What this means
How AI systems choose which retrieved sources support or appear in an answer.
Historical record
Perplexity introduces Q2D-Web for large-scale retrieval evaluation in agentic RAG
The visible user prompt is not necessarily the query a source competes for. AI visibility therefore depends on several distinct stages: query reformulation, first-stage retrieval, ranking, evidence selection, and eventual citation.
ChatGPT launches Shopping Research
Product visibility now includes machine-readable product data, reliable attributes, merchant data and recommendation eligibility.
Google introduces AI Mode and describes query fan-out
Visibility is no longer tied only to the user’s literal query; sources can be discovered through hidden subqueries and related retrieval paths.
Google launches AI Overviews broadly in U.S. Search
AI inclusion, source selection and click behavior became material concerns for mainstream SEO and GEO strategies.
Google announces Search Generative Experience (SGE)
The dominant search platform formally entered generative search, making AI-mediated source selection a core visibility issue.
OpenAI WebGPT demonstrates browser-based answering with citations
The retrieve-read-cite pattern closely anticipates later AI answer engines and modern citation optimization concerns.
Retrieval-Augmented Generation (RAG) is formalized in research
RAG is one of the core technical patterns behind modern AI search, source retrieval and citation behavior.