How Are Companies Managing Data Accuracy with Increasing Integrations and Automations?

I am wondering how people are handling the data layer with increased integrations and automations? What I've seen so far is that AI handles the execution layer well but the data it runs on doesn't stay clean on its own. Three or four tools all writing to the same CRM records, and by the time it shows up wrong in a forecast or a board deck the problem has been sitting there for weeks. How are people handling data accuracy as the automated workflow count goes up? Curious if this is a solved problem anywhere or if everyone's managing it reactively.