What Does AI Say About Your Business? How to Fix Wrong Information AI Says About Your Business in ChatGPT, Google AI Mode, and Perplexity

Ask a few AI answer engines to describe your company and you may not recognize the business they describe. A price can be out of date, a service you dropped years ago can still be listed, and in some cases the profile quietly blends your company with a competitor that happens to share your name. If that has happened to you, the practical question is how to fix wrong information AI says about your business, and the encouraging part is that the durable fix is within your control.

This guide covers how to check what AI says about you, why answer engines get the details wrong, and the content strategy that keeps your record accurate as your business changes. If your company is not appearing in AI answers at all, that is a related but different problem, and we cover it in our guide to why your business isn't cited by ChatGPT. Here we take the next question: once you are represented, is the information right?

The short version

• Check it yourself first. Ask the major answer engines to describe your business, services, and pricing, then note what is stale, missing, or confused with someone else.
• Understand the cause. Models generate from learned patterns that can be out of date, and a retrieval layer only helps when accurate, current content exists to pull from.
• Fix the basics, then fix the source. Correct your listings and structured data first, then make your own site the clearest and most current authority on your business.
• Keep it current. A one-time cleanup fades. A consistently maintained, authoritative content presence is what keeps AI answers accurate over time.

Why does ChatGPT get my business wrong?

Answer engines do not look your company up in a definitive record and read it back. They generate language from patterns learned during training, and those patterns can be thin or stale for any specific small business. Researchers have a name for the failure mode: extrinsic hallucination, output that deviates from anything the model actually learned or was given. The HalluLens benchmark, published at ACL 2025, formalized this and showed that hallucination is a structural property of current models rather than an occasional glitch. In plain terms, a model can state something about your business with full confidence even when nothing it learned actually supports it.

Newer answer engines add a retrieval step, pulling in web content before they respond. Retrieval helps, but only when there is authoritative, current content to retrieve. As an explainer on how retrieval reduces AI errors puts it, models generate through probabilistic prediction rather than factual verification, and grounding them in real source documents is the most effective way to reduce mistakes. The piece reports error-rate reductions of up to 71 percent in the figures it cites. The catch is simple: if the most authoritative, most current source about your business is missing, out of date, or outweighed by older material, the engine fills the gap with its best guess.

How reliable are AI answers right now?

AI answers are genuinely useful, and they are also wrong more often than their confident tone suggests. The most rigorous public measurement comes from a Tow Center for Digital Journalism study that tested eight AI search tools across 1,600 queries. The tools returned incorrect answers to more than 60 percent of those queries, and they did so confidently, rarely signaling any uncertainty. Performance varied widely from one tool to the next.

One caveat matters for reading these numbers. The Tow Center measured how accurately tools cited news sources, not how accurately they describe a specific company. So this is not a business-error rate. The takeaway is narrower and still important: leading answer engines will state facts and attribute sources incorrectly, with confidence, at meaningful rates.

Even purpose-built tools are not immune. A Stanford study published in the Journal of Empirical Legal Studies in 2025 found that specialized, retrieval-augmented legal-research tools still hallucinated in roughly 17 to 33 percent of cases. That is a very different domain from a business profile, so treat it only as a sense of scale. When even domain-specific, grounded tools miss this often, a general answer engine describing a small business clearly has room to be wrong.

Why this deserves your attention, not your panic

None of this means AI is out to get your business, and it is not a reason to panic. It is a reason to pay attention, because these answers increasingly shape a buyer's first impression before they ever reach your site. Forrester's Buyers' Journey Survey 2025 found that 19 percent of business buyers said they were less confident in a purchase decision because AI systems produced inaccurate or misleading results. That figure measures buyer confidence, not how often AI is wrong, but it makes the cost concrete: when the AI-generated summary of your company is off, some buyers hesitate.

How to find out what AI says about your business

The fastest way to see the problem is to look. Ask the major answer engines, ChatGPT, Google AI Mode, and Perplexity among them, to describe your business, your services, your pricing, and your locations, as if you were a prospective customer. Read the answers closely. You may find stale details, a service you renamed or discontinued, old pricing, or a profile that blends your company with a competitor of the same name. Because the models phrase everything with the same steady confidence, these errors are easy to miss unless you are checking on purpose.

