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Machine Learning is generically defined as a method of data analysis that automates analytical model building.

That's the part that's going to have the impact---automated improvement of the way Statistics is applied to data analysis.

Is that not major enough to be considered and discussed separately?

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I think the kicker is that most machine learning is incrementing on a single model. Typically one known from statistics before. The weak learner track of combining models almost guess against this, but I think even then it is usually the same shape of model.

So, I actually agree to an extent. Much as computers can be seen as the "next logic". Only, it is such a "builds on" relationship that I think calling it next is dubious.

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