day at similar companies? | Real adoption versus a good sales pitch |
Ask for a trial with your real use case
A vendor confident in their product should be willing to let you test it against a real, if limited, version of your actual problem, not just their prepared demo data. If a vendor resists this or only offers a scripted demo, that’s worth noting. It doesn’t automatically mean the product is bad, but it does mean you haven’t actually seen how it performs on your problem yet.
Check references the same way you would for a hire
Ask for a reference from a business similar to yours in size and industry, and actually call them. Ask specifically what the onboarding was like, what broke or didn’t work as expected, and whether they’re still using it a year later. A vendor’s case studies are curated. A direct reference call usually isn’t.
Watch for vague answers about pricing at scale
Some AI tools price attractively at a small scale and become significantly more expensive as usage grows. Ask directly what the cost looks like if usage doubles or triples, not just the entry price. A vendor who can’t answer this clearly may be hoping you won’t ask until you’re already committed.
Weigh the switching cost before you commit
Before signing anything, understand what it would take to leave if the tool doesn’t work out: can you export your data, is there a contract term you’re locked into, and how much staff time would unwinding it require. This question matters more than it seems like it should when you’re excited about a new tool, which is exactly why it’s worth asking upfront.
A short process beats no process
None of this needs to be elaborate. A consistent short list of questions applied to every vendor you consider, rather than being won over by whichever pitch was most polished, makes it far easier to compare options honestly and catch problems before they cost you time and money.
Evaluating a specific AI tool and want a second opinion? Visit our AI enablement page or get in touch and we’ll help you check it properly.