Why AI Shows Wrong Information About Your Business

A customer calls your office at 6:30 in the evening. They had asked ChatGPT for a business near them that handled exactly what you do, got your name back as a recommendation, and showed up expecting you to be open. Your actual closing time: 6pm. ChatGPT told them 8pm.

That is not a hypothetical. According to a 2026 study covering more than 13,000 queries across major AI platforms, 93% of businesses had at least one basic fact wrong in AI answers about them, whether hours, address, services, or phone number. Business profile accuracy on ChatGPT and Perplexity averages only 68%. In local business answers, AI serves incorrect location data, hours, or service details in nearly half of all responses.

The frustrating part is not that AI gets things wrong. The frustrating part is that the wrong information is being delivered with the same confident tone as correct information, to hundreds of people asking about your business every month, with no correction mechanism and no way for you to intercept it.

The Probabilistic Problem: How AI Decides What Is True

Most business owners assume AI works like a lookup table. You have a website, the website says your hours are 9am to 7pm, and AI reads that and reports it correctly. That is not how it works.

AI language models, including ChatGPT, are trained on massive collections of text gathered from across the internet. When that training happened, the model absorbed patterns from your website, yes, but also from Yelp, from the Chamber of Commerce directory, from an old Yellow Pages listing, from a news article that mentioned you three years ago, and from dozens of other sources. All of those sources are weighted by how many times that information appeared across the training data.

The result is probabilistic: AI does not know what is true about your business. It knows what appears most frequently and consistently. If your old phone number from 2022 appears on fourteen directories and your current number only appears on your website and Google Business Profile, the old number may have a higher confidence score in the model's representation of your business.

This is why updating your website alone rarely fixes AI inaccuracies. The web has a long memory. Old information persists in indexes, caches, archived pages, and directories that never update. AI weighs all of those signals together. Your single updated website is one vote against dozens of old ones.

5 Reasons AI Gets Your Business Information Wrong

When we audit businesses that appear with incorrect information in AI answers, the same causes appear repeatedly. Understanding them helps clarify why the problem is harder to fix than it looks, and why the fix requires more than a simple website update.

1. Conflicting Sources Across the Web

The most common cause of AI inaccuracies is a web ecosystem where your business information is spread across dozens of sources that disagree with each other. Your Yelp page says Suite 200. Your Google Business Profile says Suite 201. Your website says 201B. A local directory says no suite number at all. AI sees four versions and synthesizes a fifth, which may match none of them.

This is not a minor formatting problem. Conflicting signals create genuine ambiguity in how AI encodes your business entity. When ambiguity exists, AI either picks the most-seen version or produces a blend, both of which may be wrong. Read more on this in our breakdown of which directory listings actually help AI find your business.

2. Outdated Training Data

ChatGPT's knowledge base has a training cutoff: September 2024. Any change you made to your business after that date, a new address, new hours, a new phone number, a rebranded name, does not exist in ChatGPT's foundational knowledge unless it crawls the live web in response mode. When ChatGPT is answering a question from its base training rather than from live search, it is working from a snapshot of your business as it existed before your changes.

For businesses that have moved, changed hours, or expanded their services in the last two years, this is a significant problem. Customers are getting information about a version of your business that no longer exists.

3. Unlabeled or Missing Schema Data

Schema markup is machine-readable code that tells AI crawlers exactly what a piece of content means. When your website includes LocalBusiness schema with your current hours, address, and services, AI can parse that information with high confidence and weight it accordingly. When you have no schema, or outdated schema that contradicts your visible content, AI has to interpret your website through context clues, which introduces errors.

Businesses with properly implemented LocalBusiness schema get their information corrected faster after updates because AI crawlers can pull the authoritative signal directly. See how schema affects AI citation accuracy in our article on whether schema markup helps AI search.

4. NAP Inconsistency Across Directories

NAP stands for Name, Address, Phone. NAP consistency means that every listing, profile, and citation of your business across the web uses the exact same version of those three data points. Not "similar." Identical. Even small variations, "St." vs "Street," "LLC" included or omitted, a suite number formatted differently, signal to AI that it may be looking at two different entities.

Across 50+ directories that aggregators push your business to, even small inconsistencies multiply. AI models trained on this data absorb the inconsistency as uncertainty about your entity. That uncertainty surfaces as wrong information in responses, because the model is averaging across conflicting signals instead of reporting a single clear truth.

