When Accuracy Lies: From Smart Models to Ready Teams
A dashboard says the model is accurate. The pilot team says the interface is clear. The post-training survey says users trust the system. Everyone nods, because this is the part of AI deployment where organizations prefer numbers that look clean and verbs that sound finished: validated, launched, adopted. Then the system enters a real workflow. ...