I think ML could create a new paradigm of gaming: But it's going to take a while for the technology to get adapted by game developers, but some smarties will make the breakthrough: Kind of like John Romero's Wolfenstein/Doom: Once the games' been made, we've been seeing Doom clones ever since.
So the obvious application is board games. We've already seen this with AlphaZero (Go, Chess, etc) who now dominate those professional scene's: (Although little * beside Chess as there's a bit of a question around unfair computational equivalence of the machines used).
So any board game: Hex, etc, could (and probably should) take a ML approach to it's AI.
For 'out of the box' new game paradigm's, I always suspected gesture recognition, hand-writing/character recognition, etc, which ML can help a lot with: Touch screen, mouse drawing, or even camera 'hand' recognition.
This feels more like a gimmick than a mature solution, but it might just be me being biased against using things that you don't know how they work.
To compare with something you'd be a bit more familiar with, I always felt they(or neural networks at least) were somewhat analogous to a PID Controller. You're essentially feeding an input into a model and tweaking it to produce an output. Only with the NN model, the more data you feed in, the more 'tuned' (or corrupted!) the model becomes.
Not a 1-to-1 example: But it works for me from a 'high level' view. And just like how PID's can be used just about anything, NN's can (and are being) used for just about everything people can think of.
Not sure if GML has enough computational power to make the necessary number-crunching viable, either.
In theory, once the model is trained it should be fast. But getting the input in GML might be difficult. When Deepminds taught their AI to play the old Atari classics: Breakout, Pacman, etc. The inputs were just the pixels on the screen. GML is *slow* at reading that kind of data: So this kind of pixels-in-> controller out approach would not work in GM!