--- description: AEO targets the AI assistants and AI search surfaces where buyers ask questions, primarily ChatGPT, Google's AI Overviews and AI Mode, Gemini,… image: https://www.leanlabs.com/hubfs/LL%20V4.1/LL%20Featured%20Image.png title: What AI platforms does AEO target? --- Answer Engine Optimization What AI platforms does AEO target? # What AI platforms does AEO target? AEO targets the AI assistants and AI search surfaces where buyers ask questions, primarily ChatGPT, Google's AI Overviews and AI Mode, Gemini, Perplexity, Claude, and Microsoft Copilot. Each engine assembles answers from a different source set and crawls the web under different rules, so visibility on one platform does not transfer automatically to another. Most B2B programs weight ChatGPT and Google's AI surfaces first, then expand. ## The engines that matter for B2B buyers ChatGPT is where most B2B research starts. G2's buyer research found ChatGPT was the preferred LLM for 47% of surveyed B2B software buyers in 2025, nearly three times any other model ([G2 AI search research](https://learn.g2.com/ai-search-surging-for-b2b-buyers)). Google's AI Overviews and AI Mode come next by sheer exposure, since they appear inside the search results your buyers already use. We optimize for ChatGPT, Claude, Gemini, and Perplexity as the core set, and we track Google AI Overviews and Copilot as discovery surfaces that feed the same buying decision. Which of those you weight most heavily should come from your own data rather than from a general ranking, because a security buyer and a marketing ops buyer do not use the same assistant. ## Why you can't treat them as one channel Semrush compared brand and source overlap between ChatGPT and Google AI Mode and found the two engines agreed 67% of the time on which brands to name, but only 30% of the time on which sources to cite ([Semrush AI visibility trend update](https://www.semrush.com/blog/ai-visibility-index-trend-update/)). Two-thirds agreement on brands with less than a third on sources means the engines are frequently reaching the same conclusion by reading completely different pages, and a dashboard number averaged across platforms will paper over that gap. The practical consequence is that tracking has to happen per engine. When a client tells us they're "showing up in AI," we ask which engine and on which prompts, because the fix for a Perplexity gap and the fix for a ChatGPT gap often live on different sites entirely. ## How the engines actually retrieve | Engine | How it assembles an answer | What that changes for you | | ------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------- | | ChatGPT | Uses OAI-SearchBot for search discovery, alongside brand signals it has absorbed from third-party sources ([OpenAI publisher FAQ](https://help.openai.com/en/articles/12627856-publishers-and-developers-faq)) | Crawl permission for OAI-SearchBot is a hard prerequisite, and a robots.txt block quietly removes you | | Google AI Overviews and AI Mode | Grounded in the Search index, and may "fan out" into multiple subqueries across sources before composing ([Google AI features guidance](https://developers.google.com/search/docs/appearance/ai-features)) | Normal indexing and people-first SEO are the eligibility bar, so there's no separate AI submission process | | Perplexity | Performs live web retrieval and separates its indexing crawler from user-requested fetches ([Perplexity crawler docs](https://docs.perplexity.ai/docs/resources/perplexity-crawlers)) | Freshness and clean, retrievable pages carry more weight here than on the others | Claude and Copilot publish less about their retrieval mechanics than Google, OpenAI, and Perplexity do, so we treat them as monitoring targets and rely on the fundamentals that hold across all of them: accessible text, consistent brand facts, and third-party corroboration. You can see how the whole ingestion path fits together on our [demo site for how AEO works](https://www.howaeoworks.com). ## How to prioritize without spreading thin Start with the engines your buyers actually use, then narrow to the prompts that carry commercial intent on those engines. A comparison prompt in ChatGPT that names three competitors and not you is worth more attention than a definitional prompt in an engine your market has never opened. Technical eligibility is the one thing worth doing for every engine at once, since crawl access, indexable pages, and readable text are prerequisites everywhere. After that, the [engine-specific work in our AEO program](https://www.leanlabs.com/solutions/answer-engine-optimization-agency) gets sequenced by where your buyers are and where your gaps are largest. ### Ask AI about Lean Labs [ ![](https://www.leanlabs.com/hubfs/LL%20v5/Images/Logos/chatgpt.svg) ChatGPT ](https://chat.openai.com/) [ ![](https://www.leanlabs.com/hubfs/LL%20v5/Images/Logos/googlegemini%201.svg) Gemini ](https://www.google.com/search?udm=50) [ ![](https://www.leanlabs.com/hubfs/LL%20v5/Images/Logos/perplexity%201.svg) Perplexity ](https://www.perplexity.ai/search/new) [ ![](https://www.leanlabs.com/hubfs/LL%20v5/Images/Logos/claude%201.svg) Claude ](https://claude.ai/new) [ ![](https://www.leanlabs.com/hubfs/LL%20v5/Images/Logos/copilot.svg) Copilot ](https://copilot.microsoft.com/) Ask AI ```json { "@graph": [ { "@id": "https://www.leanlabs.com#organization", "url": "https://www.leanlabs.com", "logo": { "url": "https://www.leanlabs.com/favicon.ico", "@type": 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