Hallucination
When an AI model states something false or invented as if it were fact.
In depth
What it really means
A hallucination is when an AI model produces confident, plausible-sounding information that is simply wrong: a fake statistic, a misattributed quote, a product feature you don’t have. It happens because the model predicts likely text, not verified truth.
For brands, hallucinations are a risk and an opportunity. Wrong claims about you can spread, but clear, accurate, retrievable content reduces the chance a model invents something in the gap.
Best practices
- Publish accurate, unambiguous facts about your brand.
- Make key details, pricing and features easy to find and current.
- Monitor what AI assistants say about you.
- Correct wrong information at its source where you can.
- Give models grounded content so they retrieve rather than guess.
FAQs
What is an AI hallucination?
When a model states something false or invented as if it were fact, because it predicts plausible text rather than verified truth.
Why do LLMs hallucinate?
They generate likely-sounding language, and when they lack grounded information they can fill the gap with confident but wrong details.
Can hallucinations hurt my brand?
Yes. A model can state wrong facts about your product, so clear, accurate, retrievable content is your best defence.
How are hallucinations reduced?
Grounding answers in retrieved sources, like RAG, gives the model real facts and cuts down invention.
What if an AI says something wrong about us?
Fix the underlying information where you can, publish clear correct facts, and monitor how assistants describe you.
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