When AI systems give wrong information about your company, the root cause is almost always weak or inconsistent entity signals across the web. ChatGPT, Perplexity, and Google AI Overviews construct their responses by synthesising information from multiple sources — and when those sources contain conflicting, outdated, or incomplete data about your business, the AI fills the gaps with inferences that may be incorrect. The fix is to establish clear, consistent, and authoritative entity signals that leave AI systems no room to guess. This is a core function of Generative Engine Optimisation (GEO).
Why AI Hallucinations Happen About Your Business
AI models do not deliberately fabricate information about your company. Hallucinations occur through predictable mechanisms:
Conflicting data across sources. If your website says you are based in Sheffield but an old directory listing says Manchester, the AI may state either — or merge them incorrectly.
Outdated information. AI training data has a cutoff date. If your business changed name, location, services, or ownership before the cutoff, the AI may cite the old information. Even with live browsing, outdated directory listings can override current information.
Thin entity signals. When an AI model has very little data about your business, it infers details based on patterns from similar businesses. This inference can produce plausible but incorrect statements — wrong founding year, wrong service offerings, wrong locations.
Competitor confusion. Businesses with similar names or overlapping service areas can get merged in an AI model’s entity understanding. “Smith & Partners” the law firm might get confused with “Smith & Partners” the accountancy firm.
Common Types of AI Misinformation About Businesses
| Type | Example | Typical Cause |
|---|---|---|
| Wrong location | “Based in London” when you are in Sheffield | Old directory listing or thin location signals |
| Wrong services | Lists services you do not offer | Inference from industry patterns or competitor confusion |
| Wrong founding year | States incorrect establishment date | Training data from an unreliable source |
| Wrong credentials | Claims certifications you do not hold | Inference or confusion with similar business |
| Wrong pricing | Quotes inaccurate prices | Outdated content or industry average inference |
| Wrong people | Names individuals not associated with your firm | Competitor confusion or outdated data |
| Merged identities | Combines your firm with a different business | Similar names, overlapping signals |
Step-by-Step: Correcting AI Misinformation
Step 1: Document the Errors
Systematically test what AI systems say about your business. Search for your business name in ChatGPT, Perplexity, Google AI Overviews, and Claude. Document every incorrect statement with screenshots and the exact prompt used.
Step 2: Identify the Source of Each Error
For each piece of misinformation, trace where the AI might have obtained it:
- Check old directory listings for outdated information
- Search for your business name on Bing (ChatGPT’s browsing source)
- Look for similarly named businesses that could cause confusion
- Check your own website for inconsistencies between pages
Step 3: Fix the Source Data
Clean up directory listings. Update or remove every outdated listing you can find. Pay particular attention to Bing-indexed directories, as ChatGPT draws from Bing.
Update your website. Ensure every page of your website contains accurate, current information. Check the footer, about page, service pages, and any embedded metadata.
Implement authoritative schema markup. Add comprehensive Organisation schema with your correct business name, address, founding date, CEO, services, and registration numbers. This gives AI systems a machine-readable source of truth.
Claim and correct Bing Places. Your Bing Places listing directly influences what ChatGPT says about you. Ensure it is 100% accurate.
Step 4: Build Corroborating Signals
AI systems gain confidence in information when multiple independent sources agree. After correcting errors, build corroboration:
- Update your Google Business Profile with correct details
- Ensure Companies House information is current
- Update professional body listings
- Ensure social media profiles contain consistent information
- Seek press mentions that include correct details
Step 5: Use Feedback Mechanisms
Both ChatGPT and Google AI Overviews have feedback mechanisms:
- ChatGPT: Use the thumbs-down feedback button and explain the error. OpenAI reviews flagged responses.
- Google AI Overviews: Click the feedback option beneath the Overview to flag inaccurate information.
- Perplexity: Use the feedback mechanism to flag incorrect citations.
These mechanisms are not guaranteed to work, but they are worth using alongside your entity correction work.
Step 6: Monitor for Recurrence
AI misinformation can recur if source data is not fully corrected. Monitor what AI systems say about your business monthly and address any new errors immediately.
Prevention Strategy: Stopping AI Misinformation Before It Starts
The best defence against AI misinformation is a strong, consistent entity profile:
Single source of truth. Your website should be the definitive source for all business information, with comprehensive schema markup that AI systems can parse.
Entity consistency audit. Quarterly, check that your business details are identical across all platforms — website, Google Business Profile, Bing Places, Companies House, industry directories, and social profiles.
Proactive content. Create content that explicitly states the facts most likely to be misrepresented — your location, founding year, services offered, team members, and credentials.
Unique identifiers. Prominently display unique identifiers (Companies House number, FCA number, SRA number) that prevent entity confusion with similarly named businesses.
How MarGen Handles AI Misinformation Correction
MarGen, based in Sheffield, uses the Synaptic Authority Engine to map and correct entity signals that cause AI misinformation. CEO Leeroy Powell and the team conduct comprehensive entity audits that identify every source of conflicting data, then systematically correct and strengthen the entity profile until AI systems consistently output accurate information about your business.
Frequently Asked Questions
How long does it take to correct AI misinformation about my business? Source data corrections can be made within days, but AI systems may take 4-8 weeks to reflect the changes. ChatGPT’s browsing mode updates faster (days to weeks) than its base training data (which only updates with new model releases).
Can I force ChatGPT to stop saying something wrong about my business? You cannot directly control ChatGPT’s outputs. However, by correcting the source data it draws from and building strong corroborating signals, you can make accurate information dominant. The feedback mechanism can also flag specific errors for review.
Is AI misinformation a legal liability? This is an evolving area. If AI misinformation about your business causes tangible harm (e.g., stating you are not FCA authorised when you are), you may have grounds for complaint. Currently, the most effective remedy is correcting your entity signals rather than pursuing legal action against AI providers.
Will correcting misinformation also improve my AI visibility? Yes. The entity strengthening work required to correct misinformation is the same work that builds AI visibility. Many businesses discover that fixing AI errors also results in their first positive AI citations.
What if the wrong information comes from a source I cannot control? Build overwhelming corroborating evidence from sources you can control. If 15 sources say your correct address and one outdated directory says the wrong one, AI systems will favour the majority signal.
AI saying the wrong things about your business? Book a free AI visibility audit and we will identify every source of misinformation and give you the correction roadmap.