I don't think this is true. It's just that there aren't many optimization practitioners and the OR community has done a terrible job promoting itself. The value in scheduling and logistics is well established. So optimizers tend to congregate. But optimization could be applied to lots of other domains successfully. ML is just minimizing a loss function. I see simulation and post-hoc analyses being applied in numerous situations where optimization would be more efficient and produce a guaranteed optimal result. RL on simple, static problems is really an MDP but I've seen organizations fail to realize this. Etc.
How often do these come up? I studied some OR stuff in grad school when I was evaluating solvers and brushed up against the OR tools community for some research ideas and from what I could tell the businesses that really needed it already use these tools and the other businesses just don't have enough business dependent on optimization to be worthwhile.
