AI in Healthcare Marketing: Content & UX 

This article is the first in a new blog series exploring the hype and impact of artificial intelligence in healthcare marketing and digital experiences. Stay tuned to the Geonetric blog for future posts covering AI in development, strategy, and more. 

Artificial intelligence is everywhere right now. It’s dominating LinkedIn feeds, conference agendas, and leadership conversations. For healthcare marketers, this buzz can create pressure to move fast, even when the rules, risks, and best practices aren’t fully clear. 

When it comes to using AI in healthcare marketing for content and user experience purposes, at Geonetric, we’re taking a more measured approach. Not because we’re resistant to AI, but because healthcare requires a level of trust, responsibility, and human understanding that automation can’t — and shouldn’t — replace. 

To kick off our AI blog series, we’re taking a look at how we’re seeing AI impacting healthcare content creation today, where it may prove useful for your organization, and where our team recommends caution. 

This isn’t a definitive roadmap. It’s a snapshot of what we’re seeing right now, how we predict we’ll be talking about AI in healthcare marketing in the coming months,  and why the human touch still matters. 

How AI Is (and Isn’t) Changing Our Healthcare Content Creation  

AI has absolutely started to influence content workflows, but where we’re seeing the most value isn’t in asking AI to actually create an entire piece of healthcare content. It’s earlier in the process, where AI can assist in brainstorming article ideas, generating topic lists for content hubs, or identifying related subtopics a team may not have considered yet. 

AI can also be useful for synthesizing large volumes of information, like survey results, to help content teams quickly spot trends and common themes. 

That said, AI has not replaced our actual content writing process, and at this point, we wouldn’t want it to. The most effective healthcare content still relies on person-driven discovery: talking to stakeholders, understanding patient needs, and translating complex medical information with empathy, clarity, and a knowledge of your local audience.  

In fact, trying to hand off discovery-driven thinking to AI often creates more work, not less. The time required to prompt, refine, validate, and edit outputs is often longer than it would take your team to write the content themselves. 

At the heart of the content creation process, we still want actual people interacting with other people and creating experiences that help those people get the healthcare they need. At this stage, asking AI to handle that process eliminates the human connection that we find necessary to craft valuable, helpful digital content. 

Ethical Gray Areas of AI in Healthcare Marketing 

One of the biggest reasons our team has been cautious about pursuing AI content generation is the lack of clarity around copyright and plagiarism. Current regulations and legal guidance are still evolving, particularly regarding ownership of AI-generated content. For healthcare organizations that value original, proprietary content or that need to protect intellectual property, this uncertainty matters. 

There’s also the risk of unknowingly publishing content that closely mirrors or pulls from copyrighted sources. Even when AI tools don’t cite their references, the material they generate may be derived from protected content. In healthcare, where accuracy, credibility, and trust are non-negotiable, that’s a risk we’re not willing to take lightly. 

Tools that claim to detect whether content was written using AI aren’t a reliable solution either. They can produce false positives (one recent test plugged the Gettysburg Address into an AI detector, which determined the famous speech — written more than 150 years before the advent of AI — was 96.4% AI generated), and they don’t address the underlying issue: content should be something your organization can confidently stand behind, regardless of how it was created. 

AI’s Impact on Search & Findability 

Search engines and users alike continue to reward content that feels human, helpful, and relevant. That hasn’t changed with the rise of AI. 

We’re seeing a growing emphasis on localization in healthcare marketing — content that speaks directly to a community, references local care locations, highlights physicians, and connects to real patient stories. AI tools struggle here. They don’t understand your organization’s culture, your audience’s concerns, or the nuances of your local market the way your internal teams do. 

AI as a Tool for UX and Research 

From a user experience standpoint, again, we’re seeing AI function best as a support tool, but not a replacement for real, people-driven work. 

AI can help generate usability testing questions or spark ideas when teams are deep in wireframes and navigation decisions. It can also help organize and synthesize research inputs when working with large data sets. 

What we don’t support is replacing user research with AI-driven testing. Healthcare websites are built for humans, not bots. Automated testing introduces bias, unreliable data, and “hallucinated” insights that can easily lead teams in the wrong direction. Real users provide context, emotion, and intent — things AI simply can’t replicate. 

How about HIPAA? 

When discussing new digital marketing technology and healthcare, questions about HIPAA compliance and privacy are never far behind. In the content world, we see HIPAA concerns come up most often with AI-powered chatbots. 

While chatbots can be helpful for wayfinding or answering basic questions, users often treat them like real people, especially in moments of stress. That creates risk for your organization. 

Patients may inadvertently share personal health information without realizing how the chatbot handles, stores, or analyzes that data. For now, we recommend using AI cautiously for marketing and operational tasks, keeping any sensitive information out of AI tools, and clearly setting expectations for how chatbots should (and should not) be used. 

If chatbots are deployed, organizations should actively monitor inputs, remove unnecessary data, and include clear language that discourages sharing personal health information. 

Our Biggest Recommendation: Take Your Time 

Whether your healthcare marketing team is eager to adopt AI or feeling pressured by leadership to explore it, our advice is the same: slow down. 

There’s no prize for adopting AI first, and no penalty for being thoughtful. The tools and digital landscape will continue to evolve. Some will go out of business, others will be absorbed into larger platforms. There’s little benefit in committing too quickly to a solution before the landscape stabilizes. 

Internally, we’ve encouraged teams to experiment at their own pace, share what’s working, and be honest about when AI adds friction instead of removing it.  

At the end of the day, healthcare marketing is still about connecting with people. AI can help with task work and structure, but it can’t replace empathy, experience, or accountability. The most effective use of AI is the one that supports your organization in doing what it does best: providing the people in your community with the care they need, when they need it. 

Have questions about using AI in healthcare marketing? Want a team of human content marketers to take a look at how your organization can improve its content strategy? Reach out to Geonetric today!