Everyone remembers the headline: Air Canada's chatbot gave a passenger wrong bereavement fare information, the airline lost the lawsuit, and suddenly every executive was asking whether they should shut down their AI chatbot.
The industry framed it as an AI liability problem. Legal teams wrote memos. Compliance departments got new budgets. Conference panels debated whether companies are responsible for what their chatbots say.
They were all looking at the wrong layer.
This was not an AI problem. This was a data pipeline problem. Specifically, it was a chunk quality problem — and it is the same problem silently running in most RAG systems deployed today.
What Actually Happened
