What Do You Do When AI Gets Your Product Wrong?

What do you do when AI gets your product wrong?

You fix the source, not the answer. There is no support ticket that corrects a model's opinion of your product. What you can change is the text those systems read: your own pages, your review profiles, and the third-party pages that describe you. Then you wait, and check again.

This comes up in almost every kickoff call now. A founder asks ChatGPT about their own category, gets a price that has not been true since 2024, a feature they killed, or a competitor named as the better option, and wants to know who to email.

Nobody. That is the uncomfortable part, and it is also why the work is more within your control than it feels. Here is how we approach it.

Why do AI answers get product facts wrong?

Usually because your own site never said the right thing clearly. Models assemble answers from crawled pages, review profiles, forum threads and old articles. When your pricing lives in a PDF, your features live in a slide deck, and your positioning lives in a founder's head, the model fills the gap from whatever it can read.

Stale third-party content is the second cause. A 2023 roundup that listed your old plan names may outrank your current pricing page, and it will keep being cited long after you rewrote it.

Google itself sets expectations openly. Its help page for AI Overviews says the technology is rapidly evolving and may provide inaccurate or offensive information, and tells people to always check important info in more than one place. If the vendor says that, plan for it.

How do you find out what AI says about you?

Ask it, on purpose, on a schedule. Write down the ten questions a buyer would really type. What does your company do, what does it cost, who is it for, how does it compare to your main rival, is it any good for a team of fifty. Then run them in each assistant and save the answers.

Do it in a clean session without your account history, because a logged-in chat that knows you already shapes the reply. Record the date, the exact question and the sources cited. That file becomes your baseline.

The platform reporting helps with visibility but not wording. Google's Search Console insights, rolled out worldwide by 31 August 2026, include impressions metrics plus which pages appear in AI responses and in what countries. Useful, and silent on what the answer said. Our piece on measuring brand visibility in AI answers covers the tracking side in more depth.

Is there a way to report a wrong AI answer?

There is a feedback path, and you should use it, without expecting much. Google's AI Overviews support page describes rating a response with thumbs up or thumbs down, and clicking Report a problem to choose the category that describes the issue, with a text field for detail.

That is a signal into a quality process, not a correction request. No major vendor publishes a turnaround time for fixing a specific claim about a specific company, and we have never seen one commit to a single answer changing on request.

So treat feedback as a five minute task and put the real effort into the pages. One is free and slow. The other is the actual lever.

Does blocking the AI crawlers fix anything?

No, and it usually makes things worse. OpenAI's documentation is clear about the trade. OAI-SearchBot is used to surface websites in search results in ChatGPT's search features, and sites opted out of it will not be shown in ChatGPT search answers, though they can still appear as navigational links.

Read that twice, because people get it backwards. Blocking the search crawler does not stop ChatGPT talking about you. It stops ChatGPT quoting your site while it talks about you. Your competitors and a 2023 listicle are happy to fill in.

The separate bots do separate jobs. GPTBot crawls content that may be used to train foundation models, so disallowing it is a training decision. ChatGPT-User handles certain user actions in ChatGPT and Custom GPTs, and OpenAI notes that because those actions are initiated by a user, robots.txt rules may not apply. Our guide to controlling AI crawlers in robots.txt walks through each line.

Google works the same way. Its documentation points to nosnippet, data-nosnippet, max-snippet and noindex as the controls, and its Search Console toggle lets a site opt out of generative AI features entirely, at the cost of all traffic and impressions from them.

What actually changes an AI answer about your product?

Clear, current, checkable text in the places that get crawled. In our experience the pattern that moves answers is boring: publish the fact plainly on your own site, repeat it in the same words where buyers verify things, and remove the stale versions you control.

Consistency matters more than volume. If your homepage says one thing, your pricing page implies another and your G2 profile says a third, you have taught every system that your facts are soft. Pick the wording once and use it everywhere.

Numbers are the strongest lever. Prices, limits, seat counts, uptime, supported regions and integration counts are all things a model will happily state, and it will state whatever it found. Publish the real ones in plain text, not in an image.

Which pages should you fix first?

Pricing, then the product overview, then integrations. Pricing is where wrong answers do commercial damage, because a buyer who hears the wrong number either self-disqualifies or arrives angry. Product overview shapes the one paragraph a model writes about you. Integrations decide whether you appear in any workflow question.

Write each of those pages so a stranger could restate it correctly after one read. Short sentences, named plans, real figures, no adjectives doing the work of facts.

Then add the specifics that get quoted: what you do not do, which team size you fit, which regions you serve. Disqualifying detail is oddly powerful here, because it is the part no marketing page usually includes.

Should you publish a corrections or facts page?

We like a plain facts page, and we would not call it corrections. One page listing your current plan names and prices, founding facts, headcount range if you publish it, supported integrations and the questions people get wrong, written as short prose and dated, gives every system one canonical place to read.

It is not a magic trick, and no vendor promises to prefer it. It is a cheap way to make the right version the easiest version to find, and it doubles as a briefing page for your own sales team.

Keep it honest and keep it current. A facts page with last year's numbers is worse than none, because it looks authoritative while being wrong. Our notes on statistics pages and AI citations cover how we structure this kind of page.

What do we do when the comparison itself is wrong?

We answer it on our own site rather than arguing with the machine. If an assistant says a competitor does something you also do, the gap is almost always that their page says it in plain words and yours does not. Write the page that makes the claim checkable.

Where a third party published something false about you, ask them to correct it, politely and with evidence. Publishers update pages more often than people expect, and one corrected roundup can quietly change what gets summarised.

What we would not do is buy placements to drown it out. That is renting somebody's rankings, and Google's spam policies now describe that pattern as site reputation abuse. It is a bad trade even when it works.

What should you expect over the next year?

More surfaces, better controls, and no correction button. The trend in vendor documentation is towards opting out and reporting, not towards editing. Meanwhile AI Overviews sits at over 2.5 billion monthly active users by Google's own June 2026 count, so the cost of being described badly keeps rising.

The durable answer is unglamorous and it has not changed in twenty years of search: be the clearest, most current, most checkable source about your own product. Everything else is a workaround.

If you want help finding which pages are teaching the wrong answer about you, we are happy to walk through it. You can see how we build and write for this at phoenix.studio.