How to evaluate an AI tool before you pay for it

New AI tools launch every week, and most of them promise to save you hours. Some will. Many overlap with features you already pay for, and a few will ask for more access to your data than they should. A short, structured evaluation saves money and avoids the awkward moment of unwinding a tool your team has already started relying on.

This guide gives you a process you can finish in a week or two, alongside normal work.

Step 1: Define the job

Write one sentence describing the task and how you'll measure success. For example:

"Draft first replies to common customer emails in our tone, saving at least half the time per reply."
"Turn our weekly call recordings into summaries with action items that need little editing."

If you can't write this sentence, you're not ready to evaluate a tool. Where AI actually saves time can help you pick a good job.

Step 2: Check what you already have

Before signing up for anything new, check:

Your productivity suite. Google Workspace and Microsoft 365 both offer AI features on some plans.
Your existing tools. Your CRM, help desk, website builder, design tool, and accounting software may have added AI features recently.
General AI assistants your team already uses on a business plan.

A dedicated tool can still be better, but it should beat what you have by enough to justify another subscription, another login, and another vendor holding your data.

Step 3: Test with your real work

Demos are built to impress. Your own work is the real test.

Collect 10 to 20 real examples of the task. Remove customer names and personal details first (see AI and your customer data).

Include hard cases: unusual requests, messy inputs, and examples where the right answer is "I don't know" or "ask a person."

Run them through the tool, and if you're comparing options, through each candidate with the same inputs.

Have the person who normally does the task score the results.

A simple scorecard:

Question	Score 1 to 5
How accurate was it? Any invented facts?
How much editing did the output need?
Did it sound like us?
How did it handle the hard cases?
Total time including review, compared to doing it ourselves
How easy was it for a non-technical person to use?

Pay most attention to accuracy and total time. A tool that produces impressive output that always needs heavy fixing may not save anything.

Step 4: Check the data and security terms

Look for the vendor's privacy policy, business terms, and trust or security page. Find answers to:

Data and security terms

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Training: Does it use your inputs or outputs to train AI models? Is that off by default on the plan you'd buy?
Retention: How long is your data kept? Can you delete it?
Underlying model: Does the tool send your data to another AI provider? Which one?
Agreements: Will they sign a data processing agreement (DPA)? Do they list subprocessors?
Sign-in: Does it support two-factor authentication and, ideally, single sign-on with your Google or Microsoft account?
Admin controls: Can you add and remove users centrally, set permissions, and see usage?
Access to your systems: If it connects to your email, drive, or CRM, what permissions does it ask for? Is that more than the job needs?
Independent assurance: For tools that will hold sensitive data, do they have a SOC 2 report or ISO/IEC 27001 certification? See security questionnaires and SOC 2.

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The full set of questions is in vendor and third-party risk.

Be wary of broad permissions

Some AI tools ask to read your entire mailbox, calendar, or file storage when connecting. That may be necessary for what they do, but it means a breach at the vendor could expose all of it. Prefer tools that let you limit access to specific folders, labels, or accounts.

Step 5: Understand the pricing model

AI tools are priced in different ways, and the model matters as much as the headline price:

Per seat: predictable, but costly if only a few people use it heavily.
Usage-based (credits, tokens, tasks, or resolutions): can be cheap at low volume and expensive at high volume. Estimate your monthly usage from your trial.
Feature tiers: key features (admin controls, SSO, data protections) may only be on higher plans.

Check the current pricing page, note when the price could change, and look at the cancellation terms. Prefer monthly billing until you're confident.

Step 6: Plan your exit

Before you commit, know how you'd leave:

Your exit plan

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Can you export your data, prompts, templates, and history in a usable format?
What happens to your data when you cancel, and how quickly is it deleted?
If the tool disappeared next month, how disruptive would that be? Newer AI companies change direction, get acquired, or shut down. Avoid building critical processes around a tool you couldn't replace.

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Step 7: Decide and set a review date

Write down:

The decision and the reason
Who owns the tool (accounts, billing, settings)
What data it's approved for
A review date, usually after three months: is it actually being used, and is it saving the time you expected?

Add the tool to your approved list and your security policy if it handles company data.

Red flags

No clear answer about whether your data trains their models
No business plan, admin controls, or two-factor authentication
Claims that the AI "never makes mistakes" or is "100% accurate"
No way to export your data
Pressure to sign an annual contract before a meaningful trial
Requests for far more access than the task needs

Frequently asked questions

How long should a trial take?

One to two weeks of real use is usually enough to judge accuracy and time saved. Make sure the trial includes the people who'll use it daily.

Should we let staff pick their own AI tools?

Let them suggest tools, and make the evaluation process quick and clear. Unapproved tools used with company data are a bigger risk than a slow approval process, but a slow process is what drives people to use unapproved tools.

Is a free tool good enough?

Free and consumer plans often have weaker data protections and fewer admin controls. They can be fine for non-sensitive tasks, but use a business plan for anything involving customer or company data.