Why does the same wrong fact show up on several AI platforms?

AI platforms don't check facts against each other. Each one pulls from what it can reach, and much of what they reach overlaps. When three engines repeat the same wrong price, the likeliest explanation is one page they all read.

It helps to split an answer into the four stages that produce it:

• Parametric: what the model learned in training, frozen at a cutoff. Without live search, this is all it has.
• Access: whether a crawler can fetch your page at all.
• Retrieval: which pages enter the answer for a given question.
• Generation: which retrieved pages the model uses and cites.

A wrong fact can enter at the parametric stage (old text in training data) or at retrieval (a live page that states it). Either way, one source upstream of several engines produces the same error in all of them. So the fix is to find the source, not to argue with each chatbot. The same logic explains which brand facts AI engines get wrong most often.

On your own site

Your site can contradict itself. The pricing page says one thing, while an old blog post or the footer says another. Engines that fetch both may quote the wrong one.

The second failure is invisibility. Vercel's crawler study (December 2024) found ChatGPT and Claude crawlers fetch JavaScript files but don't execute them, so they can't read client-side rendered content. If your correct price appears only after JavaScript runs, those engines may never see it. They fall back on whatever other pages say.

On third-party pages

Review sites, directories, comparison pages and old press coverage get retrieved by several engines. If one of them carries an outdated fact, every engine that retrieves it can repeat it. A competitor's page is its own case, covered in what to do when a competitor's comparison page misrepresents you.

In training data

Older public text shapes what models say without search. As of October 2026, OpenAI lists a February 16, 2026 knowledge cutoff for its GPT-5.6 models and August 31, 2025 for the Instant model used in ChatGPT. A fact that changed after those dates can't reach an answer given without retrieval. Nobody can change that before the next model ships.

• A few sources dominate. A 2025 study of AI search citations (arXiv:2507.05301) found the top 20 news sources accounted for 67.3% of all citations for OpenAI models, using data from March to May 2025. When citation is that concentrated, one wrong fact in a popular source travels far.
• The index decides who shares an error. In Otterly's 2026 experiment, Google deindexed two test sites and Google's AI surfaces almost stopped citing them. Bing kept them, and Microsoft Copilot kept citing them. Engines on the same index share its contents. Engines on different indexes can disagree.
• Cited is not the same as used. OpenAI's API returns the full list of sources a search consulted separately from its citations, and the consulted list is often longer. The page causing the error may not be the one shown.
• Manipulated pages exist. A 2026 study (arXiv:2606.16821) measured how search agents behave once manipulated content is in their results. Third-party pages with hidden instructions about a brand are a real reputational risk, and a reason to read odd sources closely.

Not every repeated error traces back to one page.

• Guessing from absence. If no page states your headcount or founding year, an engine may fill the gap. Several engines can land on similar wrong answers. The fix is to publish the fact clearly, not to hunt for a source that doesn't exist.
• Retrieval was off. Answers given without search come from training data. You'll see no citations, so there is nothing to trace. Check whether the engine searched before you look for a page.
• Different errors on the same topic. If engines get your pricing wrong in different ways, you probably have several bad sources, or none. Treat each engine as its own case.

Errors with no source at all are covered in our guide to AI hallucinations about brands.

1. Log the error per engine. Record the exact wording, the date, and whether citations appeared. An AI error log and correction tracker keeps this consistent over time.
2. Follow the citations. Open each cited URL and search it for the wrong fact. The full method is in how to find which source caused AI to get a fact wrong.
3. Check your own site first. Look for contradictions across pricing, about, footer and old posts. Make sure the correct fact is in the HTML before JavaScript runs.
4. Check access. robots.txt rules are per bot: OAI-SearchBot controls ChatGPT search, while GPTBot governs training only. A firewall or CDN can still block a crawler that robots.txt allows. The AI Crawler Checker requests a page as each AI crawler and shows which ones get turned away.
5. Fix third-party sources where they live. Update your own directory and review profiles, and ask other site owners to correct their pages. Platform specifics are in correcting Perplexity and fixing wrong facts in Microsoft Copilot.
6. Recheck each engine separately. Search-based answers can change after engines re-crawl. Training-data answers wait for a new model. The free checker on this site gives a snapshot of what engines say for three buyer questions.