How to Evaluate an AI Tool Before You Adopt It

The fastest way to waste money on AI is to start with a tool. The sequence that works runs the other direction.

Step one: name the problem in hours or dollars

"We want to use AI" is not a problem statement. "Our team spends nine hours a week re-keying order data between two systems" is. So is "our monthly reporting takes three days and lands too late to act on." Write the problem down with a number attached, because that number is what you will measure against later.

Step two: decide what a good outcome looks like

Before any trial, agree on the target: nine hours down to two, reporting delivered in a day. Without that line, every pilot ends in a debate about whether it felt useful.

Step three: evaluate tools against the problem, not the category

Only now does vendor selection make sense, and it should be vendor-neutral. The right answer is sometimes a purpose-built platform, sometimes a workflow automation you already have licensed, and sometimes a process change with no new software at all.

Step four: govern it from day one

What data can the tool see? Who approves its output? Where does that output get stored? Answering those questions after rollout is considerably harder than answering them before. Governance is what keeps an adopted tool from becoming an unmanaged one.

What this looks like in practice

Automation is not about removing people. It is about removing repetitive work from people who have better things to do. The teams that get the most out of it are the ones who picked one measurable problem, solved it, and then moved to the next.