ChatGPT Is Giving Wrong Information About My Business. How Do I Fix It?

An assistant told a prospect your company does something you stopped doing three years ago. Or quoted a price you no longer charge. Or attributed another business’s complaints to you. The instinct is to look for the report button.

There isn’t one. No AI engine offers a mechanism to edit its answers on request, and the guidance that implies otherwise is the reason most teams waste weeks. What exists instead are four different failures that look identical from the outside and have almost nothing in common underneath: the wrong fact is on your own site, it’s on someone else’s, you’ve been confused with another company, or nothing anywhere supports it and the model produced it on its own.

The fix, the effort, and the odds are different in each case. So the first job isn’t correcting anything — it’s finding out which one you have.

Key Takeaways

• No AI engine has an “edit this answer” mechanism. Every real fix works by changing what the engine can retrieve, or by proving who you are — never by requesting a correction.
• Most wrong business facts trace to a third-party source, not your website: old press releases, unclaimed directory listings, stale aggregator profiles, and outdated job postings that engines still treat as evidence.
• Read the citations, not the answer. The sources listed under a response tell you which of the four origins you’re dealing with in about five minutes.
• OpenAI’s removal process is real but narrow: it covers personal data under privacy law, requires government-issued ID, is decided case by case against freedom of expression and public interest, and states it cannot independently investigate disputed facts.
• Bing Webmaster Tools’ AI Performance report — free, in preview since February 2026 — shows which of your URLs are cited in Copilot answers, making it the most practical way to verify a correction actually landed.

Triage First: Find Out Where the Wrong Fact Lives

Run this before touching anything. It takes a few minutes and determines everything that follows.

Ask the question that produces the bad answer, in a logged-out or temporary chat, and repeat it three or four times — answers vary between runs, and you need to know whether the error is consistent or occasional. Then work through the citations rather than the prose:

1. Does the answer cite sources? If yes, open every one.
2. Does the wrong claim appear in any cited source? If yes, you have Origin A or B — you’re looking at the actual culprit, and the rest is mechanical.
3. Is that source yours? Your site, your PDF, your old landing page, your archived subdomain — Origin A. Someone else’s — Origin B.
4. Does the answer mix in facts belonging to a different company? Wrong location, wrong founding year, wrong leadership, reviews you don’t recognise — Origin C, conflation.
5. Does the claim appear in no cited source, and nowhere you can find on the open web? Origin D.

Most teams skip straight to assuming Origin D because it’s the most alarming. In practice it’s the least common of the four, and the diagnosis matters more than the urgency.

Origin A: The Wrong Fact Is on Your Own Site

The easiest case, and more common than teams expect, because the offending page is rarely one anyone looks at.

The usual suspects: an old pricing page still reachable at its original URL, a services page describing an offering you retired, a PDF brochure from two rebrands ago, a duplicate campaign landing page nobody retired, a team page listing people who left, a subdomain or staging site that was never taken down. Engines don’t know which of your pages you consider current. They read what resolves.

Test: search your own domain for the wrong claim, including file types — site:yourdomain.com "the wrong claim" — and repeat it for any subdomain, old domain, or documents you’ve published.

Fix: correct the page rather than deleting it where possible; a corrected page at a live URL replaces the bad fact, while a deleted one leaves the claim circulating in third-party copies with nothing to contradict it. State the current fact plainly, with a date where it matters. Then make sure the page is reachable in raw HTML — a correction that only renders after JavaScript executes won’t reach the engines that don’t run it.

Timeline: days to weeks, gated by recrawl. This is the fastest correction available to you.

Origin B: Someone Else’s Page Is the Source

This is where most wrong business facts actually live, and it’s the case the vendor advice tends to skip because the work isn’t on your property.

Business information ages badly across the web and almost nothing garbage-collects it. Press releases announcing a funding round, a product, or a partnership stay live forever. Directory listings you never claimed carry a phone number from two offices ago. Aggregator profiles state a headcount and a founding year that came from a scrape in 2019. Job postings describe a tech stack you migrated off. Review platforms hold a service description you no longer offer. Each of these is a document an engine can retrieve, and retrieval doesn’t check whether the publisher is you.

Test: you already have the list — it’s the citations you opened during triage. Rank them by how often each appears across your repeated runs. The one cited every time is the one to fix first.

Fix: correct at the source, in citation-frequency order. Claim the listing. Email the publication with the current fact and a link to the page on your site that states it. Update the profiles you control on third-party platforms. Where a source won’t correct — some won’t — the goal shifts to making the accurate version more available and better corroborated than the stale one, so retrieval finds it first.

On Wikidata specifically: it has outsized downstream influence because so many systems consume it, and anyone can edit it. Be aware of the gate before you invest, though: an item is only acceptable if it links to a page on Wikipedia or a sister project, or refers to a clearly identifiable entity that can be described using serious and publicly available references, or fills a structural need. Those are Wikidata’s own notability criteria, and creating an item for a business that meets none of them wastes your time and gets reverted. If you qualify, correcting a wrong statement there is high-leverage. If you don’t, it isn’t a route.

