I’d never met this doctor before. Within minutes, he’d already made an impression. 

Before the appointment began, he looked up and said he believed in patient advocacy – and that he was using AI to help make it happen. He asked if he could use AI to transcribe the visit, walked me through the privacy policy, and noted that most patients want the transcription so they can advocate for themselves. 

It was a small moment, but it pointed to something much bigger: Healthcare professionals (HCPs) are beginning to trust AI tools and AI-generated information sources. 

I’m reminded of this during my day-to-day work with pharma and healthcare clients at Fullintel. That’s because the growing trust of AI among HCPs is fundamentally changing how pharmaceutical, medical, and other healthcare companies need to think about earned media, content strategy, and engagement.

This blog post will demonstrate the growing momentum of AI in healthcare, and how companies can capitalize on healthcare AI communications in their earned media strategy. 

Trust in AI Among Physicians Up 80% Year-Over-Year

Momentum around AI healthcare professional engagement is real and growing: 

• The American Medical Association (AMA) says nearly 70% of physicians reported the use of AI in their job in 2024. That’s a nearly 80% increase from the year prior. 
• A recent study showed that nearly 90% of U.S. clinicians agree that generative AI is useful in patient care, that nearly 93% are confident in its future usefulness, and that more than 70% support broader AI adoption (as long as humans stay in the loop). 

That’s despite the risks involved in the use of AI, especially in life-or-death situations: A recent report from the government of Ontario, Canada, says AI scribe solutions for healthcare are “not evaluated adequately” and sometimes “fabricate information.” 

That’s a huge cause for concern, says Dr. Mahmud Omar, a research scientist at the Mount Sinai Medical Center, in Live Science. “The core problem is that LLMs don’t fail the way doctors fail,” he explains. “A doctor who’s unsure will pause, hedge, order another test. An LLM delivers the wrong answer with the exact same confidence as the right one.”

Still, there’s no denying that generative AI in most medical practices is here to stay, and that it has been widely adopted to improve efficiency across note-taking, charting, and other functions. 

While it’s hard to pin down what’s driving this increase in HCP trust, it’s likely due to a combination of factors such as improved AI models and growing pressures to increase efficiency to meet demand. It’s also likely that many physicians are what you’d call “early adopters” in the technology adoption life cycle. 

Why This Shift Matters for Healthcare and Pharma Communicators

No matter the reasons for increased AI adoption, the growing trust HCPs place in AI tools has a direct implication for pharma and healthcare communicators: The content you produce – and the coverage you earn – now feeds directly into the information doctors use to make decisions.

That’s because when a physician turns to AI for a quick consult, the engine surfaces a combination of news articles, trade publications, and even content from consumer-facing platforms like Reddit and YouTube. 

• A well-placed news article or a strong piece of earned media (in outlets that allow their content to be used for AI training) now has a better chance of reaching a physician during their professional research, thanks to generative AI search. 
• At the same time, patients using AI to research their conditions are being exposed to trade publications they may have never stumbled across on their own. 

HCPs now encounter patient sentiment and social conversations alongside the clinical data they’re used to seeing, giving them a richer, more grounded perspective. And patients will likely benefit from science-backed information entering their feed. 

I think that’s a healthy exchange. For those in pharmaceutical AI marketing and communications, it’s both a challenge and an opportunity. And the brands that will win are those with content strategies that work for both audiences, because AI is already serving it to both.

Most importantly, this is why pharma and other healthcare communicators need to care about healthcare-related news coverage: Because those articles get picked up by AI, and doctors then consult those articles. According to recent Fullintel-UConn research, one of the most highly cited sources in AI engines is highly credible sources – like news articles.

Best Practices for Reaching HCPs (and Patients) in the Age of AI

At the end of the day, pharma and healthcare communicators want to get in front of providers. You want to show them a new and innovative technology solution or treatment they might not be aware of. 

(And by the way, there’s a lot they’re not aware of: While many HCPs always keep learning through seminars and conferences, others don’t as much – even though the world is constantly changing).

That means that as AI becomes a primary research tool for clinicians, the content pharma and healthcare communicators publish is now more vital than ever. According to Fullintel research, news and educational articles are among the most frequently cited sources in AI-generated responses, making media relations a critical communications strategy. 

Given this context, here’s how to ensure your content performs:

1. 1. Prioritize credibility signals AI engines reward: Because AI systems surface content with strong authority markers, it’s important to cite original research, peer-reviewed data, clinical studies, and named experts in your content. Ensure all content you produce is properly structured for AI consumption with clear headers, definitions, and factual claims. 
   2. Earn coverage in indexed, high-credibility outlets: This includes trade publications and reputable news sites. Prioritize open-access trade publications over paywalled outlets – you’re going to get a lot more bang for your buck with publications that are both informative and frequently cited by AI. 
   3. Use human visuals: Articles featuring human visuals generate longer engagement time, which improves recall and conscious influence. Our research shows machines also cite articles with human visuals more frequently. 
   4. Format content to answer questions directly: AI engines are built to answer prompts, so content structured around clear questions and direct answers gets surfaced and cited far more often. Use Q&As, bullet points, and explicit headers that signal your content answers a specific question. 
   5. Build trust through transparency: Clinicians are trained skeptics. Disclose data sources, methodology, and limitations, and avoid promotional language in earned content. 
   6. Write for both audiences: Assume your trade content will reach patients and your consumer content will reach clinicians. Avoid siloed messaging strategies and prioritize clarity and scientific accuracy across all content.

The Importance of Advanced Measurement Methodologies

In the new age of AI use and information sharing across audiences, it’s important to apply a Media Impact Score approach when creating content or measuring earned content. Fullintel’s Media Impact Score (MIS) was built to predict how likely a piece of news coverage is to influence a human audience, and it turns out the same quality signals that influence people also influence machines. 

The MIS evaluates factors like brand prominence, outlet authority, and spokesperson inclusion to score content based on predicted impact. This approach mirrors AMEC’s Barcelona Principles, which advocate for both qualitative and quantitative measures in communications measurement. 

Combined with Fullintel’s Trust Score, which was developed under a research partnership with UConn’s Dr. Tyler Page, you can also measure the credibility signals embedded in a piece of content. These signals include ability (or competence in a specific domain), benevolence (a desire to do good to your audience), and integrity (adherence to ethical and professional principles). 

These are the same markers that AI engines evaluate when deciding which content to retrieve and surface in a response. A high Trust Score means AI models are more likely to treat it as a reliable source worth citing. For pharma and healthcare communicators, that distinction is critical.

One Effective Change Healthcare PR Teams Can Make Right Now – and What It All Means for Your Strategy

What’s one of the simplest but most overlooked things PR teams can do right now to get more AI visibility? It’s simple: put your topic in the headline. 

Whether you’re pitching media, publishing a blog, or distributing a release on the wire, the headline needs to: 

• Directly address the question your content answers.
• Be framed around the patient or clinician benefit, not just a product announcement. 
• Lead with the condition, the benefit, or the patient’s needs.

When it comes to AI content strategy, start by auditing your existing coverage for the quality signals AI engines prioritize – such as expert attribution, open access, question-driven headlines, and credible sourcing. Invest in original research and data, which are frequently cited content types by AI models. And start monitoring whether and how AI tools are citing your earned coverage.

The most effective communications programs will integrate human and AI audience metrics, build content strategies that speak to clinicians and patients simultaneously, and treat earned media as a direct input into AI search engines.