Completely agree. Most business data is noise and most of the signals are already discovered as simple rules and heuristics. On the other hand, if you have a strong signal in your data, even a simple algorithm like linear/logistic regression will be able to help. What I’ll call “signal hunting” is probably the best use of DS resources and also the hardest thing to do.

I’ve done my share of experiments with ML/AI and where I’ve seen the most interesting value has been NLP applications (such as categorizing customer comments or assigning categories to products based in description) and finding “factors that influence behavior x” which then can be turned into either a model or a few simple rules.

I'm convinced this is one of the main sources of inefficiency in modern management, whether using AI or not. Managers are incentivized to be action prone so as to demonstrate their value continuously, and they are also expected to put in processes. Often these processes are on way too tight of a cadence and what ends up happening is that managers spend their entire time evaluating and chasing noise.