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Optimizing for Each AI Search Engine

Tomohiro Iida · Published June 27, 2026 · Updated July 12, 2026

ChatGPT Search, Perplexity, Google AI Overviews, Microsoft Copilot, and Gemini all draw on different search infrastructure and different crawlers, so preparing for one does not automatically prepare you for the others. This guide summarizes the common groundwork that helps with every engine — being indexed, giving clear direct answers, making facts machine-readable, and having original first-party information — before walking through what is specific to each engine: which crawler it uses, what the 'Google-Extended' token actually controls, and why Bing is often an overlooked blind spot for companies that optimize only for Google. It closes with a comparison table and a checklist. Throughout, the guide is explicit that no technique can guarantee that any AI engine will cite or list a given company; the aim is to raise the odds of being found, not to promise placement.

Key takeaways

  • The single biggest difference between the five engines is which search infrastructure they rely on: Copilot uses Bing, AI Overviews and Gemini use Google, and ChatGPT Search and Perplexity use their own crawlers — so the right preparation differs by engine.
  • The common groundwork is the same across all of them: being indexed by search engines, having accurate content, and presenting it in a machine-readable structure. This is where to start regardless of which engine matters most to you.
  • No engine can guarantee inclusion through any particular technique. This guide is about improving discoverability, not promising placement.

The common groundwork (what helps with every engine)

How each engine differs

ChatGPT Search
Uses OpenAI's own index. Its search crawler is OAI-SearchBot, distinct from GPTBot, which is used for model training. To appear in ChatGPT's search results, don't block OAI-SearchBot in robots.txt — blocking GPTBot alone (to opt out of training) does not affect search visibility.
Perplexity
Also uses its own index and crawlers: PerplexityBot for indexing and Perplexity-User for user-triggered page fetches. Perplexity foregrounds source links in its answers, so pages with clear, well-sourced claims and specific figures tend to be stronger citation candidates — though what actually gets cited is entirely Perplexity's own decision.
Google AI Overviews
A feature of Google Search with no dedicated crawler of its own; it relies on ordinary Googlebot indexing. Whether it appears varies by query, region, and time, and it does not show up for many queries at all. Standard SEO — indexing, E-E-A-T, search intent, structured data — applies directly.
Microsoft Copilot
Built on the Bing index, so being properly indexed by Bing is essential. Companies that optimize only for Google (common in Japan) often neglect Bing entirely, making this a frequent blind spot. Registering with Bing Webmaster Tools, submitting a sitemap, and supporting IndexNow are the key preparations.
Gemini
Google's generative AI. Its answers may draw on the model's trained knowledge plus, depending on the feature and settings, grounding from the Google Search index. Whether content can be used for training or grounding is controlled by the 'Google-Extended' robots.txt token — not a separate crawler — and blocking it has no effect on Google Search rankings or AI Overviews.

Engine comparison at a glance

EngineSearch infrastructureCrawler / controlMain preparation
ChatGPT SearchOwn (OpenAI)OAI-SearchBot (search) / GPTBot (training)Allow the search crawler; cite sources clearly
PerplexityOwnPerplexityBot / Perplexity-UserAllow the crawlers; provide well-sourced, primary information
Google AI OverviewsGoogleGooglebot (no dedicated bot)Standard SEO; don't suppress your own snippets
Microsoft CopilotBingBingbotGet indexed by Bing; use IndexNow
GeminiGoogleGooglebot / Google-Extended (a control token, not a crawler)Standard SEO; decide a training-use policy

What not to do, and the limits