---
title: "AI hallucination"
url: https://marketingsignals.com/glossary/ai-hallucination
type: Page
---

# AI hallucination

AI hallucination explained: why ChatGPT and other assistants state false facts, how it affects brands and what to do when an AI gets your business wrong.

GEO glossary

## AI hallucination

AI hallucination is when an AI assistant like ChatGPT or Gemini states something false or invented as if it were fact, for example a wrong price, a made-up statistic or a source that does not exist. OpenAI defines hallucinations as plausible but false statements generated by language models.

## Why do AI models hallucinate?

A language model generates likely words, not a checked answer. In a paper published on 5 September 2025, OpenAI gave two reasons. Pretraining has no true or false labels, so rare, arbitrary facts such as a person's birthday cannot be learned from patterns. And most evaluations score accuracy alone, which rewards a model for guessing rather than saying it does not know.

Search reduces the problem but does not remove it. An assistant that retrieves pages can still misread one, mix up two similarly named companies or rely on an out-of-date source.

## How hallucinations affect brands

The errors that hurt a business are specific: old prices, discontinued products described as current, invented features, a former address, or a competitor's details attached to the brand name. OpenAI's point about rare facts applies here. A brand mentioned in only a few places gives a model little consistent information to learn from.

## What to do when an assistant gets your brand wrong

Start by finding where the wrong fact comes from. If the answer cites sources, the error often traces back to one page. Feedback reports go to the platform and are not a guaranteed correction, so fixing the sources the assistant reads matters more.

- Record the prompt, platform, date and the wrong statement
- Check the cited pages and ask the owner of an inaccurate one to correct it
- Publish the correct facts plainly and with a date on your own site, with Organization structured data
- Make sure profiles, directories and your knowledge panel say the same thing
- Use the platform's feedback tools, such as Report a problem on Google AI Overviews
- Re-test the same prompts each month to see whether the answer changes

## Example

An assistant tells users that a software company's cheapest plan costs £49 a month, a price it dropped a year ago. The cited source is an old comparison article. The company dates its own pricing page, asks the comparison site to refresh its table and tracks the prompt until the answer changes.

## Related terms

- [Large language model (LLM)](https://marketingsignals.com/glossary/large-language-model)
- [Entity SEO](https://marketingsignals.com/glossary/entity-seo)
- [Knowledge graph](https://marketingsignals.com/glossary/knowledge-graph)
- [Prompt tracking](https://marketingsignals.com/glossary/prompt-tracking)
- [AI citations](https://marketingsignals.com/glossary/ai-citations)

## Further reading

- [How to Measure Performance in AI Search](https://marketingsignals.com/insights/how-to-measure-performance-in-ai-search)

Our [AI SEO & GEO](https://marketingsignals.com/service/ai-search-optimisation) service puts this into practice for brands in the UK and US.

## Sources

- [Why language models hallucinate, OpenAI (5 September 2025)](https://openai.com/index/why-language-models-hallucinate/)
- [Find information in faster and easier ways with AI Overviews in Google Search, Google Search Help](https://support.google.com/websearch/answer/14901683)
- [Organization structured data, Google Search Central](https://developers.google.com/search/docs/appearance/structured-data/organization)
- [A reintroduction to our Knowledge Graph and knowledge panels, Google (20 May 2020)](https://blog.google/products/search/about-knowledge-graph-and-knowledge-panels/)

## Ready To Get Found In AI Search?

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