I do research in a neighboring domain, and have sort of dabbled in these sorts of datasets before, with a tiny bit of ML-ish research on different topics. It's an area I've thought about expanding into.
My sense is that the sorts of EMR/EHR records you're linking to aren't fine-grained enough for the most part to be useful for the sorts of things that will constitute AI's presence in healthcare. I think they are incredibly, incredibly useful, and will find a place in AI research (I've edited papers using these sorts of datasets with AI), but my sense is that they're not the sort of thing that will give AI a foothold.
I think your sentiment and that of the OP is right in that there isn't likely to be anything major this year, but I think AI/ML will have a bigger presence over the next 10 years than people are currently expecting. There's too much research showing that many tasks currently done by clinicians can be done better algorithmically by a machine, and in contrast to a lot of fields, the content matter is supposed to be approached that way--quantitatively and scientifically.
What is needed is a lot of very fine-grained data. Not visit data or event summaries, diagnoses, procedures, providers, but actual specific image files, etc. and so forth. My experience is that this stuff is in EMRs sometimes, but not consistently, and is never made publicly available. Some of the data--much of it maybe--is not actually in hospital records at all. It might be sitting in R&D or university labs somewhere, or isn't being collected at all.
My guess is that big corporations will start collecting this data one way or another, or researchers will establish consortiums, or apps will start amassing it as they gain traction, and that's how this will proceed.