How to Stop AI Describing Your Business Incorrectly

Last updated: 23 October 2026

Stopping AI from describing your business incorrectly means auditing what ChatGPT, Gemini, Perplexity and Copilot currently say about you, correcting the source data they pull from (Google Business Profile, your website, directories), adding structured data, and monitoring outputs regularly. 93% of companies have at least one hallucinated or missing fact in AI answers about them, according to Searchable.

Key Takeaways

• 93% of companies tested had at least one basic fact hallucinated or missing from AI chatbot answers, across 13,000+ queries on ChatGPT, Perplexity and Gemini, according to Searchable.
• Half of SMEs (50%) received a fabricated fact from an AI chatbot, compared with 32% of large companies, according to Searchable.
• AI gives out a phone number with total confidence 91% of the time, but that number only matches the business's actual Google Business Profile listing 27% of the time, according to LocalDominator.
• Content with proper schema markup is 2.5x more likely to appear in AI-generated answers, according to Stackmatix.
• Google AI Overviews appeared on 86.7% of business-intent searches in April 2026, up from 56.9% a year earlier, according to Peec AI — making correct AI descriptions commercially unavoidable.

Why AI assistants describe your business incorrectly

AI assistants like ChatGPT, Gemini and Copilot describe businesses incorrectly because large language models generate the statistically likely answer, not a verified one, often blending outdated web data, competitor information and plausible-sounding guesses into a single confident response. This behaviour is commonly called "hallucination" — when a generative AI model states something false as if it were fact.

Smaller businesses are hit hardest. SMEs received a fabricated fact from AI chatbots 50% of the time, compared with 32% of large companies (500+ employees), according to Searchable. The same research found AI models confused or misattributed SME brand names roughly five times more often than large company names (4% vs 0.7%), and described SME services accurately only 87% of the time versus 93% for large brands, according to Searchable.

The gap exists because large brands generate far more consistent, high-volume, well-structured web content — press coverage, Wikipedia entries, verified social profiles — for the model to anchor on. A business in Leeds with three directory listings, an unclaimed Google Business Profile and no schema markup gives the model almost nothing reliable to work from, so it fills gaps with inference.

AI models also confidently fabricate facts at a rate of 5% for SMEs compared with 2% for large brands, according to Searchable. That confidence is the dangerous part — the model doesn't hedge, it states a wrong opening time or a defunct service line as plain fact.

Where AI tools get their information about your business

AI tools source business information from a blend of crawled web pages, third-party data aggregators, Google's Knowledge Graph, Google Business Profile, and — for tools using retrieval-augmented generation (RAG, where a model fetches live web content before answering) — real-time search results. Your own website is only one input among many, and often not the most-weighted one.

LocalDominator's study checked 165 businesses against UK company registration records and found 93% had at least one wrong or missing fact, with small businesses hit by fabricated information at roughly 1.5 times the rate of large companies (50% vs 32%), according to LocalDominator. A major driver is phone number mismatches: AI states a phone number with total confidence 91% of the time, but that number matches the business's real Google Business Profile listing just 27% of the time, according to LocalDominator.

Common sources feeding AI models include:

• Google Business Profile — opening hours, address, phone, categories, reviews.
• Companies House — registered name, SIC code, incorporation date, registered office.
• Directory sites — Yell, Thomson Local, Checkatrade, industry-specific listings, often years out of date.
• Your own website — homepage copy, About page, schema markup, footer NAP (Name, Address, Phone) data.
• Press and PR coverage — old news articles that never get corrected once published.
• Wikipedia and Wikidata — for larger or well-known businesses.
• Social profiles — LinkedIn, Facebook, X (formerly Twitter).

Because models often cannot distinguish a live, accurate source from a stale cached one, a defunct directory listing from 2019 can outrank your current website copy in the model's internal weighting.

What is AI visibility auditing and how do I check what AI says about my business?

AI visibility auditing is the systematic process of querying multiple AI assistants with the same set of questions about your business — and recording, comparing and tracking the answers over time to spot inaccuracies, omissions and competitor confusion. This is distinct from traditional SEO rank tracking, which measures Google positions rather than conversational AI answers.

To check manually, ask each platform identical direct questions:

1. "What does [Business Name] do and where is it based?"
2. "What are [Business Name]'s opening hours and phone number?"
3. "Who are [Business Name]'s main competitors?"
4. "Is [Business Name] still trading?"

