Fullintel-UConn study on AI engine citations shows the value of pitching your message to journalists and other credible outlets.

If AI is rewriting how audiences discover information, it has also significantly changed how the communications professionals we work with measure impact. Dashboards, sentiment charts, and campaign recaps using traditional media metrics simply can’t sufficiently demonstrate the value of PR in the AI era. This has left comms teams and executives wondering: Which media placements – and which sources – actually shape the information AI models surface to stakeholders?

Senior communications leaders need to re-learn how to measure value in a rapidly changing world. The pressure is real. Executives want clarity. And according to a recent Fullintel-University of Connecticut (UConn) study on media citations in AI engines, journalism’s core strengths – including credibility, structure, and sourcing – are quietly determining which stories make it into the AI ecosystem.

This article explains why journalism is central to AI visibility, how that can help reshape your PR strategy, and how you can measure the impact of credible news in 2026.

The Surprising Dominance of Journalism in AI Citations

The Fullintel-UConn study, to be presented at the International Public Relations Research Conference (IPRRC) in March, examined weight loss drug-related content cited in AI search. It showed that – far from being made irrelevant by AI – journalism has taken on a new importance in the quest for brand visibility.

That’s because, across thousands of outputs we analyzed, one pattern stood out: AI models cite “credible sources” – many of which are journalistic outlets or websites that use journalistic practices – more than any other type of content.

• 47% of all citations in AI responses came from journalistic sources, like third-party news and other informational websites
• Another 48% of citations came from a combination of corporate, university, health network, and association websites

While it’s easy to assume that AI models treat all content equally, this study shows they don’t: The models consistently favor sources that feature credibly sourced reporting, structured writing, and strong editorial rigor.

Which Publications AI Models Trust Most

The top news sources cited in AI engines from our health-focused study included medicalnewstoday.com, healthline.com, and drugs.com. The prominence of these and other sites in the study aligns with research showing that AI models rely more heavily on sources associated with high trust, reader credibility, and rigorous editorial standards.

These findings also reinforce the communications principles emphasized by bodies like the Institute for Public Relations (IPR) – transparency, attribution, and evidence-based reporting.

For PR teams, this means that being covered in outlets deemed credible news by AI models increases your organization’s visibility in AI-generated responses.

Why Credible News Beats Other Content Types: E-E-A-T

AI models are trained to favor experience, expertise, authoritativeness, and trustworthiness (E-E-A-T). Journalism naturally aligns with these signals because it offers:

• Clear author attribution
• Sourcing and quotes
• Fact-based reporting
• Editorial review
• Transparent updates and corrections

Journalistic pieces also use standardized formats, such as:

• The inverted pyramid style of writing
• Clear subheadings
• Datelines
• Attributed quotes

This helps AI models identify what happened, who said it, and why it matters – making high-quality news easily readable for retrieval-augmented generation (RAG) models.

Other studies have shown similar findings to the Fullintel-UConn study, with a recent MuckRack report showing that 27 percent of links in AI engines were from the news media. The rest were an assortment of third-party websites and owned media such as government/NGO, corporate blogs, academic research, and press release sources. 

Other highlights of the MuckRack report:

• More than 95% of citations were unpaid media
• More than 89% of links cited were earned media
• Recency was important, with more than half of OpenAI’s citations published in the past 12 months

The study indicated that the most common outlets cited across ChatGPT, Claude, and Gemini were high-authority news sites such as Reuters, the AP, and the Financial Times. 

The Three Tiers of News Sources in AI Training Data

One thing I tell the comms professionals I work with is that outlet tiering is just as important in the age of AI as it has ever been. That’s because not all news sources appear equally in AI systems. 

AI systems prioritize “credible” news sources that report using fact-based, objective methods. But there are other factors to consider, such as whether the outlet is used by models for training.

Based on licensing disclosures and observed model behavior, PR teams can tier credible media outlets based on the following criteria:

Tier 1: Publishers With Licensing Deals

Dozens of publishers – from Gannett to News Corp., Reuters, and Sky News – have signed licensing deals with various generative AI companies. This gives these outlets a built-in visibility advantage because their content is readily available for training and retrieval.

Tier 2: Freely Accessible, High-Authority Sources

While a format licensing deal may not exist, these outlets typically feed AI models to a high degree based on their highly crawlable, clean, and widely-indexed outputs. Many digital-native brands fall into this category.

