What Does AI Say About Your Brand? A Practical Guide to Auditing Your Reputation in AI Search

September 19, 2026

An analyst auditing AI-generated information and online sources about a brand

What Does AI Say About Your Brand? A Practical Guide to Auditing Your Reputation in AI Search

When someone wants to learn about a company, executive or product, they may now ask ChatGPT, Gemini, Perplexity or another AI assistant instead of working through a page of traditional search results, which means the answer they receive—whether accurate, incomplete or outdated—can influence their opinion before they visit the company’s website.

This behavior is already significant: a 2025 McKinsey survey of 1,927 US consumers found that half intentionally used AI-powered search, while 44% of AI-search users described it as their primary and preferred source of information, compared with 31% who preferred traditional search. More than 70% of these users asked questions intended to help them learn about a category, company, product or service, making the information presented by AI directly relevant to brand reputation and purchasing decisions. Source: McKinsey

AI Search Is Also Changing Google

Businesses should not think of AI search as separate from Google, because AI-generated summaries are increasingly appearing inside conventional search results and may provide an answer before a user visits another website.

Pew Research Center analyzed 68,879 Google searches made by 900 US adults and found that 18% produced an AI summary, rising to 60% among searches beginning with words such as “who,” “what,” “when” or “why.” When an AI summary appeared, users clicked a traditional search result in only 8% of visits, compared with 15% when no summary appeared, while just 1% clicked a source cited within the summary itself. Source: Pew Research Center

This means the summary itself may be the only information a user reads, increasing the importance of understanding how AI systems describe your organization and which sources are shaping that description.

Run an AI Reputation Audit

Select several platforms and ask each one the same questions in a new conversation, because previous prompts can influence later answers and make comparisons unreliable.

Useful questions include:

  • What is [company] known for?
  • Is [company] trustworthy?
  • What are the main criticisms of [company]?
  • Has [company] been involved in any controversies?
  • Who is [executive], and what are they known for?
  • What do customers or employees say about [company]?
  • How does [company] compare with [competitor]?

Include neutral, positive and critical questions, because the purpose is not simply to search for negative statements, but to identify outdated descriptions, factual errors, mistaken identity, missing services, unsupported claims and differences between platforms.

Record and Classify the Results

Create a table recording the platform, question, date, answer, cited sources, accuracy and reputational risk, then classify each finding as accurate, partly accurate, inaccurate, outdated or unverifiable.

The most serious findings usually involve false claims, confusion between similarly named people or organizations, outdated allegations presented without later developments, excessive reliance on one weak source or confident conclusions that are not supported by the available evidence.

An unfavorable fact should not automatically be classified as inaccurate, however, because an audit loses credibility when legitimate criticism is treated as an error simply because it is damaging.

Trace Every Answer Back to Its Sources

When an AI answer provides citations, open each source and determine what it actually says, when it was published and whether the AI represented it fairly; when citations are absent, search distinctive phrases from the answer and examine the leading results for the same question.

This step matters because the visible answer is often only the symptom, while the underlying problem may be an old article ranking prominently, an inaccurate directory listing, conflicting executive biographies, an abandoned profile or a lack of authoritative information addressing a frequently searched subject.

McKinsey found that a brand’s own website can account for only 5–10% of the sources referenced by AI search in some cases, demonstrating why updating a corporate website alone may not correct the wider information environment.

Improve the Information Environment

Begin with assets you control by correcting inaccurate website copy, updating executive biographies, aligning company descriptions, adding dates where context matters and publishing clear, evidence-based answers to important questions.

Next, review significant third-party profiles and request corrections where factual information is wrong, while building credible external coverage through expert commentary, original research, interviews and useful articles that independent publishers can reference.

Technical accessibility remains important, but there is no secret collection of “AI optimization” tricks: Google states that its established search fundamentals still apply to AI features, including allowing pages to be crawled, making important information available in text and ensuring structured data matches the visible content. Source: Google Search Central

Monitor the Results

Finally, repeat the audit monthly and after major announcements, leadership changes or periods of intense media coverage, because the goal is not to force every platform to produce a positive description, but to ensure that people encounter information that is accurate, current, properly sourced and complete enough to support an informed opinion.