I've published two papers on using HE for ML and it's nice, but also alarming, to see big players like Google and Microsoft making decent tools for performing HE. Although the technology is still much farther out from being commercially viable, it does pose an interesting problem about how these data aggregation companies will utilise a tech that is inherently private.
One potentially simple answer is: to make things that are otherwise illegal (for regulatory reasons) possible.
There are some instances of hand-built cryptographic protocols used in production at Google that use FHE in small doses (e.g., computing a single dot product as part of an interactive protocol), so the big question is whether having a general-purpose tool will expand the feasibility of applying these to other, maybe less critical projects that still want some privacy guarantees but can't afford to hire cryptographers.
I guess I'm curious from your perspective what and why makes the tech from being commercially viable, and the concerns of big players adopting this (which was always going to happen I imagine, but when shapes a lot of the future of the field).