Why the best AI projects start with a repetitive task, a clear measure of success and a person reviewing the output.
The best AI projects rarely start with a model. They start with a repetitive task that eats hours every week and that everyone would happily hand over.
Before choosing tools, define what success looks like: time saved, fewer errors, faster answers for customers. If you can’t measure it, you can’t improve it.
Start small and bounded: one team, one workflow, clear data sources and a person who reviews the output until the system earns trust.
Once it works, document it and extend it. The value comes from connecting the pieces, not from collecting demos.
The goal isn’t to use AI. It’s to give your team back time for the work only people can do.