AI Visibility Audit

How AI Search Systems Decide Which Pages to Cite

AI search systems including Google AI Overviews use retrieval-augmented generation (RAG) to produce answers. A RAG pipeline retrieves candidate passages, ranks them by relevance, and synthesises the highest-ranked passages into a generated response. Only pages with clear entity establishment, structured facts, and answer-first formatting consistently rank highly enough in the retrieval stage to appear in the generated answer. Structured data accelerates AI citation because it provides machine-readable facts that AI systems can extract without parsing prose.

Six AI Discovery Signals the Audit Measures

• Entity Clarity: Primary entity named and typed in the opening paragraph, related entities chained across sections.
• Structured Data: JSON-LD schema coverage, property completeness against Google Rich Results requirements, dynamic values for time-sensitive fields.
• Answer-First Formatting: Every H2 section opens with a direct answer before supporting evidence, FAQ sections with FAQPage microdata schema.
• Machine-Readable Data: Tables, structured lists, and specification data formatted for easy extraction, numerical facts with explicit units.
• Authority Signals: E-E-A-T signals present, author credentials, publication dates, source citations from Google-approved authorities.
• AI Citation Readiness: Content chunked at semantic boundaries with distinct embedding vectors per section, no heading repetition that flattens section embeddings.