Generative Pulse: Earned Media Consistently Drives AI Citations, Holding at 84%

Third What Is AI Reading? Report Analyzes More Than 25 Million Links; Confirms Consistent Citation Patterns Across ChatGPT, Claude and Gemini

• Earned media drives 84% of AI citations across ChatGPT, Claude and Gemini
• This pattern has remained consistent across three reports since July 2025
• Paid and advertorial content accounts for just 0.3% of citations
• Journalism represents 27% of all cited sources
• Analysis is based on more than 25 million links across 17 industries
• Citation behavior varies by platform, with each AI system showing distinct sourcing patterns

Miami, May 07, 2026 (GLOBE NEWSWIRE) -- - Muck Rack, the AI communications platform and company behind Generative Pulse, today released its May 2026 edition of What Is AI Reading?, the third installment of its ongoing study tracking how generative AI systems cite sources across ChatGPT, Claude and Gemini. Based on analysis of more than 25 million links, the latest findings reinforce what the July 2025 and December 2025 editions first established: earned media drives the overwhelming majority of AI citations, and that pattern has held consistent across every edition of the study.

The findings come as communications and marketing leaders face growing pressure to understand how AI answers are replacing traditional search results. When consumers ask an AI about a product, a competitor, or an industry trend, what those systems say, and what they cite, is shaped almost entirely by editorial and earned coverage, not paid placements.

Core Citation Patterns Have Remained Consistent Since July 2025

Earned media accounts for 84% of all AI citations in the May 2026 edition, including journalism, academic research, government sources, encyclopedic sites, and third-party corporate content. Paid and advertorial content represents just 0.3% of citations. Journalism alone accounts for 27% of all links cited. Both figures have remained consistent across all three editions of the study: earned media has ranged from 82% to 89% and journalism from 25% to 27% since July 2025, suggesting these are consistent patterns and not tied to a particular model update or time period.

The study found that the type of question asked significantly influences what gets cited. Industry trend queries drive journalism citations at more than double the rate of how-to questions. Press releases appear almost exclusively in industry trend responses and at a rate 3.5 times higher than in best-of queries. For PR and marketing teams, what consumers ask AI matters as much as what gets published. Questions about products, categories, and competitors all influence which content surfaces.

Each AI Provider Operates as a Distinct Information Environment

ChatGPT cites sources in 96% of responses but averages just five citations per response. Gemini cites in 82% of responses with an average of 8. Claude is the most selective, providing citations in 55% of responses, but averages 13 sources when it does. ChatGPT's most cited domain is Wikipedia; Claude's is PubMed Central; Gemini's is Reddit.

Journalism citations are distributed across more than 20,000 distinct outlets, with one notable exception. Axios appears in ChatGPT's top three cited domains across 13 of 17 industries, the only journalism outlet to achieve that across any provider. Neither the New York Times nor Reuters appears in the top three for any industry. For PR teams, the outlets that drive AI visibility depend heavily on which AI platform their audience uses.

Recency also plays a role. More than half of journalism citations come from articles published within the past 12 months, with citation volume dropping sharply after the first six months following publication.

"Three editions in, the data keeps telling the same story: earned media is what AI trusts. For communications teams, that is validation that the work they do to earn coverage in the right outlets has real consequences beyond traditional metrics,” said Greg Galant, co-founder and CEO of Muck Rack. "This is also a signal for marketing leaders who are building content and media strategies. If your brand is not showing up in the media coverage AI is reading, you are not showing up in the answers AI is giving. That is a visibility problem with real business consequences."

About What is AI Reading? 

What Is AI Reading? is published by Muck Rack's Generative Pulse team and examines how generative AI systems cite sources when responding to realistic consumer prompts. The May edition analyzed more than 25 million links from responses generated by ChatGPT, Claude and Gemini across 17 industries and multiple query types. Because generative AI systems evolve quickly, citation behavior may shift as models are updated or retrained. The full report and methodology are available at generativepulse.ai/report

About Generative Pulse

Generative Pulse helps PR and communications teams understand and influence how AI platforms describe their brands. Built around the concept of Generative Engine Optimization (GEO), it shows where brands appear in AI-generated responses, which journalists and outlets shape those answers, and how visibility compares to competitors across major large language models. Generative Pulse is integrated into Muck Rack's platform and combines AI insights with journalist data and workflow tools.

About Muck Rack

Muck Rack is the AI communications platform where trusted data, human expertise, and embedded intelligence come together to drive clarity, speed and impact. Thousands of companies turn to Muck Rack to make sense of the media conversation around them and understand how their brand shows up in the news and in AI-generated answers. Muck Rack combines global media monitoring, Generative Engine Optimization (GEO) insights, social listening, trusted media data, AI automation, and analyst advisory to help organizations manage reputation, act quickly, and prove their impact across the PR workflow. Thousands of journalists also use Muck Rack’s free tools to showcase their work and analyze the news. Learn more at muckrack.com. 

Linda Zebian
linda@muckrack.com

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