I had an intern this summer working on a project that involved mapping two data sets based on a description field. I showed him how to write a Python script using a fuzzy matching library to compare the two data sets and find matches. We then talked through the downsides of using a contextless string comparison and the situations that create false positives and false negatives.

We then tried to use a few of the AI tools to match them, hoping to demonstrate how a tool that understands context can do a better job at the expense of far more computation. All they would do was write and run a Python script using the same library, but every request would start with writing a new, slightly different script. Incredibly wasteful.

It turned into a great demo of how even if it returns a useful result, it's rarely better than a person could do in a few minutes and is far less consistent.