This article explores how AI answer engines like ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews build responses, detailing the two main modes (trained knowledge and live retrieval), the six steps from question to answer, and the five factors that make a source rank highly. It also explains what determines which entities are named in an AI answer and offers five key takeaways for communications professionals on how to influence AI outputs.
AI Communications is the discipline of building authority across AI answer engines like ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews. This article explains why founders need a distinct AI Communications strategy, separate from their company's, to manage their personal reputation and influence the information presented to investors, recruits, journalists, and board members.
A thought experiment poses the scenario of a brand disappearing from ChatGPT, highlighting the critical need for AI Communications. This article outlines what happens when a brand isn't visible to AI, what can be done immediately, what should have been done six months ago, and three crucial next steps to build AI visibility infrastructure and avoid a crisis.
The article introduces AI Communications, a discipline that redefines the traditional tier-one media list. It explains how AI engine analysis measures actual publication authority, replacing outdated assumptions with data-driven insights. This new approach combines public relations, Generative Engine Optimization (GEO), and AI-visibility research to influence answers from AI platforms like ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews. The article details the shortcomings of the old media list, which was based on inherited assumptions, and outlines how AI engines reveal a different landscape of influential sources. It highlights new patterns, such as the importance of "ignored trade" publications and older interviews, and discusses operational changes for PR professionals. The piece concludes by emphasizing that the new tier-one list is a dynamic, research-driven output, customized per category and client, and crucial for effective modern PR strategies.
The AI Communications Stack is a seven-layer framework crucial for entities to appear in AI-generated answers. Most AI visibility issues stem from a broken layer, not media problems. This stack, from Identity to Defense, ensures coherent and consistent presence, with "Citation Share" as the key metric across all layers.
Citation Share is the new metric defining AI Communications, measuring an entity's presence in AI-generated answers. This article explains how It measures a brand's inclusion in AI answers across major engines, why it's replacing traditional market share, and how communications teams can use it to drive strategy and investment.
AI Communications is a new discipline focused on building authority in AI answer engines like ChatGPT, Claude, and Gemini. It combines public relations, Generative Engine Optimization (GEO), and AI-visibility research to influence the answers people receive from these platforms. This article defines AI Communications, explains its core components—including the seven-layer AI Communications Stack—and differentiates it from traditional PR, SEO, and GEO. It also introduces "Citation Share" as the key metric for measuring success in this evolving field.
5W research across 125 brands and five industries shows the AI leaderboard doesn't match the market. Delta leads airlines; American is the largest carrier and ranks fifth. Citation Share is the new market share — and the gap is wider than most executives realize.
Healthcare GEO is the practice of building visibility for healthcare, pharmaceutical, biotech, device, payer, and hospital brands inside the answers generated by AI engines. This field guide defines the discipline, explains why it exists, and lays out how it works.
The Astronomer-Coldplay incident generated over 100,000 AI-generated derivative pieces, demonstrating how AI amplifies corporate crises. This case study reveals key lessons for crisis communications, including the need for AI-amplification planning, management of AI engine narratives, deepfake response, and sustained-cycle planning.
