Where AI actually earns its keep

Every week someone asks us to “add AI” to their product. It is the wrong starting point. AI is not a feature you bolt on to look modern — it is a tool that either removes real work or it does not. Before we write a line of code, we look for the places where it genuinely earns its keep.

Start with the expensive minutes

The best AI opportunities hide inside work your team repeats every day: reading the same kind of document, re-typing data from one system into another, drafting the same three replies, or reconciling numbers by hand. These tasks are boring, high-volume, and forgiving of a first draft that a human checks. That is exactly the shape of problem where today's models are reliable.

• High volume, so a small time saving compounds fast.
• A human already reviews the output, so an occasional miss is caught.
• The input is text, data, or images — not a physical or legal judgment call.
• Success is easy to measure against what the team does today.

Be honest about where it does not fit

If a task needs a guaranteed correct answer with no human in the loop, or depends on context the model cannot see, AI is the wrong tool and we say so. A well-placed automation or a clean data pipeline often beats a language model for those cases — and it is cheaper to run.

The question is never “can we use AI here?” It is “what is the most expensive repetitive task, and is AI the cheapest way to remove it?”

How we decide in a 2-Hour Session

In the diagnostic we map your workflow, mark the steps that eat the most time, and score each one on volume, tolerance for error, and how clean the underlying data is. You leave with a short list ranked by leverage — and a clear recommendation on which single win to build first, on a fixed deadline.