Choose the task before the product. A convincing demonstration tells you what a tool did with the supplier’s examples. Your decision depends on what it does with the work you receive and the checks you need.
Suppose you want to turn long meeting notes into short follow-up emails. You could improve your existing email template, use a standalone AI drafting tool or use an AI feature already available in your software. Start by comparing those approaches on the same suitable notes.
Make the comparison fair
Here is a fictional comparison, with no product claims or measured results implied:
Approach | What might make it useful | What the trial needs to establish |
|---|---|---|
Existing template | Familiar, predictable structure | Whether filling it in is already quick enough |
Standalone drafting tool | Can organise varied notes into prose | Whether preparation and corrections outweigh drafting time saved |
Tool inside existing software | May reduce copying between windows | Whether it can access the right material under suitable terms and permissions |
Ask each approach to produce the same useful result. Include notes with a missing date and a meeting with no agreed action. A system that invents a commitment should not win because its prose is polished.
Count the effort of preparing inputs, reading, correcting and using the output. If the standalone tool saves three minutes of writing but adds five minutes of copying and checking, the apparent writing speed is misleading.
Check the arrangement you would actually buy
Confirm the product, plan and settings used in the trial. Ask about costs at your volume, contract length, support, access controls and how to retrieve your work if you leave. Check information handling before introducing customer or confidential material.
A feature in a demonstration may require a different subscription or a connection that your business has not approved. Get those dependencies into the comparison before committing.
Decide what a good result would justify
Agree the requirements before reviewing the outputs. That keeps an attractive demonstration from quietly changing the standard.
You may find that the template handles most meetings and an AI draft helps with a narrower set. You may find that the existing software is enough. If a candidate looks useful, test it more broadly before relying on it for work the first sample did not cover.
The trial guide explains how to record the evidence. The buying decision should remain tied to the task you tested.
About Jay
I’m Jay Janes, a Practical AI Advisor and founder of Reformat Labs. I write about choosing useful work for AI, checking the results and supporting the people using it.