How to make sure AI gives correct information about your business

What does it mean for AI to describe your business correctly?

An AI assistant describes your business correctly when tools like ChatGPT, Gemini, Google AI Overviews, Google AI Mode, Perplexity and Microsoft Copilot state your name, location, products, prices, people and contact details the way your own records do. Being described correctly differs from being recommended: an engine can name your company in a list of options and still give it the wrong opening hours, a competitor’s feature or a namesake’s support email. Accuracy matters because a buyer who asks an assistant may read its answer before ever visiting your website, so a wrong fact can cost a sale you never hear about. For the recommendation side, see how AI chooses which brands to recommend.

Why does AI get facts about your business wrong?

AI assistants get facts about a business wrong because they generate answers from patterns across many sources rather than looking up one official record. When those sources disagree, are years old or say very little, the model fills the gap with something plausible. Prices, hours, team members and product lines change often, while old blog posts, directory entries and comparison pages keep the previous version alive.

The most common causes:

• Stale third-party pages still show your previous address, name or pricing.
• Conflicting sources lead the engine to pick one version or blend them.
• Thin information invites invention: if nobody has published your founding year, the model may make one up.
• Similar names get two companies merged into one.
• Model memory keeps facts learned in training after you change them. OpenAI’s own guidance says ChatGPT answers may not reflect the most current information or may contain inaccuracies.

Errors are common well beyond brand questions. In a European Broadcasting Union study, journalists reviewed more than 3,000 news answers from ChatGPT, Copilot, Gemini and Perplexity: almost half had at least one significant issue. When Columbia Journalism Review’s Tow Center tested eight AI search tools on identifying news sources, they answered more than 60 percent of queries incorrectly.

What kinds of wrong information does AI give about businesses?

AI makes seven common kinds of errors about businesses, and each usually has a different source and fix.

How do you make sure AI gives correct information about your business?

You make sure AI gives correct information about your business by running a repeatable loop: check what the engines say, trace each wrong claim to its source, fix your own site, make your company easy to identify, correct third-party profiles, report wrong answers, and re-test on the same questions. The eight steps below follow that order, because fixing sources does more than clicking feedback buttons.

Step 1: Ask the engines a fixed set of customer questions

Checking what AI says about your business starts with asking ChatGPT, Gemini, Google AI Overviews and AI Mode, Perplexity and Copilot what a buyer would ask. Keep 10 to 20 questions fixed so results stay comparable:

• “What does [company] do, and who is it for?”
• “How much does [company] cost?”
• “Where is [company] and when is it open?”
• “[company] vs [competitor]: which is better for [use case]?”
• “What do customers say about [company]?”

Run each question several times. In SparkToro’s research, 600 volunteers ran 12 prompts 2,961 times across three AI tools, and the chance that ChatGPT or Google’s AI returned the same brand list in any two of 100 responses was under 1 in 100.

Log every wrong claim with the engine, date, exact wording, tone (positive, neutral or negative), correct fact and cited sources. For a ChatGPT walkthrough, see how to check what ChatGPT says about your brand.

Step 2: Trace where each wrong claim came from

You trace where AI got incorrect information about your brand by opening the sources the answer cites and finding the page with the wrong claim. Perplexity, Google AI Overviews and AI Mode show source links with the answer; ChatGPT shows them when it searches the web.

Test with and without web search. A wrong claim with a cited page is a retrieval error, and fixing that page is the main lever. A wrong claim with no source that repeats across runs most likely comes from model memory, which changes more slowly.

Check old directory listings for outdated information. Old directories, citation sites and map listings often still carry a previous address, phone number or company name. Search your old details in quotes, then update or remove every listing you find.

Step 3: Turn your website into the reference for your own facts

Your website should state every fact a customer might ask about in plain text that crawlers can read without running scripts. Update pages in this order:

1. Homepage: one sentence on what you do, for whom and where.
2. About page: legal name, founding year, leadership, locations, and a “not to be confused with” line if you share a name.
3. Product, service and pricing pages: current offers only; redirect discontinued ones.
4. Contact page: one phone number, one support email, one address.
5. FAQ page: short answers to the exact questions engines get wrong.

Allow OpenAI’s search crawler. OpenAI’s crawler documentation says sites opted out of OAI-SearchBot “will not be shown in ChatGPT search answers.”

Step 4: Give engines one clear entity identity

Entity identity is the set of signals that lets an engine recognise your business as one specific company: the same name, address and phone number across directories, links between your official profiles, and one consistent description. When those signals disagree, engines blend you with namesakes or with older versions of yourself.

