[elwes5]

Your perspective is not just 'non-us'. The thing is since the early 80s computers can generate huge swaths of data. ML gives you a way to filter that data in a particular way. The same was true of data warehouses, smart systems, etc. The issue is not the business people vs technical people. It is an understanding of what do you want it to do. A few years ago I had a system that could generate 2k in data samples every few seconds (switches, voltages, temps, etc). What are you even looking for in that pile of stuff? You can not just feed that into a ML network and hope for the best. You have to describe what you are looking for. I had this same conversation over and over when working with data warehouse projects. A good BA on a project like that is amazing. Someone who is just kinda meh on it will kill the project dead. I do not understand your business, you do. I can apply what I have learned from other companies but only to a point. After that point I basically have to become a BA in that company just to understand what to write.