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AI + content:
A comprehensive guide for healthcare marketers

Healthcare marketers aren’t strangers to major industry disruptors. AI, however, has the potential to revolutionize how we do our work and can offer a competitive edge for brands — but only when you take a thoughtful (versus reactionary) approach.

The state of AI in healthcare marketing

Healthcare has traditionally been slow to adopt innovation. But today’s consumers are digitally savvy, expect personalization, and want timely, empathetic interactions. Marketers are under pressure to deliver more with fewer resources. AI bridges that gap.

What AI enables for healthcare marketers:

  • Smarter audience segmentation: Identify micro-segments and target with precision
  • Personalized patient journeys: Deliver tailored messages in real time
  • Faster campaign execution: Automate CRM workflows and multichannel delivery
  • Deeper insight: Analyze sentiment, behavior and content performance

Examples in acton:

  • Automating appointment reminders with natural language
  • Personalizing a health system website based on visitor behavior
  • Using sentiment analysis to adjust messaging around sensitive health topics

In short, AI enables healthcare marketers to work smarter, not harder, and connect more meaningfully with target users.

Healthcare marketers are poised to lead the AI movement. With communication instincts, deep audience insight, and the ability to turn complexity into clarity, we’re natural prompters — and innately adaptable. This is our moment to step forward with practical use cases that elevate performance, simplify workflows, and model what smart, human-centered AI adoption can look like.

Diane Hammons, director, WG Content

— Diane Hammons, director of digital engagement, WG Content

Your AI adoption journey

Getting started with AI in healthcare marketing can feel overwhelming. New tools and hot takes pop up daily, making it hard to separate signal from noise. Kick off your team’s AI content journey by starting simple, building momentum and refining as you go.

Illustration showing the the 3 steps to AI adoption
Illustration showing the three steps to AI adoption.

Step 1: Get informed and find your community

  • Identify a few credible sources to follow for updates (instead of trying to read everything).
  • Join or build an AI peer group (inside and outside your organization) to share lessons, successes and risks.
  • Look for agents of change internally: colleagues who are curious and motivated to test AI responsibly.

Step 2: Build momentum with leadership buy-in

  • Form an AI working group or committee with clear goals.
  • Develop a simple business case with:
    • Pain points AI could help solve (time savings, cost reduction, personalization, scalability)
    • Success measures (faster analysis, improved brand consistency, etc.)
  • Keep leadership engaged at key checkpoints to reinforce trust and confidence.

Step 3: Start small, test and refine

  • Begin with everyday tools (spell-check, scheduling apps, SEO helpers) before scaling.
  • Experiment incrementally: test small campaigns, learn from results, and share wins.
  • Train your AI partner with clear, specific prompts. Think of a prompt as your creative brief.
  • Refine results by adding details like format, tone, audience and examples.

Be aware of potential AI pitfalls such as:

  • Bias
  • Inaccuracies (“hallucinations”)
  • Overall impact on the writing process
  • Potential plagiarism or murky copyright infringement
  • Privacy concerns (especially around protected health information or proprietary information)
  • Sources and timelines of information

AI and content marketing

Generative AI tools like ChatGPT, Claude, or Perplexity can act as powerful assistants in the content creation process. Used strategically, AI helps teams save time, spark new ideas and streamline production workflows.

How AI supports content marketing

You can use AI for:

  • Creation: Drafting short-form content like meta descriptions, email subject lines and social media posts.
  • Distribution: Helping tailor messaging for different channels and formats.
  • Ideation: Sparking fresh ideas for campaigns, blogs and content series.
  • Maintenance: Suggesting updates to keep existing content accurate and relevant.
  • Organization: Structuring large volumes of source material for easier use.
  • Outlines: Drafting content frameworks for articles, case studies or whitepapers.
  • Performance analysis: Identifying trends and insights from analytics data.
  • Repurposing: Reframing content into new formats such as infographics, scripts or newsletters.
  • Research: Gathering background information and surfacing key points.
  • Summaries: Condensing long-form content into scannable takeaways.