5. No Direct Feedback Mechanism

Perhaps the most structurally frustrating cause: there is no correction hotline for AI. You cannot call ChatGPT and say your hours are wrong. You cannot flag an error in Perplexity and have it propagate to the model. You cannot submit a correction form to Google AI Overviews. The only way to correct AI information is to change the underlying signals AI trusts, which is a much more involved process than editing a webpage.

The Training Data Cutoff Problem: ChatGPT vs. Perplexity vs. Google AI

Not all AI platforms handle business information the same way, and understanding the differences helps explain why you might see accurate information on one platform and stale information on another.

ChatGPT's core model carries a training cutoff of September 2024. When ChatGPT answers a question without conducting a live web search, it is drawing on what was true about your business as of that date. For many businesses, that is a very different version of their operation than what exists today.

However, ChatGPT now includes a "search" mode that retrieves live web pages to supplement the base model. When it uses that mode, the accuracy of the answer depends heavily on which pages rank well enough to get retrieved, and whether those pages carry current, structured information.

Perplexity is architected differently. It uses real-time web search as its primary method, meaning it is pulling live content from indexed pages rather than relying on a static training corpus. This makes Perplexity more likely to reflect recent changes to your business, but it is still constrained by what pages rank for the query and whether those pages contain current, structured information.

Google AI Overviews occupy a middle ground. Google has its own index, which it maintains with high freshness, but the AI overlay layer uses that index in combination with its own language model to generate composite answers. Changes to your Google Business Profile can propagate into Google AI responses relatively quickly, making GBP one of the highest-leverage signals you can maintain for AI accuracy.

Accurate vs. Inaccurate AI Business Profiles: What the Difference Looks Like

Below is a comparison of the structural differences between a business that AI accurately represents and one that AI consistently gets wrong. The difference is not about size, budget, or how long you have been in business. It is about the quality and consistency of signals AI can cross-reference.

Why Conflicting Directories Are the Primary Cause

If you could only address one contributor to AI inaccuracy about your business, it would be directory conflicts. Not your website. Not schema markup. Directories, because they are third-party sources that AI weights heavily and that businesses rarely monitor after the initial listing setup.

Here is the structural problem: when you first opened your business, or when you first got listed in a major directory, aggregators picked up that data and pushed it to dozens of secondary directories automatically. Those secondary directories rarely update unless you manually correct each one. Years later, after you moved, changed your hours, or updated your phone number, the secondary directories still carry the original information.

AI models trained on the web at scale see those stale secondary directories as legitimate signals. They are real websites, with real content, mentioning your real business name. The fact that the information is outdated is not something AI can independently verify without a ground-truth data source. So it averages across what it sees.

The businesses most affected by this problem are those that have been open for more than three years and have made at least one significant change to their hours, address, or contact information in that time. That describes the majority of established businesses. As we explain in our article on what happens to AI visibility when you change your business name or address, a single address change can take 12 to 18 months to propagate fully across the directory ecosystem, and AI accuracy suffers throughout that entire window.

How Wrong Information Propagates and Compounds

The Most Common Types of Wrong AI Information

Not all business information is equally likely to be wrong in AI answers. The data points that change most often are the ones most likely to be outdated, and some types of incorrect information cause significantly more customer harm than others.

Business hours are the most commonly wrong data point in AI answers about local businesses. Hours change seasonally, temporarily, and permanently, but directory updates lag far behind those changes. A business that updated its hours six months ago may still be showing outdated hours on the majority of directories AI consults.

Physical address is the second most common error, particularly for businesses that have relocated in the last five years. The old address often persists in directories, review platforms, and even in press mentions or articles that AI uses as reference signals.

Phone numbers cause serious problems when wrong because they create immediate failed contact attempts. A customer who gets a wrong number from AI has a worse experience than one who gets a wrong address, because the failure is instant and leaves no clear path to finding the correct number.

Services offered are increasingly wrong for businesses that have expanded or contracted their offerings. If you added a new service in 2025 and your website describes it in detail, but your directory listings and older content do not mention it, AI may confidently tell a customer you do not offer that service when in fact you do.

Owner name and founding year are less operationally critical but still affect how AI presents your authority and history. Wrong founding years are surprisingly common because businesses often have multiple formation dates across different entities, and AI picks up whichever one appears most frequently in its training sources.

Which Types of Wrong Info Cause the Most Customer Loss

Which Sources AI Trusts Most by Platform

Understanding how different AI platforms weight different sources is essential for knowing where to focus your correction efforts. Not all sources carry equal authority in AI systems.

