Glossary entry
AI Search Optimization
Definition
AI Search Optimization is the practice of making a brand visible, citable, and recommended by AI engines (ChatGPT, Gemini, Perplexity, Claude) when users ask category-relevant questions. It covers schema deployment, llms.txt, content rewrites for AI extraction, and ongoing AI citation monitoring.
How it works
The mechanism.
AI engines pull information from a mix of sources: their training data, web crawl, structured data on your site, and Wikidata entries. AI Search Optimization deploys signals each of these systems uses — FAQPage schema, Organization schema with knowsAbout, llms.txt, Wikidata entries, citable statistics, comparison content. The work is continuous because AI engines update constantly.
Why it matters
Why this matters in 2026.
Over 40% of search-style queries in 2026 happen inside AI assistants. If AI engines don't know about your brand, you're invisible to that 40% — and the percentage grows every quarter as users shift from Google to AI tools.
How to check
How to test for it.
Free AI Visibility Checker at www.adsomia.com/tools/ai-visibility-checker. Tests 25 queries across the 4 major AI engines (ChatGPT, Gemini, Perplexity, Claude). Returns an AI-Readiness Score 0-100.
Adsomia services
Where this fits in our work.
Common questions
About AI Search Optimization.
Is AI Search Optimization different from GEO?
AI Search Optimization is broader. GEO focuses specifically on generative answer surfaces (the synthesized answer at the top of AI responses). AI Search Optimization covers GEO + general visibility across AI engines + citation monitoring.
Will AI engines replace Google search?
Probably not fully. Both will coexist — Google with AI Overviews + traditional rankings; ChatGPT/Perplexity/Gemini as discovery + answer surfaces. HEO covers both worlds.
Related terms
Read next.
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