AI, GEO, and PR: Building Trustworthy Healthcare Communications

How AI Is Changing Healthcare Communications

Artificial intelligence is changing how people find and trust health information. On PR's Top Pros Talk, Ivan Ruiz, Partner, Digital Health and Strategy at FINN Partners, speaks with Doug Simon, CEO of D S Simon Media, about what this means for healthcare PR and communications teams.

Audiences want information specific to their needs in the moment. Doug asks whether AI makes it easier to get answers interactively-and whether brands must be part of that exchange. Ivan is clear: communicators have to counter inaccuracies with credible content. "If the noise and the misinformation are louder than the truth, unfortunately, that's what AI is going to gravitate to. And so, we need to make sure that we're out there playing offense for our clients."

Why PR matters more in an AI-driven environment

High-quality, reference-rich content is the input AI systems use to reply to people's questions. Earned media adds authority and reach, and it feeds the sources that AI systems scan. As Ivan notes, PR has renewed strategic weight: "PR really has a front seat in this AI world because from a publication perspective, we're working really, really hard to ensure that these credible perspectives are being broadcast."

Whether through national outlets, local media, or online coverage, those stories become the backbone of what models surface.

GEO and the new distribution reality

AI and GEO (generative engine optimization) change distribution. The goal is clear signals over noise: structure, clarity, and strong sourcing so models can parse and present your message accurately. This builds trust with people and increases the odds your information is featured in AI answers.

Practical steps for healthcare communicators

• Publish reference-rich content: Cite primary sources, guidelines, and peer-reviewed research. This improves trust and gives AI systems clear signals. For context on tackling misinformation, see WHO's infodemic management.
• Structure for machines and humans: Use clear headlines, summaries, bulleted key points, FAQs, and concise takeaways. Add schema where appropriate to improve parsing by AI and search systems. Reference: Google's structured data guidance.
• Prioritize earned media: Pitch credible experts and clinical voices. Broadcast segments and reputable placements act as durable signals that models index.
• Local and national reach: Balance market-level stories with national narratives. Local relevance drives community trust; national coverage validates expertise.
• Maintain source-of-truth pages: Keep evergreen pages updated (conditions, treatments, safety, access). Link out to your own pages from media placements and vice versa.
• Monitor AI answers: Regularly check how major models answer core questions about your organization and key topics. Identify gaps, correct inaccuracies, and publish clarifications.
• Institutionalize AI: Set governance, workflows, and training. Define review standards for clinical claims, legal guardrails, and update cycles. As Ivan puts it, "You can't just talk about AI. You're either embracing it and it's part of the organization's culture and their processes, or it's not."

What good looks like

• Clear problem statement, plain language, and a short summary at the top.
• Evidence-backed claims with links to primary sources.
• Consistent expert quotes and on-record spokespeople.
• Structured markup and clean site architecture.
• Distribution through earned media, owned channels, and partner networks.

Level up your team

If your team is building AI literacy across roles, explore practical learning paths by function here: AI courses by job.

View all of the interviews in the "PR's Top Pros Talk" series. Interested in taking part? Contact Doug Simon at dougs@dssimonmedia.com.