This is suspiciously close "data science" and "machine learning" experts. Can't we just be honest and say that most of these are applied statistics jobs with a specialty in large volumes of data? Or is "statistics" just not fashionable enough nowadays?
The most value I got from this article was in the realization that, every few years or so, the academic globes align well enough (some paper de joure becomes well-read I suppose) that .. for a brief instant .. terms are defined well enough, and gain enough agreement, that progress is made .. which progress attracts more eyeballs, who tend to want to break off a chunk for themselves, and the terms begin to differ again and we have a whole new 'sub-sub-sub-' variety of the subject.
So its all about globes aligning, basically. I will now go off and implement an AI technique based entirely on the description of globes, alignment, and little chunks breaking off every now and then .. see you at the top of the AI heap in a year or ten.