- Begin the assessment from the task the tool must do, not from a feature list.
- Check eight things: purpose, data, cost, licence, integrations, security, quality on your examples and the ability to leave.
- Of two similar tools choose the one that passes your test for less.
The market for AI tools changes faster than it can be followed, and every presentation looks convincing. A good purchasing decision does not follow from the number of features on a product page but from the answers to a few questions and a short trial on your own data. The list of eight questions below rests on principles described by AI risk management frameworks and security recommendations, but is written in the language of somebody buying a tool for themselves or a small team.
Eight questions before buying
First: what task must the tool do and how will you know it does it well? Without this every comparison is an impression. Second: what data will go into it and on what terms is it processed? Google’s pricing page shows an example of the distinction: data from the free tier may be used to improve products, while data from the paid tier is not. Such differences exist at most providers and decide whether you may paste confidential content. Third: what does it really cost? Calculate the cost of a task, not the subscription price, as in the article Task cost in tokens. Fourth: what is the licence and what may you do with the outputs? For example n8n is distributed as fair-code under the Sustainable Use License, so the terms of commercial use have to be read, not assumed.
Fifth: how does the tool connect with what you already use? No integration means manual data transfer. Sixth: what safeguards does it have and what risks does it introduce? Look at the OWASP list: if the tool performs actions in your systems, permissions and consents count. Seventh: what is the quality on your examples? Eighth: can you leave? Check the export of data and results and what happens if the vendor changes terms or disappears.
| What you check | A red flag | |
|---|---|---|
| 1. Purpose | A task and a success criterion | Buying "because everybody uses it" |
| 2. Data | Where it goes and how it is used | No information on processing |
| 3. Cost | Cost of a task, limits, price schedule | Only the subscription price |
| 4. Licence | The right to use outputs and code | Unclear commercial terms |
| 5. Integrations | Connection to your tools | Manual data transfer |
| 6. Security | Permissions, consents, log | Full access without control |
| 7. Quality | A result on your examples | Only the vendor's demo |
| 8. Exit | Data export, alternatives | A closed format with no export |
Typical pitfalls in assessment
The first pitfall is judging by the vendor’s demo: a demo shows the best case, and you will work on average ones. The second is comparing plans without converting to a task: a cheaper subscription with a low limit can come out more expensive than a pricier one without limits. The third is trusting the number of integrations without checking that the ones you need work as they should. The fourth is leaving out people: a tool the team does not like will not be used, so ask the people who will use it and let them take part in the trial. The fifth is no expiry date on the decision. An assessment from a year ago is no longer an assessment.
A trial on your own data
The questions let you weed out weak candidates, but make the final decision after a trial. Prepare twenty examples from real work, including a few hard ones, and set the pass criterion in advance, as in the article on evaluating agents. Pass them through two or three tools in identical conditions and record the results, time and cost. Anthropic’s documentation on evaluation stresses that success criteria must be specific and measurable and that tests should cover edge cases. This principle works the same when you choose a tool as when you build your own.
- 01TaskWhat it must do and how you will know it does it well.
- 02Question listEight points, reject candidates with red flags.
- 03TrialTwenty own examples, the same criterion.
- 04CostThe price of a task that passes the test.
- 05PilotBriefly, in one process.
- 06DecisionBuy, give up or return in a quarter.
After the purchase
The decision does not end the evaluation. Write down why you bought the tool, who owns it and when you will check whether it still pays off. Set a reminder about the subscription renewal for the day before the deadline, because automatic renewals are a quiet source of costs. Once a quarter compare usage with cost and check whether there is a better alternative, whether terms have changed and whether the team really uses it. If two people out of ten use it, the problem is not the tool but the adoption. A first plan for adopting AI in a company is described in the article AI in a small business, and the whole topic by the AI products hub.
Last checked: 20 October 2026. Terms and prices change; check providers’ current pages.