Ever tried searching for answers about your company in ChatGPT? Chances are the results aren’t quite right…or worse, you’re not there at all.

Unsurprisingly, roughly 45% of Americans use AI search tools daily. And as generative AI tools become part of everyday research, brands are quickly realizing discovery no longer happens only on Google.

For health-tech marketers, that means adapting traditional SEO and moving toward Gen AI engine optimization (GEO): optimizing not just for keywords, but for how large language models (LLMs) understand authority, category clarity, and credibility.

What’s less clear is how to successfully make that shift. That’s where this story starts. Below, we break down, based on conversations with growth and marketing teams across the industry, what’s really shaping AI discovery, where teams are getting stuck, and which strategies are actually working.

The new search panic

There’s a new ritual inside health-tech companies: Someone opens ChatGPT and starts testing prompts.

“Do we show up?”

“Why does that competitor appear?”

“What if I add clinic size or geography?”

Next thing you know, Slack is full of screenshots and meetings turn into live prompt-testing sessions. A single weird answer can send everyone into a spiral because nobody is sure what it means or what to do about it. Welcome to the new search anxiety.

These nerves come from a real shift in how discovery works. Search isn’t just about keywords anymore. It’s about real questions, layered context, and practical constraints—the way buyers actually think and talk. AI tools build answers by stitching together how clearly a brand fits into those conversations and how consistently that positioning is reinforced across credible sources.

And this visibility matters. Data shows that AI-cited content is driving 30–40% higher conversion rates than traditional search results, because buyers trust the answers they’re getting and move faster when brands show up clearly.

Healthcare feels this shift more than most. Trust is everything, regulations shape what can be said, and research starts long before anyone books a demo. So if your brand doesn’t surface early, you might never enter the conversation at all. And if it shows up in the wrong place, that sales conversation may not happen because a competitor gets the call instead. Because there’s a lack of information outside about what companies really do and where they sit in the market (this publication aims to be an exception), LLMs are often offbase.

The tricky part? Most teams still don’t really understand how AI search works. The tools are evolving fast, the metrics are fuzzy, and best practices are still emerging. Without a clear framework, it’s easy to fixate on individual prompt results instead of building the deeper signals that actually drive consistent visibility.

What’s really happening under the hood (and what isn’t)

ChatGPT is not replacing Google. But the two are deeply intertwined.

When tools like ChatGPT or Perplexity don’t already have a confident answer stored in their training data, they actively run Google searches behind the scenes. They then pull together their answers by leaning on the same pages that already show up at the top of Google.

That means classic SEO still matters. Optimizing for Google is also optimizing for AI discovery. The difference is that AI tools aggregate sources to decide which brands seem most authoritative within a topic or category.

So, AI search isn’t just “SEO 2.0.” Instead, it works more like a system for recognizing authority across the web—and there’s no tricking it with shortcuts. That’s why the brands that AI keeps surfacing consistently check these boxes:

Strong authority signals and E-E-A-T: Content backed by real experts, clinical reviewers, clear credentials, and credible citations tells models which brands can be trusted.
Clean, machine-readable structure: Fast-loading sites, clear headings, bullet lists, and schema (especially FAQ schema) make it easier for search engines and AI tools to parse and reuse your content correctly.
Credible external mentions: Press, analyst reports, directories, podcasts, newsletters…it all signals credibility. AI tools care about broad consensus, which means consistent mentions beat a single big splash.

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What healthcare companies are doing today (and where they’re going wrong)

Across health tech, we keep seeing the same three patterns repeat:

Treating AI search like Google SEO: Teams double down on keyword optimization instead of concentrating on the things that actually drive visibility.
Publishing long, AI-generated explainers: Teams pump out high volumes of content without a real strategy, ending up with lots of words and little trust-building substance.
Running internal ChatGPT bake-offs: Teams endlessly tweak prompts (“Why does Competitor X show up here but not there?”) without understanding the real signals AI tools rely on to surface brands.
Declining to speak about the business in a real way: The old days of sharing jargon and putting a company in a category that doesn’t exist just to be the leader of it might genuinely confuse the LLM.

And almost everyone ends up buying an AI tracking platform — usually Profound (there are many, mostly cheaper, others btw) — to try to make sense of it all.

The problem with all of these approaches is the same: they focus on busywork instead of fundamentals. Tweaking keywords, churning out content, or testing prompts won’t get you anywhere if the core signals aren’t in place — things like real expertise, clean structure, current information, and solid third-party validation.

The strategies that are working right now

After publishing 300+ articles, Derek treated each one as a real-world GEO test, and one thing became clear: The brands that consistently show up in AI answers are the ones that nail the fundamentals.

Here’s what we’ve seen move the needle:

1. Structured pages

High-performing brands build product pages that are clean, skimmable, and straightforward.

They clearly spell out who the product is for, the problems it solves, how it works, pricing signals where appropriate, and real outcomes. Most importantly, these pages directly answer the kinds of conversational questions people ask in AI tools, versus trying to avoid them like the old days:

What does this solve?
Who is it for?
Why would someone choose this over an alternative?
What is the competition?
How does the business model work?
What is the pricing?

If those answers aren’t obvious within seconds, AI tools struggle to summarize or recommend your offering. And often, that’s where the information shared back is inaccurate.

2. Machine legibility

AI tools hate mixed messages. If your positioning shifts from page to page or your target customer sounds different across your site, the models get confused. And when that happens, they usually default to the competitor whose story is easier to understand.

