I think there is a big craze with regard to ML. Most people just draw a black box call it ML/Brain/"hire data scientist" without realizing that for most nontrivial problems its not going to work like magic. Some of the things that I see people underestimating is; a) how hard it is to make the magic black box b) amount of data you need c) how clean the data needs to be d) at times, you need lots of human annotated data -- cost and time to collect it e) how much it's a art than a science. Moreover, people don't have a good understating of the technical challenges and cost when you need to scale to n (features) * m (customers) * p (products). Maybe Azure solves some of these challenges but quickly looking at the pricing -- it seems like its a bit too costly.