AI discoverability

Spencer Thursfield · Last reviewed 2026-08

AI search adds a selection layer on top of ordinary search engines. Where a results page showed ten blue links, that layer chooses a handful of sources. This pillar explains how the choosing works, as far as public evidence allows, and what a small business can do about it.

The essential facts, each covered in depth in this pillar's articles:

• AI search is retrieval first. Google's generative features run on Search's core ranking systems; ChatGPT search depends on its own crawler reaching you and its rewritten queries matching you. If you are not retrievable, nothing downstream matters. Official recommendation
• One question becomes many. Systems issue multiple related searches for a single question, a mechanism called query fan-out, so pages compete on sub-questions they never targeted. Official recommendation
• Selection is volatile. The same question, asked twice, can cite different sources. Anyone promising a stable "AI ranking" describes a system that does not behave that way. Emerging
• Being cited and being used are different. A page can be listed as a source without shaping the answer, and shape the answer without prominence. Our study measures the two separately. Emerging
• There is no secret markup. No special schema, file or chunk size buys inclusion; see the folklore ledger. The platforms' own guidance rewards retrievability, relevance, and material that is not a commodity. Official recommendation

In this pillar

• How AI search finds sourceslive
• What makes a page citablelive
• Crawler controls: search vs traininglive
• How query fan-out changes content strategylive
• Appearing in ChatGPT searchlive
• Google AI Overviews · Google AI Mode · Gemini · Perplexity · Measuring AI citations · Browser agentsplanned