Is AI Telling Prospects the Wrong Price? How to Check and Fix It

The pricing misinformation problem

Imagine a potential customer asks ChatGPT: "How much does [your product] cost?"

ChatGPT answers confidently: "$99/month."

Your actual price is $29/month. But the customer doesn't know that. They've already moved on to a cheaper competitor. You lost a deal you never knew existed.

This isn't hypothetical. Across our first batch of brand audits, the majority had at least one factual error in AI responses. Wrong pricing was the #1 issue.

The majority of brands across our initial audits had at least one factual error in AI responses. Wrong pricing was the most common.

Whether you're a business owner checking what AI tells potential customers about your brand or an agency running audits for clients, the pattern is the same: AI states these errors with complete confidence. There's no asterisk, no "I'm not sure." It presents wrong information as fact.

The most common AI errors we found

Unlike a search engine that shows ten results, AI gives one answer. If that answer has your pricing wrong, every user who asks gets the same wrong number — and there's no competing link to correct it.

Where do these errors come from?

AI models are trained on web content — blog posts, review sites, comparison articles, forums. If a blog post from 2023 said your product costs $99/month, and that post got indexed by the AI's training data, that's now "truth" in the model's mind.

It doesn't matter that you updated your pricing page. AI doesn't check your website in real time. It relies on whatever data it was trained on — what's known as parametric knowledge — which is often months or years out of date (learn more in our AI Visibility Knowledge Base).

Third-party review sites are the biggest culprit. G2, Capterra, and comparison blogs often have outdated pricing and feature information. AI treats these as authoritative sources. If a review from 2023 says your product is "$99/month for enterprise," AI will confidently repeat that — even if you now have a $29/month starter plan.

The second major source is your own legacy content. Old landing pages, archived press releases, and outdated documentation can all feed incorrect information into AI training data. For a deeper look at how these errors propagate and what to do about them, see our guide on fixing AI hallucinations about your brand.

What wrong pricing actually costs you

Let's be concrete. Say your product costs $29/month but AI tells people it's $99/month:

Price-sensitive buyers eliminate you immediately. They never visit your website. They never see your actual pricing. You're out of the running before you even knew you were in it.

Comparison shoppers think your competitor is the better deal. If AI says you're $99 and your competitor is $49, the competitor wins the recommendation — even though you're actually cheaper.

Now multiply that across every AI conversation about your category. If 500 people per month ask AI about tools like yours, and a significant share see wrong pricing, even a small conversion impact compounds fast. A $29/month product quoted at $99/month doesn't just lose one sale — it repositions you as a premium option in every AI answer going forward.

How to fix it

The first step is finding out exactly what AI says about you — every platform, every major query, every claim. This is the core of AI visibility work. Whether you're checking your own brand or auditing a client, you need to know:

• What price does each AI platform quote for the product?
• What features does AI say you have (or don't have)?
• How does AI position you vs. competitors?
• Where is the wrong data likely coming from?

Once you know the errors, you can fix them at the source:

1. Update third-party listings. Go to G2, Capterra, TrustRadius, and every comparison site where your brand appears. Update pricing, features, and positioning to reflect current reality.
2. Add structured data to your pricing page. Use Schema.org Product markup with explicit pricing information in plain HTML. AI crawlers can't execute JavaScript — if your prices load dynamically, they're invisible. Here's a minimal example:

   <script type="application/ld+json">
   {
     "@context": "https://schema.org",
     "@type": "Product",
     "name": "Your Product",
     "offers": {
       "@type": "Offer",
       "price": "29.00",
       "priceCurrency": "USD",
       "billingIncrement": "month"
     }
   }
   </script>

3. Publish clear comparison content. Create "Brand A vs Brand B" pages with accurate, up-to-date information in structured HTML tables. This is the content format AI models extract from most reliably.
4. Remove or update legacy content. Find old blog posts, press releases, and archived pages that reference outdated pricing. Update or add canonical redirects.
5. Re-audit after 4–6 weeks. AI models retrain on different schedules. Measure whether the corrections have propagated into AI responses. For a structured timeline, see our 90-day AI visibility playbook.