AI hallucination occurs when a large language model produces output that sounds plausible and authoritative but is factually wrong, invented, or unsupported by any source. Hallucinations arise because LLMs generate text based on statistical patterns in training data rather than verified facts. They are a significant risk in high-stakes applications such as legal, medical, or financial content. Mitigation strategies include retrieval-augmented generation (RAG), human review, and grounding AI outputs in cited, verifiable sources.
Hallucination is also a brand risk: AI tools can state incorrect details about your business, services, or pricing. Our AI visibility plans monitor what AI search tools say about your brand so errors get caught and corrected.
