AI engines are the systems that answer questions by retrieving, grounding, and synthesizing web content. They differ in how they fetch sources, how they cite them, and how much of the answer comes from live retrieval versus model memory.
What AI Engines covers
This page links to the main subtopics in this area:
- Citations — source selection and attribution across engines.
- ChatGPT — OpenAI’s answer and search surfaces.
- Google Gemini — Gemini grounding and source behavior.
- Google AI Mode — Google’s generated answer experience.
- Perplexity — answer engine behavior and crawler patterns.
- Claude — Anthropic’s assistant and web search behavior.
- Bing Copilot — Microsoft’s answer experience and Copilot crawlers.
- Grok — xAI’s answer surface.
- Meta AI — Meta’s assistant behavior.
- You.com — the search-and-answer experience.
Why it matters
Different engines favor different source types, citation styles, and retrieval patterns. A page that works well for one engine may not perform the same way in another, so track by engine-specific share of voice.
Example:
Ajey is checking how AwesomeShoes Co. appears across engines before launching a new product page. ChatGPT may prefer a direct answer and one cited source. Perplexity may pull a longer source list. Google AI Mode may surface the page through search-style grounding. The same page can perform differently in each system, so the work has to be measured per engine instead of assumed from one result.
Implementation discussion: Ajey and the analytics lead run fixed engine-specific query sets, compare citation and mention patterns by platform, and route findings to content or technical owners based on root cause. This keeps strategy aligned to how each engine actually retrieves and synthesizes sources.