Timeline: weeks to months. You’re waiting on someone else’s publishing schedule plus the engine’s recrawl.

Origin C: You’ve Been Confused With Another Entity

Here the facts are real — they just belong to someone else. Models resolve a name to an entity before they say anything about it, and when resolution goes wrong, everything downstream is confidently wrong.

It happens when another company shares or nearly shares your name, when you’ve rebranded or been acquired and both identities still exist in the record, when a franchise location and the corporate brand blur together, or when your name collides with a larger organisation in an unrelated industry. The signature is an answer that’s partly right: your category, someone else’s address, or your name attached to reviews you’ve never seen.

Test: ask “who is [your company] and what do they do?” several times, then “where is [your company] located?” and “who founded [your company]?” Conflation shows up fast under those three.

Fix: consistency is the whole game, and it’s tedious rather than clever.

• Make the description of what you do identical across your site, your profiles, and your listings — same category words, same locations, same scope. Variation is what leaves room for a wrong resolution.
• Add Organization schema with sameAs pointing at your official profiles, so the properties you control are explicitly connected to each other.
• Claim your knowledge panel. Google’s process is to find the panel in search results, click Claim this knowledge panel, and verify through an official profile — Search Console, YouTube, X, or Facebook. Verified representatives can then suggest changes to the entity’s information.
• If you serve customers at a location or in a service area, keep your Business Profile current and consistent with everything above.

Note the boundary with a related problem: if the issue is that no engine can tell who you are at all, that’s an entity-resolution failure covered in our diagnostic for businesses that don’t appear in ChatGPT. Here, the model is confident — it’s confidently wrong.

Timeline: weeks to months, and it accumulates rather than flipping on a date.

Origin D: Nothing Supports It — and There Is No Correction Mechanism

This is the case people fear, the one the vendor guides gloss over, and the one where honesty is worth more than reassurance.

If a claim appears in no cited source and nowhere on the open web, it was produced by the model rather than retrieved. And there is no way to edit that. You cannot submit a correction that changes what a model has internalised; the parameters aren’t a database with rows you can update. This isn’t an oversight in the product — the privacy group noyb built a formal complaint against OpenAI on precisely this point, arguing that the inability to correct inaccurate output is a structural property of how these systems work, not a missing feature.

What actually helps is indirect, and it’s the same work that wins any other AI visibility problem: make the accurate version abundant, current, and corroborated across sources engines retrieve. Modern assistants retrieve live documents before answering a large share of questions, and a well-supported retrieved fact generally beats a vague internalised one. You are not editing the model. You are giving it something better to find, repeatedly, from more than one direction.

Two honest caveats. First, this takes months, and no one can promise a date. Second, if the fabrication is intermittent — appearing in some runs and not others — that’s normal behaviour rather than evidence your work failed. Track the rate.

When It’s Not Just Wrong, But Damaging

A narrow set of cases justifies a formal channel rather than a content strategy. These instruments are genuinely narrow, and using them for ordinary inaccuracy wastes weeks you could have spent on Origins A through C. This is a description of the mechanisms that exist, not legal advice — take actual legal questions to a lawyer.

Content that is defamatory or otherwise legally actionable. Google operates a legal removal process covering content that violates law or its policies, distinct from ordinary quality feedback. It exists for material that is unlawful — not for facts you’d prefer weren’t surfaced. The cases where it’s genuinely appropriate look like an engine attributing another business’s complaints or misconduct to you.

Personal data about an individual. OpenAI operates a removal process under privacy laws including the GDPR, submitted through its Privacy Portal and covering information that is inaccurate, excessive, irrelevant, or no longer appropriate. The published criteria are worth reading before you file, because they set realistic expectations:

• It applies to personal data about individuals — not to facts about a company.
• Government-issued ID or equivalent proof is required.
• Each request is balanced against competing interests including freedom of expression and the public interest, and information tied to someone’s professional role is more likely to remain.
• OpenAI states it assesses accuracy from what you submit and cannot independently investigate disputed facts — so supply evidence, not assertions.
• Requests are not always approved, and there’s a route to complain to a supervisory authority if you disagree.

That last point is the realistic frame. This is a rights-based process with a balancing test, not a support ticket.

How to Verify the Fix Actually Landed

Checking once and seeing the right answer proves nothing — the same prompt produces different answers across runs, and you may simply have caught a good one.

Re-test as a rate. Run the same prompt at least five times, logged out, across at least two engines, and record how often the wrong fact appears. Compare that rate to your baseline from triage. The number you want is “appeared in 1 of 10 runs, down from 8 of 10,” not “I checked and it looked fine.” Our AI visibility audit walkthrough covers how many runs you need before a change is real rather than noise.

