How to find and fix what AI gets wrong about your brand

From my experience of working in SEO, one thing I've learned is that AI tools can sometimes show outdated or incorrect information about a brand. The first thing I do is ask different AI tools questions about the company, its services, pricing, locations, or products to identify what information is wrong or missing.

Once I find the issues, I update the website with clear, accurate, and well-structured content. I also make sure the same information is consistent across the Google Business Profile, social media pages, business directories, and other trusted websites. If there are outdated articles or incorrect third-party listings, I try to get them updated as well.

I've noticed that AI tools rely on trusted and consistent sources. So, the more accurate and up-to-date your online presence is, the better the chances that AI will provide the correct information about your brand. This isn't a one-time task either; it's something you should check regularly as your business grows and changes.

Yes, I have gone through this exact process for several client websites, and finding what AI gets wrong about a brand is honestly more common than most business owners expect.

The first thing I do is run the brand name through ChatGPT, Gemini, and Perplexity with a few different prompts. Not just the business name alone, but questions like "what services does X offer" or "where is X located" or "who runs X." The variation in how you phrase the question often surfaces different inaccuracies. Sometimes the description is outdated, sometimes a service is missing entirely, and occasionally the AI confidently states something that was never true in the first place.

On the content side, the most effective fix I have found is making sure the website itself states things clearly and unambiguously. AI models pull from what is publicly available, and if your About page is vague or your service descriptions are thin, there is nothing solid for the model to work with. Rewriting key pages so they directly and factually state what the business does, where it operates, who leads it, and what makes it different gives the model cleaner material to reference.

For structured data, adding or cleaning up Organisation schema on the website helps significantly. Including the business name, address, contact details, founding date, social profiles, and a clear description in your schema markup creates a reliable machine-readable record that AI systems and search engines can reference with more confidence.

Google Business Profile and other listings matter more than people realise in this context. Keeping these accurate and consistent across platforms strengthens what SEO people call entity signals, which is essentially how confidently an AI or search engine can identify and describe your brand based on corroborating information across multiple sources.

Publishing authoritative content about the brand also helps over time. Press mentions, interviews, guest articles, and third-party references that accurately describe the business contribute to how AI models form their understanding of it. A brand that only exists on its own website is easier to misrepresent than one that appears consistently and accurately across several credible sources.

One thing worth knowing is that you cannot directly submit corrections to most AI platforms the way you can with Google's Knowledge Panel. Perplexity does index the web in real time so it tends to update faster when your source content changes. ChatGPT and Gemini work from training data with cutoff dates, so corrections take longer to filter through and in some cases may not update until the next model training cycle.

The most practical approach I recommend is treating your own website as the primary source of truth, keeping it factually detailed and well-structured, building consistent listings across authoritative directories, and monitoring what AI platforms say about the brand periodically. It is not a one-time fix but an ongoing part of how digital presence management works now.

As an SEO analyst working in Dubai for over three years, I have noticed that AI-generated answers can sometimes present outdated or inaccurate information about businesses, especially when a brand has evolved significantly over time. One of the most memorable cases I handled involved a Dubai-based education consultancy. When we checked how various AI platforms described the company, we found that several tools were still referencing old service offerings, outdated branch information, and even mentioning partnerships that no longer existed. This created confusion for prospective customers who were relying on AI-powered search tools to research the business before making contact.

To solve the issue, we approached it systematically. First, we audited what major AI platforms were saying about the brand. We tested multiple prompts across ChatGPT, Gemini, Perplexity, and Google's AI search features to identify recurring inaccuracies. Once we documented the issues, we focused on strengthening the company's authoritative digital footprint.

The first step was updating all core website content. We refreshed service pages, company descriptions, leadership information, FAQs, contact details, and location pages. We also created dedicated pages that clearly explained the company's current services and expertise. AI systems often rely on publicly available information, so the website needed to become the most accurate source of truth.

The second step involved improving structured data. We implemented Organization, Local Business, FAQ, and Person schema wherever applicable. This helped search engines and AI systems better understand the company's services, locations, founders, and areas of expertise.

The third step was consistency across external platforms. Many AI inaccuracies originate from conflicting information found across the web. We updated Google Business Profiles, business directories, social media accounts, industry listings, and partner websites to match the information on the company's website.

At our digital marketing agency in Dubai, my teammates have encountered similar issues across different industries. For example, a healthcare client was repeatedly associated with treatments they no longer offered. In another case, a real estate company was being described as operating only in a limited geographic area despite expanding significantly. We addressed both situations by publishing authoritative content that directly answered common questions about the business, services, locations, and expertise.

One technique that has worked particularly well is creating detailed knowledge hub content. Instead of assuming AI systems will infer information correctly, we publish clear articles covering company history, services, leadership, locations, certifications, and frequently asked questions. This gives AI models more reliable information to reference.

I also recommend actively building entity signals. This includes earning mentions from reputable publications, obtaining citations from trusted industry sources, participating in interviews, publishing thought leadership content, and maintaining strong social media activity. The stronger the brand entity becomes, the easier it is for AI systems to associate accurate information with the business.

My step-by-step process is simple:

1. Audit what AI platforms currently say about the brand.

2. Document every inaccuracy.

3. Update website content thoroughly.

4. Implement structured data.

5. Standardize information across all external platforms.

6. Publish authoritative resources and FAQs.

7. Strengthen brand mentions and entity signals.

8. Recheck AI platforms regularly and monitor improvements.

In my experience, fixing AI misinformation is not about trying to influence AI directly. It is about creating a consistent, authoritative, and highly visible digital presence that gives AI systems accurate information to learn from. Businesses that actively manage their online entity signals are far more likely to be represented correctly in AI-generated search experiences.

