You’ve decided your team could benefit from an AI tool. Maybe you’ve read our guide on the first five tools to try, or maybe a vendor reached out with a polished demo that looked incredible. Either way, you’re about to spend money, and you want to know: how do I tell whether this thing actually works for my business?
This is harder than it should be. AI vendors are very good at demos. They’ve picked the perfect examples, the lighting is right, and everything works on the first try. Your actual use cases, with your messy data and your specific workflows, are a different story.
Think of evaluating AI tools like test-driving a car. You wouldn’t buy one based on the commercial. You’d drive it on your actual commute, in traffic, with your kids in the back seat.
Start with your problem, not the tool
Before you look at a single product, write down what you’re trying to solve. Be specific. “We want to use AI” is not a problem statement. These are:
“Our customer service team spends 15 hours a week writing responses to the same 20 questions.”
“Our sales team can’t find information in our proposal archive and ends up rewriting proposals from scratch every time.”
“I spend every Monday morning compiling a report from four different spreadsheets, and it takes three hours.”
Start with the pain. The clearer you are about the problem, the easier it is to judge whether any tool actually solves it. If you can’t describe the problem in one or two sentences, you’re not ready to buy a tool. You’re ready to do some thinking first.
We’ve watched businesses buy AI tools because a vendor showed them something exciting, only to realize months later that the exciting thing wasn’t related to any actual problem they had.
The test drive: what to do during a free trial
Every AI tool worth considering offers a free trial or a free tier. If one doesn’t let you try before you buy, that’s your first red flag.
During the trial, don’t test with the vendor’s sample data or example workflows. Test with yours. Here’s what matters:
Take your three most common tasks and try doing them with the tool. Not the tasks the vendor showed you. Your tasks. The emails you actually write, the documents you actually read, the reports you actually compile. If the tool can’t handle the work you do every Tuesday, it doesn’t matter how impressive the demo was.
Then test the bad cases. Give it messy inputs, ambiguous requests, something with a typo or incomplete data. Real work is messy. If the tool only works with clean, perfect inputs, it won’t survive contact with your team’s actual workflow.
Have someone non-technical on your team try it. Not your most tech-savvy person. Pick the person who will have the hardest time adopting it. If they can figure it out and find it useful within an hour, you have something worth considering. If they need a full training session just to get started, factor that cost into your evaluation.
And time everything. How long does the task take without the AI tool? How long with the tool? Include the time spent reviewing and correcting the AI’s output, because that time is real and people always forget to count it.
Questions to ask vendors
When you’re past the trial and talking to a sales rep, here are the questions that matter. Some of them will make the sales rep uncomfortable. That’s the point.
Start with data handling. “Where does my data go when my team uses this tool?” You want a specific answer, not “our servers.” Which servers? Which country? Is the data encrypted? Can their employees access it? The good vendors have clear, written policies. The ones who get vague here are telling you something. Related: “Is my data used to train your AI model?” Some tools feed customer data back into model training, which means your proprietary information could influence outputs that other companies see. Many tools offer enterprise tiers that exclude your data from training. If data privacy matters to your business, this question is non-negotiable.
Ask about exit terms. “What happens to my data if I cancel?” Can you export everything? Is it deleted? How long do they retain it? A vendor who can’t answer this clearly hasn’t thought about it.
Ask for proof. “Can you show me a case study from a company similar to mine?” Not a Fortune 500. Not a tech company. A business roughly your size, in a roughly similar industry. If they can’t, that’s not necessarily a deal-breaker, but it means you’re more of an experiment for them than an established use case.
Ask about onboarding. The answer you want to hear involves actual humans helping your team get started. The answer that should worry you is “we have a knowledge base and some tutorial videos.” Those are fine as supplements. They’re not a substitute for someone walking your team through the tool with their actual work.
And always ask: “What are the limitations of this tool?” If the sales rep says “none” or struggles to name any, end the conversation. Every tool has limitations. A rep who won’t acknowledge them is either uninformed or dishonest.
Red flags
Over the years, we’ve developed a nose for which AI vendor pitches are solid and which are smoke.
The most common red flag is the suspiciously perfect demo. Everything works on the first try, every output is flawless, the example data produces beautiful results. Real AI tools produce imperfect outputs that need human editing. If the demo doesn’t show that, they’re hiding it.
Watch for vendors who lead with the technology instead of the problem. If the first 15 minutes of the pitch are about their proprietary model and their training data, and they haven’t asked about your business yet, they’re selling technology, not something that helps you. The best vendors ask about your problem before they show you anything.
Hidden or complicated pricing is another warning sign. If you can’t figure out what it costs from the website, there’s usually a reason. Complex pricing with per-seat fees, usage fees, API fees, and premium features creates a situation where the real cost is always higher than the number they quote first. Ask for the total annual cost for your team size, including everything, in writing.
Be skeptical of any ROI projections made before the vendor understands your workflows. “This will save your team 20 hours a week” is a claim that requires knowing what your team does for 40 hours a week. And if a vendor discourages you from trying competitors, pay attention. A company confident in its product says “try us and try them, we think you’ll prefer us.” Pressure to sign quickly means they’re worried about the comparison.
Involve your team early
I keep coming back to this point because it’s where we see the most expensive mistakes. The person buying the tool is usually not the person who will use it daily. An operations director evaluates the tool, gets excited, buys licenses for the team, and three months later nobody’s using it.
The fix: bring two or three actual end users into the evaluation from day one. Let them test the tool during the trial. Ask them not “do you like it” but “would you use this tomorrow?” and “what’s annoying about it?”
The tool your team will actually use beats the tool that looked best in the demo every single time. We’ve seen “inferior” tools outperform “better” ones purely because the inferior tool was easier for a non-technical team to adopt.
If your team feels like they had a say in the decision, adoption goes up. If they feel like a tool was imposed on them, adoption craters. This isn’t an AI-specific problem. It’s a people problem. But it matters more with AI tools because most people are still uncertain about them and need to feel comfortable, not forced.
The 30-day gut check
After you’ve picked a tool and started using it, put a date on the calendar 30 days out. When that date arrives, ask yourself:
How many people on the team are actually using it? Not “have logged in once,” but actively using it at least a few times a week. Has it saved measurable time on the specific problem you bought it for? Not “it’s cool” or “it has potential,” but actual tasks completed faster. And what’s the most common complaint from your team? If they say “the output needs too much editing,” that might improve with better prompting. If they say “I forget it exists,” you have a bigger problem.
If the tool fails this check, cancel it. You can always revisit later. Too many businesses keep paying for tools nobody uses because it feels like admitting failure to cancel. It isn’t. It’s good management.
The bottom line
Evaluating AI tools is less about understanding the technology and more about asking good questions. You don’t need to know how the AI works under the hood. You need to know whether it works for your business on a Tuesday afternoon when everything is slightly on fire.
That’s what the test drive tells you. And it’s the one thing no vendor demo can fake.