[apohn]

I've been in Analytics + Data Science (most of that in customer facing roles) for close to a decade now, and I'm one of the first people to say there's a ton of hype in AI/ML. However, the real issue with the hype is unrealistic expectations and BS marketing, not the actual usefulness of ML/AI. This includes Data Science tutorials which are basically - 1) Here is some clean and ready data. 2)Pick the best model. 3)??? 4) $$$/Profit!! That doesn't match the real world at all.

Between myself other people I've worked with, I've seen ML/AI helping address business problems in Healthcare, Industrial Manufacturing and Operations, Energy (e.g. Oil&Gas), Consumer Goods, and Finance. These types of projects tend to succeed when they are part of a larger initiative that includes some organizational change. A lot of "let's drop ML/AI into our existing business process without changing anything" tends to fail.

As for needing an ML/AI specialist versus SWE with some basic knowledge of an ML toolkit, I think you need both. Not every business problem is a software engineering problem.

[giantg2]

I agree with the comment about hype. It seems the business people think it's either a magic bullet for all problems or that a futuristic Terminator is going to replace their job.