AI Hallucination
AI hallucination is when an AI model confidently generates information that sounds plausible but is factually incorrect or entirely made up.
How AI Hallucination works
Because an LLM predicts likely-sounding text rather than retrieving verified facts, it can state incorrect information — a wrong statistic, a fabricated quote, or a nonexistent legal clause — with the same fluent confidence as correct information.
Why it matters for your business
This is the single biggest reason businesses need a review step before publishing or acting on AI-generated content, especially for anything factual, financial, or legal. Understanding hallucination isn't a reason to avoid AI — it's the reason to use techniques like Retrieval-Augmented Generation and human review alongside it.
Frequently Asked Questions
Why do AI models hallucinate?
LLMs generate text by predicting the most statistically likely next words, not by looking up verified facts — so when they lack real information, they can produce fluent-sounding but false answers.
How can a business reduce AI hallucination risk?
Ground answers in real documents using RAG, ask the model to cite sources, use lower 'creativity' settings for factual tasks, and always have a human review AI output before it reaches a customer or a decision.