Tier 3: Blocked or Restricted Publishers

Other publications restrict AI crawlers via robots.txt, sit behind dynamic paywalls, provide limited access to archives, or are even sometimes involved in ongoing litigation against AI companies. While many well-respected outlets fall into this category, their presence is limited in AI outputs based on the situation above.

Why This Matters

Some media outlets allow AI models to use their content for training, and others don’t. Coverage in Tier 1 and Tier 2 outlets disproportionately shapes what AI models reveal to audiences – and what your stakeholders may see in generative search.

That’s important because of the growing importance of AI search when it comes to engaging your audience. Consumers are increasingly getting their information from AI models: So-called “zero click” searches are real, with around 60 percent of searches not clicking through to source websites.  

What This Means for Your Media Relations Strategy

There are three main things you can do right now to tailor your media relations strategy to the AI era: 

1. Prioritize Placements in AI-Friendly Publications

Tier your target media outlets based on which are the most AI-friendly. Tier 1 and Tier 2 outlets must play a more strategic role in PR planning because they appear more consistently in AI citations.

This does not mean abandoning specialized or local media – only that PR leaders must be intentional about placing stories where AI systems are most likely to see them.

2. Optimize Your Owned Media for AI Citation

Owned content has a much better chance of being “understood” by AI models – and reporters, for that matter – if you follow a few simple guidelines. 

• Use quote-heavy releases that offer spokespeople with clear credentials
• Format with  tables, headings, bullet lists, and other organization tools to make information more easily scannable
• Include recency markers and context blocks
• Avoid jargon that obscures key messages
  

3. Move Beyond AVE and Traditional Metrics

Advertising value equivalency (AVE) has long been rejected by industry leaders as a measure of communication performance. The growing importance of AI search – and the momentum of zero-click searches, where consumers of information don’t even leave the engine during the search – further underscores its irrelevance.

Instead of trying to arbitrarily measure the monetary value of coverage based on advertising rates that probably aren’t even accurate, the most valuable earned media is increasingly that which is cited by AI models and that impacts the information returned in those models.

Measuring the AI Advantage in Your PR Programs Through Journalism

To truly take advantage of journalism’s impact on brand visibility in the AI era, PR teams need new measurement practices specifically tailored to AI citations.

Track Which Outlets Drive Your AI Citations

Monitoring coverage using traditional metrics like volume, sentiment, and share of voice still provides value, but should be paired with newer metrics around AI citation volumes of your brand’s appearances in AI-friendly outlets (Tiers 1 and 2 from the earlier section). 

This creates a new layer of visibility: your brand’s AI media footprint.

Apply a Media Impact Score Approach

Fullintel’s Media Impact Score (MIS) uses quality metrics to help predict how likely news coverage is to influence audiences. Interestingly, these same quality metrics can be used to predict which content will have the most impact on AI models.

MIS looks at variables such as brand prominence, outlet tier/authority, spokesperson inclusion, and other factors to score media based on its predicted impact. This aligns with AMEC’s guidance to consider qualitative and quantitative measures in comms measurement programs. 

Educate Your Executive Team

We won’t dispute one thing about AVE and impressions numbers: At first glance and at face value, those large numbers can seem impressive – especially when they include a dollar sign in front.

But chasing large AVE and impressions numbers has become increasingly meaningless in the age of AI search. That’s why it’s important to educate your executive team on why credible journalism, not volume, drives influence.

PR’s Most Valuable Asset in the AI Era: Journalism

Journalistic media is under threat from multiple directions, from the economic sustainability of legacy outlets to criticism around its objectivity and accuracy. However, far from eroding journalism’s standing, AI hasn’t diminished the value of earned media in credible, objective news sources. Instead, it has clarified it – and even elevated its importance. 

That’s because credible journalism is now one of the strongest predictors of AI visibility, narrative influence, and stakeholder understanding. 

When PR teams work with AI-friendly journalistic sources as a core part of their comms strategy, they strengthen reputation, trust, and the organization’s future discoverability.

Five Actions PR Leaders Can Take This Quarter

1. Map your coverage across Tier 1, Tier 2, and Tier 3 media
2. Identify the top AI-cited publications in your industry
3. Prioritize placements in outlets that enhance AI visibility
4. Use a quality metric like Media Impact Score to predict which coverage is more likely to drive AI search outcomes
5. Educate executives on the importance of quality citations in credible sources
   

The future of PR belongs to leaders who understand how AI evaluates information – and who place their stories where AI is already looking.