Why AI models hallucinate
- Models predict likely words, not verified facts, so a fluent wrong answer can come out as easily as a right one.
- Gaps in training data, or old information past the knowledge cutoff, push the model to guess.
- Search results can be outdated or wrong, and the model may repeat them or mix two sources.
- Similar names, products or companies get blended together.
Common brand hallucinations
- Old or invented prices and plans.
- Features you never had, or ones you removed.
- Wrong founders, locations, integrations or availability by country.
- Confusing you with a company that has a similar name.
How to reduce hallucinations about your brand
- 1Find them: ask the questions buyers ask across engines and markets, and read the answers.
- 2Trace them: look at the sources cited next to the wrong claim.
- 3Fix the source: update your own pages and ask third party sites to correct old information.
- 4Make facts easy to find: a clear pricing page, an about page, structured data and an llms.txt file.
- 5Check again over the following weeks to confirm the answer changed.
What it means for brands
- Hallucinations about your price or features can cost sales without you ever seeing it.
- You cannot edit a model, but you can fix the pages it reads.