Is Your Model Corrupting Your Model?

There is an urgency problem where you detect some sort of data drift and your model accuracy is degrading. Are there strategies to deal with or to respond really quickly in the MLOps lifecycle? I think it depends on a few different factors. Training a model might take a while. So what are some backstops that you might have to say stick with the accuracy, maybe or segment your users in a way where you get the same accuracy?"