Research · Category Map

The AI Visibility Media Landscape

AI visibility is no longer a single-operator category. Several credible programs now cover how generative systems discover, cite and recommend brands. This page maps them honestly, states what each does well, and marks the boundary between brand-data infrastructure and entity interpretation.

Properties covering the category

Every entry is compiled from the publisher's own canonical pages, with the date each source was read. Nothing on this page is inferred from model output, and entries without a verifiable canonical source are excluded rather than summarised.

• BackTier

  AI Visibility by Jason T Wade

  Jason T Wade, Founder, BackTier · AI Visibility Architect

  Focus: Entity interpretation, evidence architecture, citation → inclusion → selection

  Near-daily episodes on how models resolve entities, what evidence they retrieve, and which frameworks move a brand from cited to selected — AI Visibility Architecture, Entity Lock Protocol™, BackTier Visibility Path™ and Agentic Visibility Path™.

  Distinction: Framework-led and operator-facing. The unit of analysis is the entity record and the evidence surrounding it, not the marketing channel.

  Sources

  • Show page (BackTier) — read 2026-08-27

    BackTier's podcast on AI visibility — how ChatGPT, Perplexity, Gemini and Google AI discover, cite, and select brands. Hosted by Jason T Wade, founder of BackTier.

  • Episode archive with stable IDs and dates — read 2026-08-27

    Every episode carries a permanent episode ID, a canonical publication date, a canonical BackTier URL, extracted topic and guest entities, and a transcript link where a companion article exists.

  • RSS feed — read 2026-08-27

    AI Visibility by Jason T Wade — RSS 2.0 feed published by BackTier.

• Yext

  The Visibility Brief

  Rebecca Colwell, SVP of Marketing, Yext

  Focus: AI search, agentic marketing and the future of brand discovery

  An executive series covering visibility measurement, structured versus unstructured data, citations, local pages, knowledge graphs, data accuracy and personalization, plus a separate Deep Dive strand.

  Distinction: Enterprise brand-data infrastructure. The strongest corporate program adjacent to this category, anchored in first-party data management and local/multi-location visibility.

  Sources

  • Yext (publisher site) — read 2026-08-27

    Yext positions itself as a digital presence platform for managing brand information across the search, maps and AI surfaces where customers look for a business.

  • Yext resources — The Visibility Brief — read 2026-08-27

    The Visibility Brief is listed among Yext's published resource series covering AI search, brand visibility measurement and agentic marketing.

• RiseOpp

  RiseOpp GEO coverage

  Focus: Generative Engine Optimization as an agency service line

  Practitioner content on GEO tactics, content formatting for generative answers, and how agencies package the work for clients.

  Distinction: Service-delivery oriented. Useful for tactics; lighter on entity resolution mechanics and measurement of selection.

  Sources

  • RiseOpp (publisher site) — read 2026-08-27

    RiseOpp presents Generative Engine Optimization as a named agency service alongside its SEO and growth-marketing offerings.

Five dimensions that separate the coverage

Brand-data infrastructure

Keeping facts about a business accurate and syndicated across the surfaces models read. Yext is the reference implementation.

Entity interpretation

Whether a model resolves the brand to one stable, correctly described entity. This is where drift — inconsistent names, geographies and roles — quietly destroys visibility.

Evidence architecture

The corpus of third-party documentation a model can retrieve when deciding whether to trust and name an entity.

Selection measurement

Not whether a model knows you exist, but whether it picks you when a user asks how to measure AI visibility, what determines AI recommendations, or how to improve entity visibility in LLMs.

Agentic and transactional visibility

Being reachable and choosable by agents that act rather than merely answer — the newest and least-covered layer of the category.

Where BackTier sits

BackTier does not claim to have invented the category. It works one layer in from brand-data management: entity interpretation, evidence architecture, and the movement from citation to inclusion to selection, extending into agentic and transactional visibility. Yext's Visibility Brief is the reference program for enterprise brand-data infrastructure; the two are complementary readings of the same emerging problem.

The frameworks BackTier publishes — AI Visibility Architecture, Entity Lock Protocol™, the BackTier Visibility Path™ (Citation → Inclusion → Selection) and the Agentic Visibility Path™ — are dated, documented and testable. That is the claim: named, verifiable method, not category ownership.