Use the one report that shows citations directly. Bing Webmaster Tools’ AI Performance report, in public preview since February 2026, shows how often your content is cited across Microsoft Copilot and Bing’s AI answers, and which URLs are referenced. In June 2026 it expanded with Intents, Topics, Citation Share, and Compare. It’s free, it covers only one engine’s ecosystem, and it’s still the most direct confirmation available that your corrected page is the one being read.

Watch the source list, not just the answer. The fix has genuinely landed when the stale source stops appearing in citations — the answer text usually follows.

The Correction Map

Origin	How you know	What actually works	Timeline
A. Your own page	Wrong claim is on a URL you control	Correct the page (don’t just delete); ensure it renders without JavaScript	Days–weeks
B. Third-party source	Wrong claim is in a cited source you don’t own	Fix at source, in citation-frequency order; claim listings	Weeks–months
C. Entity conflation	Answer mixes another company’s facts with yours	Identical descriptions everywhere, Organization + sameAs, claim the knowledge panel	Weeks–months
D. No source anywhere	Claim appears in no citation and nowhere findable	No correction mechanism — publish and corroborate the accurate version	Months, indirect
Legally actionable	Content is unlawful, not merely wrong	Google’s legal removal process; OpenAI’s privacy process for personal data	Case by case

The pattern worth taking away: the speed of a fix is set by how close the wrong fact sits to something you control. That’s also the order to work in — A, then B, then C — because each step makes the next one more likely to hold.

The Underlying Problem Is Usually Corroboration

Most persistent accuracy problems are a symptom rather than a cause. A business whose current facts are stated clearly in many independent places is difficult to get wrong; a business whose record is thin and inconsistent is easy to get wrong, and stays wrong because nothing contradicts the stale version. Fixing individual errors is necessary, but a brand that has to fix them repeatedly has a corroboration problem, not a correction problem.

That’s the same foundation that decides whether you’re recommended at all — worth reading alongside why engines recommend a competitor instead of you and the playbook for getting recommended by AI engines, and worth tracking with the same visibility metrics you’d use for any other AI-channel work.

Frequently Asked Questions

How do I correct wrong information about my business in ChatGPT?

There is no form that edits an AI’s answer, so the fix depends on where the wrong fact lives. If it appears on your own site, correct it and wait for a recrawl — days to weeks. If it comes from a third-party source the engine cites, correct it at that source. If the model has conflated you with a similarly named company, the work is entity disambiguation. And if nothing anywhere supports the claim, no correction mechanism exists — your only lever is publishing and corroborating the accurate version so retrieval finds it first.

Why does ChatGPT have wrong information about my business?

Usually because something it can read says so, and it is not always your site. Old press releases, unclaimed directory listings, outdated aggregator profiles, and stale job postings persist long after you have moved on, and an engine assembling an answer treats them as evidence. The second common cause is entity conflation, where another company shares your name and their facts get attached to you. Genuine invention with no supporting source is the least common of the three, though it is the one people assume first.

Can I report incorrect information to OpenAI and have it removed?

Only in narrow circumstances. OpenAI operates a personal data removal process through its Privacy Portal, grounded in privacy laws such as the GDPR and scoped to information about individuals rather than business facts. Requests require government-issued identification, are assessed case by case against competing interests including freedom of expression and the public interest, and OpenAI states it cannot independently investigate disputed facts. Requests are not always approved.

Why does Google’s AI Overview show another company’s information for my business?

That is entity conflation, common when a similarly named business operates in your category or region, or when your company has rebranded, been acquired, or runs both franchise and corporate locations. The model has resolved your name to the wrong entity. The fix is disambiguation: identical descriptions everywhere, Organization schema with sameAs links to your official profiles, a claimed knowledge panel, and third-party profiles consistent with all of it.

How long does it take for corrected information to appear in AI answers?

It depends on the origin. Corrections on your own pages surface over the following crawl cycles, typically days to weeks. Corrections at third-party sources take as long as that source needs, plus the engine’s recrawl — weeks to months. Entity disambiguation accumulates rather than flipping on a date. Where a claim has no source behind it, there is no timeline to promise. Verify by re-testing repeatedly over time rather than checking once.

Does adding schema markup fix wrong information in AI answers?

Schema helps with entity disambiguation but does not overwrite a claim found elsewhere. Organization markup with sameAs links helps a model resolve who you are and connect your properties, which genuinely helps when the problem is conflation. It does nothing for a wrong fact sitting in an old press release that engines keep retrieving. Structured data is a clarification layer, not a correction mechanism.

---

See what AI is actually saying about you — free. Run your site through the free AI visibility checker to see how you appear across ChatGPT, Gemini, Perplexity, and more in seconds, no credit card required. When you’re ready to track how often the right answer shows up, prompt by prompt, start a 7-day free trial.