Why AI Gets Things Wrong (And Can't Use Your Data)

Part 1 of 8 — RAG Article Series TechNova is a fictional company used as a running example throughout this series. The Confident Wrong Answer A customer contacts TechNova support. They want to return their WH-1000 headphones — bought last month, barely used. The AI assistant checks the policy and replies immediately. Friendly. Confident. Thirty days, no problem. The policy changed to fifteen days last quarter. The return window closed two weeks ago. The customer escalates. A support agent has to intervene, apologize, and explain that the AI was wrong. Nobody on your team wrote the wrong answer. The model was not confused. It gave the only answer it could — the one it learned from a document that was accurate at the time of training, and wrong by the time it mattered. The most dangerous AI answer is not nonsense. It is the fluent, plausible answer that sounds right and was never connected to your system in the first place. Why Models Get This Wrong There are two causes. They are separat