Run the same prompts on ChatGPT, Google Gemini, Perplexity, Microsoft Copilot and Claude, and screenshot every answer. Doing this manually across six engines, several prompts each, on a recurring basis quickly becomes unworkable for a business with limited marketing resource — which is why automated citation tracking exists.

Aether AI's citation tracking monitors brand mentions across six AI engines — ChatGPT, Perplexity, Google AI Overviews, Claude, Gemini and Copilot — flagging where a business is named, misnamed or omitted entirely. A free AI-visibility audit at /audit gives a baseline snapshot before you start correcting anything, which matters because Google's AI Overviews now appear on 86.7% of business-intent searches, up from 56.9% a year earlier, according to Peec AI — meaning most of your prospective customers now see an AI-generated summary before they ever reach your website.

How to correct inaccurate information on Google Business Profile and key listings

Correcting your Google Business Profile means logging into Google Business Profile Manager, verifying ownership, and directly editing the business name, address, phone number, categories, hours and services — the core fields most AI tools pull first. Google Business Profile is Google's free tool letting businesses manage how they appear across Google Search and Maps, and it remains one of the single most-weighted sources for local AI answers.

Work through listings in this order of impact:

Beyond Google, audit Bing Places (which feeds Copilot), your Companies House filing for the correct SIC code and registered office, and any industry-specific directories relevant to your sector — a security firm, for instance, should check its listing accuracy on the Security Industry Authority public register if licensed activities are involved. Inconsistent NAP data across even three or four of these sources is enough to push a model towards guessing rather than quoting your true details.

What to update on your website so AI describes your business more accurately

Your website should restate your core facts — legal name, services, locations, founding date, pricing model and contact details — in plain, unambiguous prose on your homepage and About page, because AI models retrieving live content favour clear, direct statements over marketing language. Instead of a phrase like "industry-leading solutions," state "Aether AI provides AI citation tracking across six engines" instead, in a single declarative sentence a model can lift directly.

Specific updates that make a measurable difference:

• Rewrite your About page as fact statements. Open with "[Business Name] is a [category] based in [place], providing [specific service] since [year]."
• Keep NAP data identical everywhere — same phone format, same address wording, on your website, footer, contact page and every listing.
• Publish an FAQ page answering the exact questions customers (and AI models) ask, since FAQ-structured content maps well onto how models retrieve conversational answers.
• Date-stamp key pages so models can judge freshness rather than relying on an old cached crawl.
• Correct outdated press mentions where possible by requesting updates, since old news articles are a frequent source of stale AI facts.

"Blocking GPTBot to protect your content is like delisting from Google to protect your brochure. Defensible for a paywalled publisher; self-harm for anyone who sells something. If assistants can't read you, they recommend whoever they can read." — Lauren Dawkins, Head of Content, Aether AI

That point matters directly here: if your robots.txt blocks AI crawlers such as GPTBot or Google-Extended, you remove your own corrected content from the model's available evidence, leaving only the stale directory listings and old press clippings to fill the gap.

How structured data and schema markup help AI understand your business correctly

Structured data is a standardised code format — usually JSON-LD (JavaScript Object Notation for Linked Data) — embedded in your website's HTML that explicitly labels facts like your business name, address, opening hours and services so machines don't have to infer them from prose. Schema.org is the shared vocabulary most search engines and AI systems use to read this markup.

The impact is measurable: content with proper schema markup has a 2.5x higher chance of appearing in AI-generated answers, and sites with complete Tier 1 schema see up to 40% more AI Overview appearances, according to Stackmatix. Tier 1 schema typically includes Organization, LocalBusiness, and FAQPage schema types defined on Schema.org.

Priority schema types to implement:

• Organization schema — legal name, logo, founding date, contact points.
• LocalBusiness schema — address, geo-coordinates, opening hours, price range.
• sameAs properties — linking your website to your verified Google Business Profile, LinkedIn and other profiles, which helps AI perform entity resolution (confirming which real-world business a webpage refers to).
• FAQPage schema — marking up your FAQ content so models can extract question-answer pairs directly.

Without schema, a model has to parse unstructured prose and guess at which sentence is the authoritative fact. With it, the fact is labelled unambiguously, which is why Search Engine Land's guide to structured data treats inconsistent or missing schema as a direct cause of AI models distrusting or ignoring a business's own data.

