How to evaluate an AI tool before buying it

A persuasive demonstration is not a business case. Evaluation should use real work, dated provider evidence and predetermined acceptance criteria.

Key takeaways

• Define the workflow and acceptance criteria before viewing products.
• Test the same representative tasks across shortlisted services.
• Include governance, integration, support and exit cost in the decision.

Define the job before the product

Write the workflow problem, current baseline, users, constraints and acceptable failure level before comparing features.

Test representative work

Use the same permitted source pack and scoring method across shortlisted products, including difficult and incomplete cases.

Review the whole service

Assess the exact plan, data handling, administration, support, accessibility, regional availability, integration and exit options.

Build a weighted scorecard

Score output quality, correction effort, privacy, security, administration, accessibility, integration, reliability and total cost. Weight them according to the workflow’s actual risk.

Record evidence and uncertainty rather than collapsing the decision into one unexplained number.

Run a time-limited pilot

Use a small authorised group, a baseline, support route and stop conditions. Measure complete workflow results before committing to a broad annual contract.

Action checklist

1. Write the workflow problem and baseline.
2. Choose representative and failure-case tasks.
3. Verify provider claims using current primary documentation.
4. Score quality, controls, effort and total cost.
5. Pilot with owners, measures and a clear exit decision.

A sensible next step

Create a two-product scorecard and run three controlled tasks with the same sources and reviewers. Continue with the practical AI recipes, compare the reviewed AI tools or use the AI Finder to narrow your next decision.