Research & Insights on AI Visibility

AI systems like ChatGPT, Perplexity, and Google AI Overviews make citation decisions about organizations every day. We research how those decisions are made, what signals drive them, and how organizations can structure their presence accordingly.

Research by Mia Cheraghian, PhD

Three Research Initiatives

AI Visibility Index

A research initiative measuring how organizations appear across AI systems such as ChatGPT, Perplexity, and Google AI Overviews. The index evaluates entity consistency, authority signals, cross-platform presence, and information architecture to produce a quantified understanding of AI visibility.

AI Search Ecosystem Map

A framework explaining how generative AI systems retrieve and synthesize information from the internet. This maps the relationships between knowledge graphs, trusted source hierarchies, website content, structured data, and the citation selection process that produces AI-generated answers.

AI Discoverability Framework

A strategic model explaining how organizations can structure their information so AI systems correctly interpret, reference, and recommend them. This framework connects information architecture principles to the specific behaviors of generative search systems.

A new information layer is forming

People are asking AI for recommendations instead of scrolling through search results. AI must decide which organizations to name — based on information consistency, authority signals, content structure, and technical readability. This layer follows different rules than traditional search. Organizations that understand it early will compound advantages that late movers spend years closing.

Upcoming Studies

AI Visibility for Nonprofits

How mission-driven organizations with limited marketing resources can structure their presence for AI discoverability.

Generative Search Behavior

Comparative analysis of citation selection behaviors across ChatGPT, Perplexity, Google AI Overviews, and Copilot.

AI Citation Patterns

What types of content, sources, and structured data correlate with higher AI citation rates across industries.

Information Architecture for AI Systems

How organizational information should be distributed and structured for AI systems that synthesize from multiple sources.

Research updates will be published on our Insights page.

Interested in our research?

We work with organizations who want to understand how AI search systems interpret their presence.