How long it takes AI tools to reflect corrected business information

AI tools reflect corrected information at different speeds depending on whether they use retrieval-augmented generation (RAG, where the model fetches current web content live) or a static training snapshot. Perplexity and Google AI Overviews, which lean heavily on live retrieval, can reflect a Google Business Profile correction within days of Google recrawling and reindexing the change. Models relying more on training data, refreshed only periodically, can take considerably longer — sometimes until the next major model update.

A realistic expectation timeline:

• Google Business Profile edits: visible in Google's own interfaces within 1–7 days of verification; AI Overviews and Gemini often follow shortly after reindexing.
• Website changes with schema: crawled within days to a few weeks depending on your site's crawl frequency; reflected in RAG-based tools faster than in training-based answers.
• Directory corrections: often 2–4 weeks per listing, sometimes longer for manual review processes.
• Training-data-only models: corrections may not appear until the provider's next training cycle, which isn't published on a fixed schedule.

This is why a single fix rarely "sticks" everywhere at once — it propagates unevenly across six different engines, which is precisely the gap ongoing citation tracking is built to catch.

Costs of fixing AI business descriptions and whether to hire a specialist

Fixing how AI describes your business costs nothing beyond staff time if you handle listings and schema yourself, but doing this manually across Google Business Profile, your website, directories and six AI engines on an ongoing basis is time-intensive and easy to let slip. The decision is less "can I afford it" and more "can I sustain it without software or outside help."

For many self-serve marketers, the sensible middle path is software that automates citation tracking across all six engines simultaneously rather than manually prompting each one weekly. Aether AI's platform provides exactly this: automated AI-optimised article generation, citation tracking, keyword and competitor tracking, and Google Search Console integration, with public pricing available at /pricing rather than a quote-only model.

Common mistakes UK businesses make correcting AI descriptions

The most frequent mistake is fixing one source — usually the website — and assuming AI tools will follow, when in practice inconsistent data elsewhere (a stale directory, an old Companies House SIC code, a mismatched phone number) keeps feeding the model conflicting facts. AI gave out a phone number with total confidence 91% of the time but matched the real listing only 27% of the time, according to LocalDominator — a gap that a website fix alone will not close if Google Business Profile still shows an old number.

Other recurring errors:

• Treating this as a one-off project rather than ongoing monitoring, when AI outputs drift as the web changes beneath them.
• Blocking AI crawlers out of misplaced caution, removing your own corrected content from the pool of evidence models can draw on.
• Ignoring schema markup entirely, leaving models to infer facts from prose rather than reading structured, unambiguous data.
• Assuming one correction fixes all six engines when each has different retrieval mechanics and update cadences.
• Not assigning clear internal ownership, so nobody actually checks AI outputs again after the initial fix.

Who should own monitoring AI descriptions: marketing, PR or legal

Day-to-day monitoring of AI descriptions sits best with marketing or digital/SEO teams, since they already own Google Business Profile, website content and schema markup — the primary levers for correction. PR should be looped in when an inaccuracy is reputationally damaging rather than merely factually wrong, and legal should be consulted only where an AI-generated claim could expose the business to regulatory or defamation risk.

A workable split:

• Marketing/SEO: owns the audit cadence, corrects website and listings, implements schema, monitors citation tracking tools.
• PR/Comms: steps in for reputationally sensitive errors (e.g. AI falsely linking the business to a scandal or a competitor's negative press).
• Legal: reviewed where AI statements could constitute defamation or breach advertising standards, particularly for regulated sectors like financial services or healthcare.

Without a named owner, AI monitoring quietly falls between departments — which is exactly how a wrong phone number or defunct service listing survives for months unnoticed.

UK legal rights if an AI tool gives false or damaging business information

UK businesses have limited but real legal avenues where an AI tool publishes false, damaging information: defamation law (the Defamation Act 2013 in England and Wales), which requires proving "serious harm" to reputation, and data protection complaints to the Information Commissioner's Office (ICO) where inaccurate personal data about individuals within the business is involved. There is currently no dedicated UK statute governing AI-generated business misinformation specifically.

