Wiki · citable explainer
AI hallucination occurs when a model generates plausible but incorrect information — a primary risk for businesses without verifiable machine-readable identity.
AI hallucination is fluent but incorrect generation. For businesses, it appears as wrong addresses, phone numbers, ownership claims, or service descriptions delivered with confidence.
Publish consistent, structured, verifiable identity evidence. Do not invent encyclopaedic notability. Prefer selective public records over bulk directory spam.
What is AI hallucination?
It is when a language model produces confident, fluent statements that are factually wrong or unsupported by available evidence.
Why do businesses get hallucinated?
Sparse, conflicting, or unstructured public data forces models to infer. Similar names, outdated listings, and missing identity anchors increase the risk.
How does verification reduce hallucination risk?
Stable URLs, server-side structured data, consistent NAP, and selective public evidence packages give models better grounded material — without guaranteeing perfect outputs.