Use cases for AI writing assistants

AI writing assistants are especially helpful for:

  • Brainstorming and breaking through “blank-page syndrome”
  • Generating interview questions
  • Organizing and summarizing source material
  • Spotting content gaps across websites or campaigns

Just remember to leave writing custom content to humans. That’s because authentic healthcare content should draw from natural, human experiences — something generative AI tools simply can’t do.

There are a lot of guardrails you’d want to put in place around using synthetic users to help make decisions about your user experience and your content, but there’s a lot of promise around using AI for enhanced user testing.

Stella Hart, content strategist, WG Content

— Stella Hart, content strategist, WG Content

The basics of prompting

Like healthcare marketing writing itself, prompting in AI is grounded in clear, plain language. It’s asking questions of AI and giving it the framework it needs to complete an assignment. When you’re prompting an AI tool, you should give it:

  • The role you want it to take when responding
  • Your goal (what you want to accomplish)
  • The context it needs to evaluate your request
  • Any guidelines, such as health literacy
  • An example (any do’s or don’ts)
  • The tone, such as friendly or professional
  • The output (exactly what you’re expecting from it)
  • Any limitations, such as avoiding jargon or slang
Illustration showing the 4 types of prompting
Illustration showing four types of prompting.

Prompt chaining

This technique uses a series of prompts to guide a generative AI tool through a multi-step task. With prompt chaining, let your stream of consciousness flow.

Healthcare example:

  • Your prompt: List five engaging topic ideas for articles promoting preventive screenings, targeting busy working parents ages 30 to 45. 
  • When the tool gives you five ideas, you choose one and further refine your next prompt: Using number 3, outline an engaging and conversational article that includes an intro, three key sections with examples of specific screenings and a motivating conclusion. 
  • Or, you can input an article you’ve written and ask the tool to provide five Facebook post ideas based on it. If none fit the bill, your next prompt could tell the tool to try again, explaining why they didn’t work for you. For example, “These lack punch. Choose language to make this message more memorable.” 

Prompt role play

You can ask a generative AI tool to play different roles to deliver the suggestions you’re seeking. For instance:

  • Time traveler: Imagine it’s five years from now, and our new patient-care initiative was highly successful. Describe what exactly contributed to this success from the perspective of a healthcare executive looking back.
  • Eavesdropper: Pretend you’re secretly overhearing employees talking candidly in the cafeteria about our upcoming merger. What are two genuine fears or worries you’d expect them to express?
  • Social media critic: Create three realistic social media comments responding to our recent health fair announcement — one positive, one skeptical and one critical — to help us anticipate community reactions.

Persona prompts

With persona prompts, you put yourself in your audience’s shoes, based on their:

  • Demographics (age, occupation and role)
  • Background and context (experiences and responsibilities)
  • Goals and motivations (what drives them, their desired outcomes)
  • Challenges or pain points (obstacles, frustrations)
  • Values, attitudes or beliefs (what matters most to them)
  • Behaviors and preferences (how they communicate, their decision-making style)

You can also build a detailed persona. Here’s one Andy Crestodina with Orbit Media Studios, a web design company, recently shared.

Build me a persona of a [job title] at [industry/company size/geography] with [roles/skills/responsibility]. This person is looking for help with [challenge/problem/task] and is considering [product/service]. List their hopes/dreams, fears/concerns, emotional triggers and decision criteria for hiring/contacting a potential partner/provider.

Meta prompting

Ask your generative AI partner to explain the best way you can prompt it to get the best response.

For example:

  • What’s the best way to prompt you if I want…
  • Please generate five sample prompts that demonstrate how to incorporate personas to push past assumptions.

