Correcting AI: How to Fix Inaccurate Brand Information in ChatGPT and Other LLMs

You asked ChatGPT a simple question about your brand, and it gave a confident, yet completely wrong, answer. It’s a jarring and increasingly common discovery for brand managers everywhere. The 2025 Edelman Trust Barometer special report on AI revealed that 58% of consumers report losing trust in a brand after seeing it misrepresented by an AI, making these inaccuracies a significant threat to your reputation.

While your first instinct might be to find an "edit" button, you can't simply log in and change an LLM's knowledge. But you are not powerless. This guide answers the most urgent questions about this problem and provides a direct, step-by-step framework for correcting the record and regaining control of your brand's narrative in the age of AI.

Table of Contents

• Why Can't You Just "Edit" ChatGPT?
• What Is the Right Way to Correct an AI?
• What Is the Step-by-Step Process for Fixing Inaccuracies?
• How Do You Know If Your Corrections Are Working?
• Frequently Asked Questions (FAQ

Why Can't You Just "Edit" ChatGPT?

Before diving into the solution, it's crucial to understand why a direct edit is impossible. Answering this question requires a basic understanding of how these powerful models work.

How do LLMs actually learn?

Large Language Models (LLMs) are not real-time databases like Google Search. They are trained on massive, static snapshots of the public web. According to a 2025 report from Stanford's Institute for Human-Centered AI (HAI), an LLM's core knowledge is primarily established during its initial training, with subsequent 'fine-tuning' accounting for less than 5% of its total knowledge base. They learn by identifying patterns and what appears to be the consensus on a topic from their training data. To change the answer, you must change the data they learn from.

Why are feedback buttons not a quick fix?

Using the "thumbs up/down" feedback buttons on platforms like ChatGPT is helpful for the AI provider's long-term research, but it is not a reliable or timely method for correcting a specific factual error about your brand. It sends a signal, but it doesn't guarantee a change.

What Is the Right Way to Correct an AI?

The correct, long-term approach to fixing inaccuracies is through a proactive and strategic methodology. This is the foundation of a strong AI Visibility program.

What is Generative Engine Optimization (GEO)?

The right way to influence AI is through Generative Engine Optimization (GEO). This is the strategic process of improving your brand's data and digital footprint to be more accurately understood, interpreted, and trusted by AI models. It's a shift from the old world of SEO vs. GEO; instead of just optimizing for clicks, you are optimizing for truth.

What is the "Overwhelming Consensus" principle?

The core principle of GEO-based correction is to create an "overwhelming consensus" of correct, consistent, and authoritative information about your brand across the web. The goal is to make the right fact so prominent and trustworthy that it becomes the new consensus for the AI to learn from during its next data refresh or update cycle.

What Is the Step-by-Step Process for Fixing Inaccuracies?

Follow this workflow to systematically correct misinformation and manage your brand information in AI.

Step 1: How do you document and diagnose the error?

You cannot fix a problem you haven't clearly defined. Before taking any action, create a precise record of the error.

• Which LLM(s) are showing the error? (e.g., ChatGPT, Claude, Perplexity).
• What was the exact prompt you used? (e.g., "When was [Your Company] founded?").
• What was the incorrect answer? (Quote it verbatim).
• What is the 100% correct information? (e.g., "The correct founding date is March 2012.").

Step 2: Where should you start correcting information?

Your correction campaign must start with the high-authority digital properties you control directly. These are often the first places an AI model looks for trustworthy data. Research by the Wikimedia Foundation in 2025 indicates that Wikipedia articles are among the top 5 data sources referenced in the training sets of most major LLMs.

Your High-Priority Audit Checklist:

• Your own website's "About Us," "Press," and "Contact" pages.
• Your official Wikipedia and Wikidata entries.
• Your Google Business Profile.
• Your LinkedIn Company Page and Crunchbase profile.

Step 3: How do you create a new "source of truth"?

Actively create new, definitive content on your own website that directly and clearly refutes the AI's inaccuracy. This gives AIs and human researchers a clear, authoritative source to cite and learn from. For example, if an AI misstates your product's key feature, publish a detailed blog post or even a technical whitepaper titled "An In-Depth Look at [Correct Feature] in Our Product." You can then promote this through a press release and other channels.

Step 4: How do you influence data you don't control?

This is the most challenging step: correcting information on third-party sites.

• Media Outreach: Politely contact journalists and editors of publications that have published the wrong information, providing a link to your "source of truth" content as proof.
• Partner Websites: Reach out to partners, resellers, or affiliates to ensure your information is correct on their sites.
• Review Sites & Forums: If you see the incorrect fact being repeated in user reviews or forums, reply with a helpful, public correction.

How Do You Know If Your Corrections Are Working?

This process is effective, but it is also manual and time-consuming. A Q2 2025 survey by the Public Relations Society of America (PRSA) found that managing brand reputation across digital platforms now consumes over 12 hours per week for many teams. How do you decide which inaccuracy to tackle first? And crucially, how do you monitor if your corrections are being adopted by the AIs without spending all day prompting them?

This is where the ability to measure your brand's AI Visibility with specialized tools becomes essential for an efficient strategy. An AI Visibility Report from a platform like Mention Network, for instance, is designed to answer the question, "How can I track my progress?" It automates the discovery and monitoring of inaccuracies, showing you if your GEO correction efforts are working and helping you prove the value of your work to leadership. This data-driven approach is critical for understanding the future of AI recommendations and your brand's place in it.

Conclusion

Correcting how an AI perceives your brand is not a quick fix but a continuous, strategic process of curating a truthful and consistent digital identity. By following the framework of Diagnosing, Auditing, Publishing, and Influencing, you can methodically correct the record. While you don't have direct control over AI models, you have significant power to influence their understanding of your brand through a dedicated and persistent GEO strategy, thereby regaining control of your narrative.

What Are Some Frequently Asked Questions (FAQ)?

How long does it take for an LLM to "learn" a correction?

It varies greatly. It depends on the authority of the sources you change and the AI provider's own schedule for data refreshes and model updates. It could be weeks or many months. GEO is a long-term strategy.

What if the wrong information is on a news site I don't control?

Most reputable publications have a corrections policy. Politely contact the editor with a clear explanation of the error and provide a link to your official "source of truth" content on your website as evidence.

Will paying for ChatGPT Plus let me fix my brand information?

No. Premium subscriptions to AI services provide advanced features and access for the user, but they do not grant any special privileges or tools to edit the model's underlying knowledge base. The correction process is the same for all.