Machine Learning used to be considered a sub-discipline of AI (open an AI textbook and you'll see a couple chapters on it). It's grown so big that now it's a term used in and of itself outside of AI. It is starting to be seen as distinctive from "traditional" AI in some circles. So the correct understanding is either that Machine Learning is a subset of AI or that Machine Learning is a field that emerged from AI.
I don't think that's right, as the techniques are still called machine learning.
Though the distinction between the terms "machine learning" and "artificial intelligence" is somewhat unclear (depending on usage) I think a useful one is to see ML as a technique/strategy and AI as the goal.
It's also not as though AI is or means the same as "strong AI" or AGI [1].
Sort of like BigData and Web 2.0, vague terms used for almost everything.