I welcome the breadth. Data science is science with data, right? What could be more broad? If anything, it will be nice to break the association somewhat between data science and AI hype.
I also think thats justified. A newer, and more specific term I particularly like is "Machine Learning Engineer", which will probably soon be recoined to "AI Engineer".
We (www.datarevenue.com) basically have to use "AI" now to make it clear what we do. Something that would have made me feel awkward just 3 months ago.
Do you see a substantive difference between AI and ML? "Machine learning" to me is pretty cut and dry, in that anytime something is automated we are employing machine learning, literally teaching a machine to do something. "Artificial intelligence" I have a hard time defining, because I don't have a good definition for "intelligence".
Behind AI I would always expect at least Deep Learning. Machine Learning I use for everything that learns it's own decision boundaries. When it's humans teaching a machine, I'd call it simply automation or expert-system.
Although a lot of "teaching" still goes into feature engineering ...
