Then quality of the power (clean sine or noise spikes) auditing, then the factor that UPS's do square wave. Though that's more stability and indeed longevity of your kit plugged that appreciates those nuances.
It is one big rabbit hole and can imagine the likes of Google having dedicated teams to focus just on power optimisations as the dividends at that scale - more than pay for the team.
By the way if you still have AC UPS systems that is probably your #1 problem and you definitely will not benefit from some fancy machine learning thing. Just get rid of most of your AC systems. For example you may benefit by adopting Open Rack 48V-to-point-of-load scheme that uses an in-rack DC UPS.
https://www.opencompute.org/files/External-2018-OCP-Summit-G...
The cut-off for that level of work I'd say is if you design your own servers over just speccing from a vendor level is when you would be doing this. Upto that, it's still vendor off shelf. Though been a while and an option some vendors may now offer at lower scales these days.
https://www.morganclaypool.com/doi/abs/10.2200/S00874ED3V01Y...
(1) Existing power usage doesn't work that way. You're basically on the hook for a predicable amount of usage. Of course, this could change, but the inertia behind this paradigm is high.
(2) Google has a bunch of hardware with relatively fixed costs that they'd prefer to run 24 hrs/day, 365 days/year.