Guides · Nov 7, 2026 · 5 min
A practical checklist for evaluating AI tools — from output quality to data handling and total cost.
Start with the job, not the model. Write down the specific task you want to speed up and what a good result looks like. A tool that is impressive in a demo but mediocre on your real work is not the right tool.
Test on your own material. Use real documents, real briefs and real data during a trial. Compare output quality, speed and how much editing the results need.
Read the data terms. Check whether your inputs are stored, for how long, and whether they are used for training. These answers matter more than any feature list.
Estimate total cost. Usage-based pricing can be cheap for experiments and expensive at scale. Model your expected monthly volume before you commit.
Plan for the team. Seats, permissions, invoicing and support become important the moment more than one person relies on a tool.
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