You know you are buying the right AI solution when you can say exactly which problem it solves, it fits how your people already work, it handles your data safely, it has been tested on your real tasks and the people who will use it want it. If any of those is missing, you are likely buying a demo rather than a solution.
Seven checks before you buy
1. Is the problem defined?
Write the problem in one sentence, with a number: "Our support team spends around half its time on repetitive questions." If you cannot, you are not ready to choose a tool.
2. Have you tried general tools first?
Many problems can be solved with general AI assistants you may already have. Specialist tools make sense when they offer something clearly better for your specific workflow, not just a nicer interface on the same technology.
3. Has it been tested on your real work?
Insist on a trial with your actual documents, data and tasks, run by the people who would use it. Polished vendor demos use ideal examples. Your reality will be messier.
4. Does it fit your workflow?
A tool that adds steps, requires switching between systems or duplicates data entry will be abandoned. Watch people use it during the trial and note where they struggle.
5. Is your data protected?
Check where data is stored, whether it is used to train models, how access is controlled and how it complies with UK GDPR. Involve your data protection lead before signing, not after.
6. Do users want it?
Ask the trial users directly: would you choose to keep using this? Lukewarm answers predict low adoption, whatever the features.
7. Can you leave?
Understand contract length, data export options and what happens if you switch. Avoid long lock-ins while AI tools are changing so fast.
Comparing options
When comparing two or three solutions, score each against the same criteria:
| Criterion | Weight | Option A | Option B |
|---|---|---|---|
| Solves the defined problem | High | ||
| Fits workflow | High | ||
| Data protection | High | ||
| User preference | Medium | ||
| Total cost | Medium | ||
| Contract flexibility | Medium |
Score with the trial users, not just procurement.
Red flags
- The vendor cannot explain how it handles your data.
- Pricing is unclear or rises sharply after year one.
- The trial is only possible with their sample data.
- Promises of dramatic results with no customer references.
- Pressure to sign quickly.
For a more detailed buying checklist, see our guides on questions to ask before buying AI tools and how to evaluate AI software.
The buyer matters as much as the tool
The best protection against a poor AI purchase is a buyer who has used AI tools extensively and knows what good looks like. Our Leading AI Innovation & Organisational Transformation course gives managers hands-on experience with mainstream AI tools, so they can judge solutions on substance rather than sales pitches.
Frequently asked questions
How long should an AI tool trial last?
Long enough for real users to try it on real work, typically a few weeks. Short demos are not enough to judge fit.
Should IT or the business choose AI tools?
Both. The business judges fit and value; IT checks security, integration and support.
What if we already bought the wrong AI solution?
Review usage honestly, check your exit terms and redirect the budget if needed. Continuing to pay for an unused tool is the most expensive option.