AI policy best practices

AI policy best practices in healthcare content creation must balance innovation with responsibility, accuracy and compliance. Here’s a breakdown of key best practices:

1. Transparency

  • Disclosure: Clearly note when AI-generated content is used, especially in patient-facing materials.
  • Attribution: Label content as AI-assisted or AI-generated and confirm it was reviewed by a qualified human expert.
  • Explainability: Use tools whose outputs you can understand and explain — critical when content informs medical decisions.

2. Accuracy and clinical oversight

  • Expert review: A licensed professional should review any clinical or treatment-related content before publication.
  • Evidence-based sources: Align AI outputs with trusted authorities like the CDC, WHO or peer-reviewed journals.
  • Error prevention: Watch for “hallucinations” or fabricated information by building fact-checking guardrails into workflows.

3. Privacy and data security

  • HIPAA compliance: Never enter protected health information (PHI) into AI tools unless they are certified as HIPAA-compliant.
  • Anonymization: De-identify patient data if it’s used in AI-assisted content or model training.
  • Vendor standards: Partner only with AI vendors who meet strict privacy, security and data storage protocols.

4. Bias mitigation and health equity

  • Bias audits: Regularly review AI tools to detect bias that could reinforce healthcare disparities.
  • Inclusive language: Ensure outputs are culturally sensitive, accessible and inclusive.
  • Audience testing: Validate clarity, tone and impact with diverse focus groups.

5. Content governance and accountability

  • Editorial guidelines: Define when AI can be used (e.g., ideation, drafting, summarizing) and when it cannot (e.g., diagnoses, legal disclaimers).
  • Audit trail: Keep records of how AI was used, and by whom.
  • Human-in-the-loop: Require human review and approval before publishing any AI-generated content.

6. Regulatory compliance

  • FDA and FTC guidelines: Ensure AI-assisted claims align with advertising and marketing regulations.
  • Disclaimers: Use clear disclaimers for AI tools that could be misunderstood (e.g., symptom checkers).
  • Local laws: Stay compliant with regulations such as the Colorado AI Act in the U.S. or the EU AI Act internationally.

Support for AI

Adopting AI is as much a cultural shift as it is a technical one. To succeed, your organization must support people with the right resources and mindset.

  • Train and upskill: Run AI literacy workshops. Teach teams how to prompt, experiment and integrate AI into real workflows.
  • Empower change agents: Appoint early adopters as AI ambassadors. They mentor peers, spot opportunities and connect staff with leadership.
  • Celebrate wins: Share success stories to build momentum and show AI’s impact.
  • Create feedback loops: Encourage input on challenges, improvements and new needs. This builds trust and keeps AI grounded in reality.

AI can be an effective teammate. It doesn’t replace real people, but it’s a collaborative tool and a new addition to the lineup that supports everyone’s efforts.

Diane Hammons, director, WG Content

—Diane Hammons, director of digital engagement, WG Content

AI in healthcare marketing: frequently asked questions

Begin with small, low-risk use cases like summarizing reports, brainstorming headlines or organizing content calendars. These quick wins build confidence before expanding into bigger applications.

Hallucinations are errors or made-up facts in AI outputs. Always verify information against trusted sources and require subject-matter or clinical review before publishing.

Strong prompts give AI context, tone and structure to follow. Weak prompts often result in generic or inaccurate responses. Treat prompting like briefing a junior team member: clear, specific, and goal-oriented.

We help marketing teams build custom GPTs using their internal assets. They are particularly helpful as brand experts, trained in your writing preferences and editorial styles.

Your partner in smarter AI + content

At WG Content, we’re leaning into AI and helping our clients do the same. We feel empowered to explore how we can use generative AI to free up time for creative work, but our clients take the lead on what AI usage is right for their team and brand.

We can also partner with you as a consultant on AI through our WGC Catalyst program, helping you identify ways to use AI that speed up your workflows and scale your efforts without increasing your spend.

Ready to make AI work for your marketing team?

Let’s talk