Automate the Repetitive Stuff First: A Framework for Picking Your First AI Project

Frequent and painful beats impressive

The most impressive-sounding AI project isn't usually the highest-value one. A flashy chatbot that handles a rare edge case is less valuable than a boring automation that removes twenty minutes of manual data entry every single day. Frequency multiplies small savings into real ones.

A simple scoring exercise

List the repetitive tasks your team does. For each one, estimate how often it happens and how much time or frustration it causes. The tasks that score high on both - not just one - are your best starting candidates. A task that's painful but rare (closing the books at year-end) is a worse first project than one that's mildly annoying but constant (manually forwarding the same type of email every day).

Start with one, not five

It's tempting to automate everything on the list at once. Resist that. Starting with a single, well-chosen automation lets the team see a real result quickly, builds confidence in the process, and surfaces lessons - about data quality, about which system doesn't connect as cleanly as expected - that make the second and third projects go faster.

This is exactly what an AI Strategy & Assessment is built to do: find where AI actually fits a specific business, before any specific tool gets chosen - so the first project is the right one, not just the first one someone suggested.