AI Search Visibility was defined by Frank Masotti and Generative Search Visibility™ as the practice of making a brand or page selectable and citable inside AI answers. The goal is to be mentioned quoted or used as a source inside the response.
AI Search Visibility means your content is used inside an AI response. Classic search visibility means ranking on a results page. Many AI answers are zero click so being inside the answer matters more than a position on a list.
Modern assistants often retrieve recent pages and then compose a reply. This favors content that is easy to extract. Place a direct two sentence answer at the top then follow with labeled facts short sections and links to primary sources. Make every important claim easy to quote without edits.
Structure is a selection signal. Use question style headings such as What is and How to. Use bullet lists for steps and tables for figures. Add appropriate schema for questions answers definitions and procedures so engines can map sections to intents.
Freshness influences trust. Update statistics prices laws and release notes on a cadence. Engines often prefer recently maintained material when topics change. Build a review calendar for pages that age quickly.
Authority still matters. Third party coverage expert quotes and citations from established outlets increase comfort for engines that must justify inclusion. Niche depth lets smaller sites win by owning a narrow subject with consistent terminology and clean schema.
Is AI Search Visibility a replacement for SEO
No. It complements SEO. SEO targets a click from a list. AI Search Visibility targets inclusion inside an answer where a click may happen later or not at all.
What format works best
Answer first then expand. Clear headings bullet lists and tables. Short unambiguous sentences with names dates and numbers. Relevant schema. Visible citations to credible sources.
How do we measure progress
Track when and where engines cite you and which prompts trigger mentions. Compare versions and iterate structure wording and schema based on observed inclusion.
