Glossary · AI agents & automation

AI hallucination

Also called: hallucination, confabulation, AI making things up

Definition

An AI hallucination is a confident but false statement from a language model, such as an invented fact, quote, citation or product detail.

AI hallucination explained

Language models generate text that is plausible given their training and prompt. When they lack the right information, they can fill the gap with something that sounds right but isn't: a feature your product doesn't have, a price from years ago, a study that doesn't exist, or a mix of your company with a similarly named one.

Hallucinations matter for brands in two ways:

  • In AI search, assistants can state wrong facts about your business to potential customers.
  • In AI tools you build, wrong answers can reach customers or colleagues with your name on them.

To reduce them in AI search, publish clear, consistent, current facts about your company on your own site and the sources assistants rely on, and monitor what assistants say. In your own tools, ground answers in retrieved documents, require sources, limit the scope of questions the tool will answer, test with realistic questions, and keep a person reviewing anything high-stakes.

Example

A prospect tells your sales rep that ChatGPT said your software has no mobile app, though you launched one last year. Adding a clear, current features page and updating the review sites that assistants cite corrects the hallucination over time.

Why it matters

A hallucinated price, feature or policy can cost a sale or create a support problem, so accuracy needs active management.

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Published by Vidern, founded and led by Malhar Shah. Updated .

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