March 29, 20269 min read

How to Fix AI Errors and Hallucinations About Your Brand

A practical guide to correcting AI hallucinations: wrong prices, outdated information, incorrect brand descriptions. Diagnosis, correction strategy, and monitoring results.

Vladislav Puchkov

Founder of GEO Scout, GEO optimization expert

When a neural network tells a customer that your product costs $50 instead of the actual $150, or describes a feature you don't have — it's not just an error. It's lost deals, negative customer experiences, and eroded brand trust. According to GEO monitoring practice, hallucinations about prices and specifications affect a significant share of brands that don't invest in GEO optimization.

What Are AI Hallucinations and Why Are They Dangerous

AI hallucination is the generation of factually incorrect information that a neural network presents as reliable. In the context of a brand, this includes:

• Wrong prices and rates — AI states outdated or fabricated prices
• Nonexistent products — AI describes features or services you don't offer
• Outdated descriptions — AI uses information that's 2-3 years old
• Confusion with competitors — AI attributes characteristics of another company to you
• False facts — AI "invents" company history, employee count, or locations

Why Hallucinations Occur

AI doesn't "know" information — it synthesizes answers from available data. Hallucinations arise in three situations:

More about how AI systems choose sources for their responses — in the article what is brand AI visibility.

How to Diagnose Hallucinations

Before fixing anything, you need to understand the scale of the problem. Diagnosis is conducted in three stages.

Stage 1: Systematic Check Across Providers

Ask the same questions about your brand to all major neural networks:

• "What is [brand] and what are their prices?"
• "Tell me about [brand]'s products"
• "Compare [brand] with [competitor]"
• "What are the pros and cons of [brand]?"
• "Where is [brand] located and how many employees do they have?"

Check responses in ChatGPT, Claude, DeepSeek, Gemini, Perplexity, Grok, Google AI Mode, Google AI Overview, and Yandex with Alice. Each provider can hallucinate differently.

Stage 2: Error Classification

Document all inaccuracies found and classify them:

Stage 3: Identifying Error Sources

For each hallucination, determine where AI might have gotten the wrong information:

• Check your website — are there outdated pages with stale information
• Check search engine caches — Google Cache may contain old versions
• Check aggregators and directories — Google Maps, Yelp, review sites
• Check Wikipedia and similar resources
• Check old PR materials and press releases

Correction Strategy: 5 Levels

Fixing hallucinations is not a one-time action but systematic work across five levels.

Level 1: Updating the Primary Source (Website)

Your website is the first source AI systems turn to during web search.

What to do:

• Update all prices and rates to current ones
• Remove or update outdated pages
• Verify that the "About Us" page contains current data
• Ensure product descriptions match the current version
• Update dateModified in page metadata

Critical: Don't leave "ghost" pages with outdated information on your site. If a product is discontinued or a plan is no longer available — delete the page or set up a 301 redirect to the current one.

Level 2: Structured Data (Schema.org)

JSON-LD markup provides AI with unambiguous, machine-readable facts. This is the most effective way to combat hallucinations about specific characteristics.

Priority markup for combating hallucinations:

More about Schema.org markup for AI — in the GEO website audit guide.

Level 3: Authoritative External Sources

AI gives more weight to information confirmed by multiple independent sources. If your website shows a price of $150, but three aggregators show $50 (outdated), AI may choose the majority version.

What to update:

• Google Merchant, marketplaces — current prices and descriptions
• Google Maps, Apple Maps — addresses, business hours, contacts
• Industry directories — descriptions, pricing
• Professional publications — current expert content
• Social media profiles — current company descriptions

Level 4: Content Strategy Against Hallucinations

Create content that directly answers questions where AI is hallucinating:

• If AI incorrectly describes your product — publish a detailed FAQ on your website
• If AI confuses you with a competitor — create a comparison page with clear differences
• If AI attributes nonexistent features — publish a complete feature list including what you don't offer

Format matters: comparison tables, numbered lists, and FAQs are cited by AI more often than plain text. More about this — in the article how to get into neural network recommendations.

Level 5: Monitoring and Iteration

Hallucinations aren't fixed once and forever. New errors appear when models update, data sources change, or new products launch.

Correction cycle:

1. Monitor AI responses (daily)
2. Identify new hallucinations (weekly)
3. Determine the error source (upon detection)
4. Correct primary sources (within 1-3 days)
5. Verify results (after 2-4 weeks)

Provider-Specific Correction Approaches

Different AI providers require different correction approaches.

ChatGPT

• Sources: training data + Bing search
• Update delay: 2-6 months for training data, days for web search
• Correction priority: update website + Schema.org + presence in Bing-indexed sources

Yandex with Alice

• Sources: Yandex ecosystem — search, Zen, Market, Maps
• Update delay: weeks for the Yandex ecosystem
• Correction priority: update Yandex Business profiles, publish on Zen, update Market listings

More about working with Yandex Neural Search — in the article how to check if Yandex Neural Search mentions your company.

Perplexity

• Sources: real-time web search with citations
• Update delay: minutes to hours
• Correction priority: update website — Perplexity will pick up changes faster than anyone

Google AI Mode / AI Overview

• Sources: full Google index + Knowledge Graph
• Update delay: days to weeks
• Correction priority: Schema.org, Google Business Profile, content updates

Prevention: How to Avoid Hallucinations

The best strategy is to prevent hallucinations from appearing. Preventive measures:

Data Consistency

Ensure that the same facts (prices, descriptions, contacts) are identical across all sources:

• Company website
• Google Business Profile
• Aggregators and directories
• Social media
• Press releases and media publications

Regular Updates

• When prices change — update all sources simultaneously
• When launching a new product — prepare a structured description before the announcement
• During rebranding — conduct a full review of all mentions

Proactive Content

• FAQs with questions users ask AI
• Comparison pages with competitors (reduces confusion risk)
• Regular publications with current data and dates

Measuring Correction Effectiveness

How to tell if corrections worked:

Tracking these metrics manually is costly. GEO Scout lets you set up daily monitoring of specific prompts and observe how AI responses change after your corrections.

Checklist: Fixing AI Hallucinations About Your Brand

Diagnosis (1-2 days)

• Check brand responses across all 9 AI providers
• Classify all errors found by severity
• Identify the source of each hallucination
• Establish a baseline to measure progress

Primary Source Correction (week 1)

• Update all prices and rates on the website
• Remove or update outdated pages
• Add or update Schema.org markup (Product, Organization, FAQPage)
• Update profiles on aggregators and directories
• Update Google Business Profile

Content Correction (weeks 2-4)

• Create FAQs for questions where AI hallucinated
• Publish comparison pages with competitors
• Place expert publications with current facts in industry media
• Update publications on Yandex Zen (for Alice)

Monitoring and Iteration (ongoing)

• Set up daily AI visibility monitoring
• Use the Command Center to track corrections
• Verify results 2-4 weeks after each fix
• Update all sources simultaneously when data changes
• Repeat full diagnosis monthly