Measurement & risk
Hallucination
A confident AI statement that is factually wrong, unsupported, or invented.
A hallucination is a confident statement from an AI model that is factually wrong, unsupported by any source, or entirely invented. It happens because models generate plausible text from patterns, not from a checked record of truth — so fluent nonsense can come out sounding authoritative.
Hallucination is relevant to brands in two ways. First, grounding and retrieval reduce it, which is why engines that cite sources are generally safer and why being a clear grounding source protects accuracy about you. Second, models can hallucinate facts about your company — wrong pricing, features or claims — and the fix is to make the correct facts unmissable and well-corroborated so the engine grounds on them instead of guessing.
Monitoring what AI engines say about you, and strengthening the authoritative sources for your key facts, is the practical defence.
Related terms
Grounding
Constraining an AI's answer to retrieved source documents instead of model memory.
Grounding Source
The specific document an AI cites as evidence for a claim in its answer.
Fact Density
How many specific, sourced facts a passage packs per sentence.
Entity Optimization
Making a brand or topic unambiguously recognizable to engines as a distinct entity.
Prompt Injection (SEO)
Hiding instructions in page content to try to manipulate what an AI answer says.
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