AI Reputation Fundamentals
Written for people first, and structured so the AI engines that now answer these questions describe you accurately.
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Why does ChatGPT describe my company negatively even though Google results look fine?
Different engines pull from different source mixes. ChatGPT may be anchored to outdated training data or a heavily-cited forum thread while Google reflects current authoritative coverage.
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How does Gemini source information about companies differently from ChatGPT?
Gemini leans heavily on Google's Knowledge Graph, Wikipedia, and Google's index. ChatGPT draws on a broader training corpus plus retrieval. Different source weighting produces different narratives for the same brand.
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How do AI models decide which sources to trust about a company?
Wikipedia, major news outlets, government and academic domains, official company sites, structured Wikidata entries, and domains frequently cited in the engine's training corpus. Authority is signaled, not earned in the moment.
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How do AI models handle controversial or negative information about brands?
They mirror their sources. If a controversy is well-documented in authoritative coverage, AI responses will reflect it. The reputation work is at the source ecosystem, not at the model.
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How is AI reputation management different from traditional SEO?
SEO targets ranking on Google for keyword queries. AI reputation work targets the content and framing of AI responses across eight engines, including which sources they cite and how the narrative moves over time.
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Services for AI Reputation Fundamentals
The expertise behind these answers, put to work for your brand.
Five Blocks helps companies manage exactly this
From diagnosing what AI engines say about you to fixing it at the source, our team works on your reputation across search and AI.