Run the check across more than one engine and more than one phrasing. Different tools draw on different sources, so an error in one may not appear in another, and the pattern across them shows you where your record is weakest.

How to fix wrong information AI says about your business

Once you know what is wrong, the fix happens on two levels. The first is immediate cleanup. The second, and the one that actually lasts, is making your own content the authoritative source these engines learn from and retrieve.

Start with the profile and listing basics

Correct the records the engines lean on for the facts. Make sure your business profile, your primary listings, and the structured data on your own site all show the same current name, services, hours, locations, and pricing approach. Google's own guidance on AI features is blunt about this: there is no secret optimization for AI Overviews or AI Mode. A page has to be indexed and eligible to appear in Search with a snippet, and the levers are the ordinary ones, helpful and reliable people-first content, sound technical setup, accurate structured data, and keeping your profile information current. Making these consistent removes the most common conflicting signals that send an engine astray.

Then fix the source, not just the symptom

Cleaning up a listing corrects today's answer. It does not change the deeper reason an engine got it wrong, which is that your business was not the clearest, most current, most authoritative source on the topic. That is where the durable fix lives. Similarweb's 2026 Generative AI Brand Visibility Index, which benchmarked 113 brands across six sectors, found that authority, not size, is emerging as the differentiator in AI search. Smaller, specialist players with deep, high-quality content on their subject outperformed much larger brands that relied on thin pages. You do not need to be the biggest name in your category. You need to be the clearest and most trustworthy source about what you do.

This is also why the profile fix alone fades. Answer engines that use retrieval can only ground on content that exists and is current. When your site holds the clearest, most up-to-date explanation of your services, your pricing approach, and your expertise, both the retrieval layer and the profile layer resolve to accurate facts. When it does not, the engine falls back on older, heavier associations, and the wrong answer returns.

Keep it current, because your business keeps changing

A one-time cleanup starts aging the moment you change a price, add a service, or open a location. The record only stays accurate if the authoritative source stays current. That is the case for treating your blog and core pages as a maintained asset rather than a one-time project. A steady stream of accurate, specialist, up-to-date content is what keeps your business the source these engines resolve to, and keeping that content accurate and on brand matters as much as keeping it frequent. This is the problem DraftDash was built to solve, publishing consistent, on-brand, search-ready content so your site stays the clearest and most current authority on your business without adding to your team's workload.

Can I report wrong AI answers about my company?

To a degree, yes, and it is worth doing. Most major answer engines include a feedback or report control on their responses, and correcting the underlying records they draw from, your listings, your profile, and your structured data, is the most direct way to prompt a change. Treat this as first aid. Reporting a single wrong answer or fixing one listing resolves that instance, but it does not make your business the source the engines prefer next time. The lasting correction is to be that source, consistently, so the accurate version is simply what there is to find.

The encouraging part

It would be easy to read all of this as a reason to distrust AI search entirely. The evidence points somewhere more useful. The same grounding research that documents the errors also shows the fix works: when a model can retrieve authoritative, current source material, its error rate drops substantially. Google says much the same from the platform side, that there is no trick, only the ordinary fundamentals of helpful, accurate, up-to-date content applied consistently. How AI represents your business is not an uncontrollable black box. It responds to the quality and freshness of what you publish, which means it is something you can steer.

Keep your business the source AI trusts

Have more questions or want to get in touch? If you would rather keep your site the clearest, most current authority on your business without managing it by hand, we can help. Explore how DraftDash works and see our plans, and start turning consistent, accurate content into an advantage in AI search. We look forward to hearing from you.

Citations

1. Association for Computational Linguistics. "HalluLens: LLM Hallucination Benchmark" (ACL 2025)
2. Progress Software. "How Retrieval Improves Accuracy and Reduces Hallucination in AI" (April 2026)
3. Columbia Journalism Review, Tow Center for Digital Journalism. "AI Search Has a Citation Problem" (March 2025)
4. Journal of Empirical Legal Studies (Stanford RegLab and HAI). "Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools" (2025)
5. Digital Commerce 360 (reporting Forrester Buyers' Journey Survey 2025). "Forrester: B2B buyers now demand proof, not promises, about AI" (October 2025)
6. Google Search Central. "AI Features and Your Website" (updated December 2025)
7. Similarweb. "Similarweb Report Benchmarks AI Brand Visibility Winners and Overachievers" (March 2026)