Actually, you kind of are already in the RL space when using AB testing to make online decisions, you just may not be thinking of it that way. From Sutton & Barto "Reinforcement learning is learning what to do--how to map situations to actions--so as to maximize a numerical reward signal." That is exactly what you are doing when applying A/B style hypothesis testing to inform decisions in an online application. Plus, personally, I think A/B testing is, in a way, much harder to interpret, at least most folks interpret wrong, which isn't a knock, since it is provides a non-intuitive - at least to me ;) - result.