What stands out to me about this whole conversation is the timing of it. By the time someone reaches your website, they have probably already formed an opinion based on what an AI tool just told them. If that information is wrong, the damage is already done before you even get a chance to correct it yourself.

This feels different from how reputation management used to work. Before, if your website had the right information, that was usually enough. Now there is a layer in between, the AI tool, and it is summarizing and deciding what to tell the customer before they ever land on your page. If it gets the address wrong, mentions a service you no longer offer, or pulls outdated pricing, the customer is already walking in with the wrong expectation or worse, they just move on to a competitor without ever realizing the information was inaccurate.

To actually find these gaps, I think the simplest approach is to ask AI tools the same questions a real customer would. What does this business do, where are they located, what do people say about them. Doing this across ChatGPT, Gemini, and Perplexity usually surfaces different answers since they pull from different sources, and that difference itself tells you where the weak points are.

Fixing it comes down to cleaning up the source rather than trying to argue with the AI directly. That means making sure your website, Google Business Profile, and any directory listings all say the same thing, and that outdated mentions on third party sites get corrected wherever possible.

What makes this trickier is that AI tools can still get things wrong even when everything on your end is accurate. Sometimes it is outdated training data, sometimes it is pulling from an old directory listing or an unreliable third party source you have no control over. So this is not always a case of the business doing something wrong, it is sometimes just a limitation of how these tools generate answers in the first place.

That is why I do not think this is a one time fix. Businesses need to check this regularly rather than assuming that fixing it once means it stays fixed. If that first impression is wrong, you are already starting from a deficit, and most customers will not stick around long enough to find out the truth.

Yes, I've actually run this check for a few of my clients, and you'd be surprised how often AI tools get basic brand details wrong, especially smaller and mid-sized businesses that don't have a strong digital footprint.

Common issues I've seen are outdated addresses, wrong phone numbers, old leadership names, services the company no longer offers, or even mixing up two similarly named businesses. ChatGPT and Gemini tend to pull from older training data, while Perplexity and Google AI Overviews lean more on live web sources, so the errors are usually different depending on the platform.

Here's what's actually worked for fixing this:

Strengthen your Google Business Profile and structured data first. AI search tools heavily rely on schema markup, so adding Organization schema, LocalBusiness schema, and proper sameAs links (linking your social profiles, Wikipedia, Crunchbase, etc.) to your homepage makes a real difference in how accurately you're represented.

Update your "About Us" and key pages regularly. If your leadership team, services, or contact info changed, don't just update it once, make sure it's consistent across your website, Google Business Profile, LinkedIn, and any directory listings. AI tools cross-reference multiple sources, so inconsistency is what causes confusion.

Publish authoritative content that directly answers common questions about your brand. Things like an FAQ page, a detailed "What we do" page, or press mentions help reinforce correct information across the web, which AI models eventually pick up on, especially tools like Perplexity that crawl live.

Get listed correctly on third-party sources. Wikipedia, Crunchbase, industry directories, and news articles carry a lot of weight for AI training data. If your brand has any outdated mentions there, reaching out to get them corrected helps more than you'd think.

Build digital PR and backlinks from credible sources. This is something people overlook, but the more reputable sites mention your brand correctly, the more "votes of confidence" AI models get when generating answers about you.

One challenge I've personally faced is that even after fixing everything, older LLMs like ChatGPT don't always update in real time since they rely on training snapshots. Perplexity and Google AI tools usually reflect the changes faster since they pull from live search results.

So the real strategy is treating this like ongoing entity SEO, keeping your information consistent everywhere, reinforcing it with authoritative sources, and being patient since some platforms take longer to "catch up" than others.

From what I have seen, many businesses do not realise that AI tools can sometimes say the wrong things about their brand until a customer points it out. I think the first step is accepting that AI does not always pull information from one official source. It learns from websites, directories, reviews, articles, social platforms, old pages, and sometimes outdated or incorrect content. Because of this, businesses can end up with wrong service details, outdated contact information, incorrect company descriptions, or even confusion with another brand.

The way I usually approach this is by acting like a customer. I search for my business name in tools like ChatGPT, Google AI Overviews, Gemini, Perplexity, and voice assistants to see what information appears. I ask simple questions that customers might ask, such as “What services does this company offer?”, “Where is it located?”, “What are people saying about them?”, or “Who are their competitors?” This helps me quickly spot misinformation, missing details, or weak brand positioning.

Once I identify what AI is getting wrong, I focus on fixing the source of the problem rather than trying to fight the AI directly. In my experience, AI usually reflects what already exists online. So if old business information is still sitting on outdated directories, if the website messaging is unclear, or if there are conflicting descriptions across platforms, AI will often repeat those mistakes. I start by cleaning up business listings, updating website content, improving About pages, clarifying service descriptions, and making sure contact details are consistent everywhere online.

I have also found that publishing stronger brand content helps a lot. If your website clearly explains who you are, what you do, who you help, and where you operate, AI tools have better information to reference. Case studies, FAQs, founder pages, service explanations, media mentions, and customer reviews can all help shape how AI understands your business. I also try to make content specific rather than vague because AI tends to understand clear information better.

Another thing I pay attention to is third party mentions. If trusted websites, industry publications, review platforms, or local directories describe the brand accurately, AI is more likely to reflect the right information. On the other hand, poor or outdated mentions can continue feeding confusion.

I do not see this as a one time task anymore. I treat it more like reputation management. Every few weeks or months, I check what AI tools are saying about the brand again, especially after major business changes, new services, rebranding, or location updates. Small corrections made consistently can make a surprisingly big difference in how your business is represented online.