Practical realistic steps, in order:

1. Use each platform's own feedback mechanism first — ChatGPT's thumbs-down/report function, Google's "send feedback" on AI Overviews, and similar tools on Gemini and Copilot.
2. Request corrections at source — Google Business Profile, Companies House, directories — since AI providers generally cannot "edit" a fact directly but will reflect a corrected underlying source over time.
3. Document the harm with dated screenshots if you believe the inaccuracy is causing measurable commercial damage.
4. Take defamation advice only where the statement is false, published to a third party, and causes or is likely to cause serious reputational harm, as defined under the Defamation Act 2013.
5. Contact the ICO where the issue concerns inaccurate personal data rather than general business facts, under UK GDPR's accuracy principle.

For most ordinary factual errors — wrong hours, wrong address, outdated service list — correction at source remains far faster and more effective than any legal route.

Your AI business description correction checklist

• Run identical prompts about your business across ChatGPT, Gemini, Perplexity, Copilot and Claude, and record every answer.
• Verify and correct your Google Business Profile name, address, phone number, hours and categories.
• Align NAP data exactly across your website, footer, listings and directories.
• Rewrite your homepage and About page as clear, factual, declarative statements.
• Implement Organization, LocalBusiness and FAQPage schema markup using JSON-LD.
• Confirm your robots.txt does not block GPTBot, Google-Extended or other AI crawlers.
• Correct your Companies House SIC code and registered details if outdated.
• Set a recurring monthly or quarterly audit to re-check all six engines.

FAQ

Why does ChatGPT describe my business incorrectly?

ChatGPT generates the statistically likely answer rather than a verified one, often blending outdated directory data, old press mentions or competitor information when your own authoritative facts aren't clearly available or structured. SMEs are hit especially hard, with 50% receiving at least one fabricated fact, according to Searchable.

How do I find out what AI is saying about my business right now?

Ask each AI platform — ChatGPT, Gemini, Perplexity, Copilot, Claude — the same direct questions about your opening hours, services and location, and record the answers. Automated citation tracking tools, including Aether AI's free audit at /audit, can run this across six engines simultaneously rather than manually.

Can I directly edit what an AI chatbot says about my company?

No, you cannot edit an AI model's output directly, but you can correct the underlying sources it draws from — Google Business Profile, your website, Companies House and directories — and most platforms let you submit feedback flagging a specific answer as wrong. Corrections at source are the only reliable long-term fix.

How does schema markup help prevent AI misinformation about a business?

Schema markup labels facts like your name, address and hours in a standardised machine-readable format, so AI models can extract them directly rather than inferring them from prose. Content with proper schema is 2.5x more likely to appear in AI-generated answers, according to Stackmatix.

How long does it take for AI tools to update after I correct information?

It varies by platform: tools using live retrieval, like Perplexity, can reflect a Google Business Profile correction within days of Google reindexing it, while models relying on static training data may not update until their next training cycle. Directory corrections typically take two to four weeks to filter through.

Why does AI confuse my business with a competitor with a similar name?

AI models struggle with entity resolution — correctly identifying which real-world business a name refers to — especially when multiple companies share similar names and neither has strong, consistent structured data. SME brand names were confused roughly five times more often than large company names (4% vs 0.7%), according to Searchable.

What should I do if a third-party website has outdated information that AI is citing?

Contact the site owner directly and request an update or removal, since AI models cannot distinguish a stale third-party page from a current one unless the underlying content actually changes. If the site won't cooperate, strengthen your own primary sources — Google Business Profile, your website, schema — so they outweigh the stale listing over time.

Stopping AI misdescriptions with Aether AI

This entire problem — AI models confidently stating wrong phone numbers, outdated services or confused brand identities — is exactly what Aether AI's citation tracking is built to catch before it compounds. Rather than manually prompting six different AI engines on a spreadsheet, Aether AI tracks brand mentions across ChatGPT, Perplexity, Google AI Overviews, Claude, Gemini and Copilot continuously, flagging where your business is named, misnamed or missing entirely.

Aether AI's own measured baseline — 700 live AI engine scans of UK brands' target keywords between July and August 2026 — found those brands named in just 23 answers, or 3.3% of scans, with the longest-established brand appearing in 6.3% of its 270 scans. That baseline is the same starting point most UK businesses are working from before they begin correcting sources and monitoring outputs.

If you want to see exactly what AI currently says about your business before fixing anything, start with the free AI-visibility audit at /audit, or review public pricing at /pricing to see how ongoing monitoring fits into your marketing workflow.

Related Reading

• How to Get Cited by Perplexity: A UK Business Guide 2026
• How to Get ChatGPT to Recommend Your Product (2026)
• How to Get Mentioned in Claude Answers (2026)