Pick one canonical version of each fact and use it on your site, Google Business Profile, Bing Places, LinkedIn, Crunchbase and industry directories. Add identifiers such as registration numbers and your legal name if another company shares your name. For more depth, see brand entity optimization for AI.

Step 5: Add Organization or LocalBusiness schema markup

Schema markup lets machines read your identity, location and core details without parsing prose. Google says organization structured data on your home page can help it understand your administrative details and disambiguate your organization; useful properties include legalName, foundingDate, address and iso6523Code for identifiers such as DUNS or LEI.

Use LocalBusiness for physical locations. LocalBusiness structured data can describe opening hours and departments.

Link profiles with sameAs. Schema.org defines sameAs as a reference page that unambiguously indicates the item’s identity, such as a Wikidata entry. Google also asks that structured data matches the visible text on the page. Implementation details are in our schema markup guide.

Step 6: Correct the third-party sources engines read

Third-party sources can outweigh your own site, because engines treat independent pages as evidence and a claim repeated on many sites can beat one official page.

• Google Business Profile: Google lets you edit a verified profile and reviews changes before they go live.
• Bing Places, LinkedIn and Crunchbase: update descriptions, leadership, locations and links.
• Wikidata: add or correct an item only if your company meets the notability criteria, for example by being describable with serious, publicly available references.
• Articles and comparison pages: email the publisher the wrong sentence, the correct fact and a link that proves it.
• New coverage: earn accurate mentions in publications and lists in your category, so current sources outnumber stale ones.
• Forums: a factual reply from a named company account can correct a thread. See how Reddit and Quora feed AI citations.

Treat reviews as customer evidence. Reviews show engines what customers experienced, in their own words. Ask customers to name the service they used, and answer wrong claims in reviews with the correct fact.

Step 7: Report the wrong answer inside each engine

Reporting a wrong AI answer sends a signal to the engine’s team, but it does not rewrite the answer for everyone, so do it after fixing the source.

• Google AI Overviews: click thumbs-down, then Report a problem and pick a category.
• ChatGPT: OpenAI says to use the thumbs-down button or the report flow to flag incorrect replies.
• AI Mode, Gemini, Perplexity and Copilot: use the feedback option shown with the answer, and include the correct fact and a link to your source page.

Step 8: Re-test on the same questions and keep a log

Prompt-based auditing means re-running the same question set on the same engines and comparing each answer with your log. Re-test monthly, after every fix and after major model releases, and record per engine whether each wrong claim is gone, changed or still there, and which source is now cited.

Is there a way to influence what AI says about your company?

Yes, you can influence what AI says about your company, but only indirectly, by changing the sources the engines read. Google states there are no additional requirements or special optimizations needed to appear in AI Overviews or AI Mode, and its checklist includes keeping Business Profile information up to date. The same logic applies to ChatGPT, Gemini, Perplexity and Copilot: you improve what AI says about your brand by improving what the web says about it.

You can influence your own pages, schema markup, business profiles, directory listings and corrections from publishers. You cannot directly control facts already in a model’s memory, pages other people own, or run-to-run variation in answers.

How long does it take for AI to correct wrong information?

No AI company publishes a timeline for correcting facts about a business, so be wary of anyone quoting a fixed number of weeks. Retrieval-based answers, the ones that cite web pages, can change once the source is fixed and re-crawled. Memory-based answers, with no source and the same error on every run, change when the model is updated, which you do not control. OpenAI’s only stated timing is narrow: it can take about 24 hours from a robots.txt update for its systems to adjust, per its crawler documentation.

What mistakes stop the fix from working?

Corrections usually fail because the wrong source stays online or the business checks only once.

• Fixing only your website while ten directories still show the old address.
• Relying on thumbs-down and leaving the wrong source online.
• Checking once, when answers vary between runs.
• Adding schema that contradicts the page text.
• Creating duplicate profiles, which adds another conflicting source.
• Ignoring support tickets. When customers quote a wrong AI answer, add the correct fact to your FAQ and support replies.

Checklist: correct what AI says about your business

• Run 10 to 20 fixed questions on each engine, several times
• Log wrong claims with engine, date, wording and sources
• Test with and without web search
• Find and fix old directory listings
• Update homepage, About, product, contact and FAQ pages
• Allow OAI-SearchBot in robots.txt
• Add Organization or LocalBusiness schema with sameAs
• Update Google Business Profile, Bing Places, LinkedIn, Crunchbase
• Ask publishers for corrections
• Report wrong answers in each engine
• Re-test monthly