AI search optimization is the adaptation of search strategy for AI-powered search experiences - Google's AI Overviews, Perplexity, ChatGPT's web search and similar - where an AI reads sources and composes a direct answer with citations, instead of only ranking links. The goal shifts from winning the click to being the cited source.
AI search engines retrieve, read and synthesize. To be cited, content needs to be retrievable (classic technical SEO still applies), quotable (clear claims, definitions, data points) and trustworthy (authority signals, consistent entity data).
Practical moves: answer questions directly near the top of pages, use structured data, publish original numbers and comparisons AIs like to cite, and keep facts about your business identical everywhere they might be read.
It overlaps GEO but is narrower: AI search optimization targets citation in search-grounded answers; GEO also covers what models say from their training knowledge when no live search happens.
Why it matters
AI answers absorb the clicks classic results used to get. Being the cited source keeps you in the journey; being uncited makes even a #1 ranking invisible inside the answer box.
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