AI is already woven into everyday work, powering dashboards, copilots, customer journeys, and planning tools. But even with all this adoption, most teams still don’t trust what they’re seeing. In most cases, the issue isn’t the model, it’s what’s feeding it. When customer records are outdated, recommendations miss. When internal sources don’t line up, GenAI outputs feel wrong or, worse, misleading. Bad data slows teams down, introduces risk, and puts trust and reliability in question.