How do different AI models – ChatGPT, Gemini, Claude, Perplexity – differ in how they talk about brands?

The major engines differ in source mechanics and those differences tend to show up directly in how they describe brands. ChatGPT pulls from a broad training corpus including books, news archives, web content, Reddit and forum content, plus retrieval through ChatGPT Search; the framing often leans neutral with weight on whatever sources the model considered most authoritative in training. Gemini tends to lean heavily on the Knowledge Graph, Wikipedia, and Google’s index, often producing answers that closely track what Google itself returns about an entity. Claude tends toward cautious phrasing and a clear willingness to caveat or refuse on contested topics. Perplexity is typically citation-first, showing the sources inline and producing answers tightly coupled to what its retrieval finds in the moment. Copilot tends to emphasize Microsoft’s enterprise and Bing index. Grok tends to pull heavily from X. Each pattern has implications for which source-layer interventions move which engine fastest, and AIQ™ exposes the differences directly so the work is targeted.