The consistent thread across all platforms: authoritative, cross-source consistency is the strongest signal. Google Business Profile is the single highest-leverage source for local business accuracy because it is a primary trust anchor for multiple AI platforms simultaneously. Keeping your GBP current, verified, and complete is the first defensive action any business should take.

Ignoring the Problem vs. Actively Monitoring AI Accuracy

Why Fixing This Matters More Than Most Businesses Realize

ChatGPT now handles 2.5 billion prompts per day. Even if a small fraction of those prompts are about local businesses like yours, the volume of people receiving AI-generated information about your business is significant. At 900 million weekly active users, even a 0.001% query rate about a single local business could translate to hundreds of impressions per month.

The compounding effect is what makes this particularly important. AI accuracy errors do not stay isolated. When a customer has a bad experience based on wrong AI information, they may leave a review that mentions the confusion. That review becomes another data point AI picks up in future training cycles. The misinformation generates more misinformation.

There is also a trust dimension that is harder to quantify. When a customer discovers that the AI they trusted sent them to the wrong address or gave them the wrong phone number, their confidence in that AI platform drops. But their confidence in your business also drops, because you were the one they went looking for when the error occurred. Wrong AI information creates negative associations with your brand even when you had no control over what was said.

The businesses that address this systematically tend to see measurable improvement in their incoming lead quality and call volume, not because AI starts saying more about them, but because what AI says about them is accurate enough to produce successful customer contacts. An accurate AI profile for a business with verified hours, correct address, and current services listed is a 24/7 referral that actually delivers.

For a broader look at how AI visibility affects whether your business gets mentioned at all, see our article on why AI never mentions your business by name. Accuracy and visibility are related but distinct problems, and most businesses have gaps in both.

AI Accuracy Signals You Need to Control

Frequently Asked Questions

Why does ChatGPT show the wrong business hours for my company?

ChatGPT relies on training data with a cutoff of September 2024. If your hours changed after that date and the update only appears on your website, AI platforms trained before that update will still cite the old hours. Additionally, if multiple older directories still show the original hours, AI probabilistic weighting may favor those sources over your updated website, even after the training cutoff passes. The fix requires updating not just your website but the authoritative sources AI weights most heavily, starting with Google Business Profile and major directories. Call (213) 444-2229 to audit what AI currently shows.

Does updating my website immediately fix wrong AI information?

No. Updating your website is necessary but not sufficient. AI platforms weigh consensus across many sources. If your website now says 7pm closing but thirty directory listings still say 5pm, AI will often defer to the majority signal. The correction must propagate to the authoritative sources AI trusts most, including Google Business Profile, major directories, and structured data on your site. For platforms that use live search like Perplexity, website updates help faster, but directory consistency remains the foundational fix.

What is NAP consistency and why does it matter for AI accuracy?

NAP stands for Name, Address, and Phone. NAP consistency means your business details appear identically across all directories, social profiles, and citations online. When your NAP is inconsistent, AI platforms receive conflicting signals and often default to whichever version appears most frequently across sources, which may not be the current or correct version. Across 50+ directories that aggregators push your business to, even small inconsistencies multiply into significant AI accuracy problems. Email us to learn what a NAP audit covers.

Is Perplexity more accurate about business information than ChatGPT?

Generally yes, because Perplexity uses real-time web search to generate answers rather than relying solely on training data. This means Perplexity is more likely to reflect recent changes to your business information. However, Perplexity still surfaces information from whichever pages rank well for the query, so conflicting directory data can still cause errors. The best approach is to ensure your top-ranking sources, Google Business Profile, Yelp, your website, carry correct and consistent information so that whichever source Perplexity retrieves is accurate.

What types of business information does AI get wrong most often?

The most common AI accuracy errors for businesses involve business hours (especially after seasonal or permanent changes), physical address (especially after a relocation), phone number (after a number change), services offered (if you have expanded or discontinued offerings), and the business name itself (if you rebranded or changed your DBA). Hours errors are the most frequent because they change often and propagate slowly across directories. Phone number errors cause the most immediate customer friction because a wrong number produces an instant failed contact with no clear recovery path.

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

The most reliable approach is to query ChatGPT, Perplexity, and Google AI with questions your customers would ask: your business name, your services and city, and questions like "what are the hours for [your business name]." Note any discrepancies between what AI says and what is actually true. A structured audit, like The Answer Engine's free Blind Spot Report, tests this systematically across multiple platforms and query types, giving you a complete picture of where AI is wrong about you and why. (213) 444-2229