How to correct what AI says about your brand

You can’t edit an AI answer directly, but you can change the sources it draws from. Correcting what AI says about your brand means finding the wrong answers, tracing them to the pages that feed them, fixing what you own, earning corrections on pages you don’t, and re-checking until the answer changes. It works best as a repeating loop, not a one-off fix.

This chapter of the AI Visibility Engineering guide walks through that loop step by step. If you first want to understand why errors happen and what they can cost, start with when AI gets your brand wrong: accuracy and risk.

Why you can’t just ask AI to fix it

AI answer engines don’t keep an editable profile of your brand. They assemble answers from what they learned in training and, increasingly, from pages they retrieve at the moment someone asks. If those pages are outdated, inconsistent or written by someone with a different agenda, the answer inherits the problem.

That means the fix is upstream. You change the evidence, and the answer follows. It also means the fix takes time, because models and retrieval indexes refresh on their own schedules, not yours.

Step 1: Start with one real buyer question

Don’t try to audit every possible prompt at once. Pick one question a real buyer, patient, client or journalist actually asks, ideally one you heard on a sales call, in support tickets or in search data.

Good starting questions tend to be:

• High stakes: pricing, eligibility, safety, availability or what your product does and doesn’t do.
• Comparative: “Is [brand] better than [competitor] for X?”
• Recent: anything touched by a rebrand, merger, product change or policy update.

One well-chosen question run through the whole loop teaches you more than a spreadsheet of fifty prompts checked once.

Step 2: Find out what AI actually says

Ask the question in the answer engines your audience uses, such as ChatGPT, Google AI Overviews and AI Mode, Perplexity, Gemini and Copilot. Ask it a few different ways, because small wording changes can produce different answers.

For each answer, record:

• What the answer says about your brand, word for word.
• Whether it’s accurate, outdated, incomplete or simply wrong.
• Which sources it cites, if any.
• Which competitors appear alongside you or instead of you.

Keep these as a saved set of monitoring prompts. You will rerun the same set later to see whether anything moved.

Step 3: Trace each error back to its source

Most wrong answers have a traceable origin. Common ones include:

• Your own stale pages: an old pricing page, an archived press release or a product page nobody updated.
• Inconsistent facts across your site: different founding dates, service areas or feature lists on different pages.
• Third-party listicles and directories that copied old information.
• Forum threads and reviews, such as Reddit discussions, where one confident comment gets repeated.
• Competitor comparison pages that describe you on their terms.

Cited sources make this easier, but even when an answer cites nothing, searching for the exact wrong claim usually turns up the pages that repeat it. For more on why some sources get picked over others, see how LLMs choose citations across ChatGPT and Google.

Step 4: Fix what you own first

Your own site is the one source you fully control, so it should be the clearest, most current statement of the facts.

• Answer the question directly. Put a plain, quotable answer near the top of the most relevant page, under a heading phrased the way people ask.
• Make the facts consistent everywhere. Name, description, pricing model, locations, leadership and product details should match on every page, in your structured data and on your profiles. The Klass Wagen case study on consistent brand facts shows what that alignment looks like in practice.
• Retire or redirect outdated pages rather than leaving conflicting versions live.
• Attribute expertise. Where accuracy matters, show who wrote or reviewed the content and why they’re qualified.
• Add a dated FAQ for the specific misconception, so there’s a direct, citable correction.

Step 5: Earn corrections on pages you don’t own

Owned content alone rarely outweighs several third-party pages saying the opposite. AI systems look for corroboration, so the correction needs to appear in places they already trust.

• Ask for updates. Many directory owners and listicle editors will fix factual errors when you send a short, polite note with the correct information and a link to your source page.
• Pitch the same proof to relevant publications. An earned mention in a trade outlet that states the correct facts gives AI a second, independent source.
• Participate where the conversation happens. In communities like Reddit, a transparent, helpful reply from a named company representative can add accurate context to a thread that’s being cited.

The melin case study on correcting how LLMs describe a brand shows how Reddit, listicles and PR can work together to shift the description over time.

When a third party earns you an accurate mention, link to it from your own relevant page. That ties the corroboration back to your owned answer.

Step 6: Distribute, then amplify only what works

Share the corrected answer and any earned coverage through your own social channels and newsletters. Watch which posts draw real engagement and new questions, because those questions are often your next monitoring prompts.

Paid promotion belongs at the end of this step, not the start. Boost a post only after it has shown organic traction and the facts behind it are settled. Paying to spread a message before the sources agree can amplify confusion instead of fixing it.

Step 7: Re-check, and feed the next round

Rerun your saved monitoring prompts on a regular schedule, such as monthly, and compare against your first record. Look for:

• Whether the wrong claim still appears.
• Whether your corrected page or new third-party sources are now cited.
• Whether new errors or new questions have surfaced.

Anything new becomes the next buyer question, and the loop starts again from a stronger position. In our client work we see that brands treating this as an ongoing process hold their corrections far better than brands that fix one page and move on.

When the stakes are higher: regulated and YMYL brands

For finance, health, legal and other “your money or your life” categories, a wrong answer can create compliance exposure or real harm to the person relying on it. The loop is the same, with tighter controls:

• Review every correction with compliance or a qualified subject matter expert before it goes live.
• Prioritize accuracy over reach. More visibility for an inaccurate answer is a liability, not a win.
• Keep an escalation path for answers that could cause harm, including who decides and how fast.
• Document what you changed and when, so you can show a good-faith effort to keep information accurate.

Public trust is part of the stakes too. The US AI Search Trust Survey statistics cover how Americans view the reliability of AI search answers.

Frequently asked questions

How long does it take for AI answers to change?

It varies by platform and by how the answer is produced. Answers built from live retrieval can shift within weeks once the cited sources change, while answers that lean on a model’s training data may take until the next model update. Track progress with the same saved prompts so you can see when the change lands.

Can I contact OpenAI or Google to correct an answer?

Most platforms offer feedback buttons on individual answers, and it’s worth using them for clear factual errors. But feedback alone rarely fixes the underlying problem. Changing the sources the answer draws from is the more dependable route.

What if the wrong information comes from a competitor’s page?

Make sure your own pages state the correct facts clearly, then build independent corroboration through reviews, directories and earned coverage. If a competitor’s claim is factually false, a direct, documented request for correction is reasonable. Avoid public arguments, which can add more confusing content for AI to draw on.

Do I need to fix every wrong answer?

No. Prioritize errors that affect buying decisions, safety, compliance or your reputation. Minor inaccuracies in low-stakes answers can usually wait until the higher-impact ones are handled.

Should I use paid ads to push the correct answer?

Paid promotion can help spread an accurate message once the facts are consistent across your site and third-party sources. It doesn’t change the sources AI cites by itself. Use it to amplify proof that is already working, not as a substitute for fixing the sources.