Your brand has to be easy for machines to understand, not just humans. That means:

Using basic schema and structured data
Maintaining strong internal linking between related pages
Removing contradictory or fuzzy messaging, and avoiding jargon at all costs

3. External authority

Nothing boosts AI visibility faster than credible third-party validation. Think:

Analyst reports
Media coverage
Podcast appearances
Directory listings
Partnerships
Case studies with real numbers
Even social media posts that get a lot of traction
And a prediction: Market maps will be the new hot content offering

All of this adds up to the “consensus” AI tools look for—signals from across the web that multiple trusted sources agree on who you are and what you do. And in practice, one strong, data-backed case study can do more for your visibility (and authority) than ten generic blog posts ever could.

4. Customer language

The content that works best sounds like your customers, not your marketing team.

High-performing content answers what an orthopedic clinic actually asks, not what your brand assumes they care about. It focuses on real workflows, day-to-day operational problems, and practical decision points rather than abstract feature lists or big-picture explainers.

5. Category ownership

The tighter your niche, the easier it is for AI systems to confidently surface you in the right conversations.

The brands that win here usually lean into real-world credibility, like:

Featuring clinicians and subject-matter experts
Sharing patient or customer stories
Grounding content in lived experience

All of that helps signal that you know your lane.

On the flip side, when you try to be everything to everyone, models struggle to understand where you fit. And when that happens, they default to competitors with sharper positioning.

How to measure your performance in ChatGPT

All of this is great in theory, but how do you tell if any of it is actually working? Here’s how to check.

Tools

A growing wave of AI visibility tools now lets you see how your brand shows up across generative search.

These platforms track how often you’re mentioned in AI answers, which prompts surface competitors, and where citations come from across tools like ChatGPT and Perplexity. They’re still evolving, but they give teams their first real line of sight into AI discovery.

Profound: Probably the best known and definitely the most expensive.
Scrunch AI: Our current fave for tracking AI citations with the richest feature-to-cost ratio we’ve seen.
Gauge
Goodie
Gumshoe AI
Waikay
Semrush & Ahrefs: Traditional SEO tools now adding more and more AI visibility and data

How to run an internal audit

Most teams aren’t going to manually test dozens of prompts, and that’s totally fine. You don’t need a massive effort to get useful insights. Here’s the practical way most companies handle this today:

Start with a small set of high-intent questions your ICP actually asks: Think real buyer queries like “Best behavioral health platform for community clinics” or “RPM tools for Medicaid providers.”
Run those prompts in ChatGPT and Perplexity: Note who shows up, how brands are categorized, and what sources get cited. This gives you your baseline.
Use an AI visibility tool to scale the work: Many offer free trials. The platforms listed above can show you which brands appear most often, what queries surface competitors, and where your content is being cited.
Look for patterns in the results: Pay attention to the sources AI keeps citing, how categories are being defined, and what use-case language shows up most often.
Compare where you show up versus where competitors do: Those gaps usually point directly to what needs fixing or what content you should build next.

Define your “must-win queries”

These are your money keywords. But for AI, they need to be more specific, more human, and way more useful.

Instead of trying to win big, vague searches like “healthcare software” or “RPM platform,” focus on the real questions buyers actually ask, like “best behavioral health platform for Medicaid payers in the Midwest” or “RPM tools that integrate with Epic for small clinics.”

These longer, more detailed queries matter more than generic ones because they reflect how people really make decisions. AI tools are built to answer specific problems, not broad category searches. When you show up for conversational, use-case-driven questions, you meet buyers right when they’re narrowing their shortlist, which is where deals actually start to get made.

Action plan: how to influence ChatGPT results over the next 90 days

If you want to stop guessing and start showing up, this is the short, no-nonsense playbook we give most teams.

Fix your messaging and category narrative: If your story isn’t crisp, no amount of optimization can save you. Get clear on who you serve, what problem you solve, and where you fit in the market. Then make sure that message is consistent everywhere.
Tighten your product pages: Cut the fluff. Add structure. Clearly answer the core questions AI tools look for. If a human can’t understand it quickly, a model won’t either.
Build external authority: If your company doesn’t exist across credible sources like analyst reports or case studies, you effectively don’t exist to AI search. This is exactly the focus of Healthyish Content’s recently launched Authority Building service: creating and placing real-world proof points (mostly driven by clinicians) that reinforce a brand’s expertise in places AI tools already trust.
Clean up your site structure: Make your site easy to parse. Use schema, tighten internal links, and eliminate contradictory messaging that can confuse humans and machines.
Set up monthly AI benchmarking: Pick a fixed set of high-intent prompts and track them over time. Log who shows up, how categories are framed, and what sources get cited so you can measure progress instead of guessing.
Publish the best answers on the Internet for your target prompts: Create a small set of best-in-class resources for your ICP (aka pages that aim to be the single best answer on the internet for your highest-value questions).
Create content off-site: Show up where your buyers already ask questions (like Reddit, YouTube, Quora, LinkedIn, and niche clinical or ops forums). Focus on real participation, not promotion—especially on Reddit, where thoughtful answers to real questions build the credible footprint that AI tools pick up and reward.

What’s coming next: The Era of Conversational Ranking

AI answers are only going to get more transparent. Citations will appear more consistently, which means authority and broad consensus across credible sources will matter even more than they do today.

Healthcare will also face the toughest filters. Because of the risk of medical misinformation, AI tools will continue prioritizing vetted sources and brands that demonstrate real expertise and trustworthiness.

The winners will be companies with strong expertise signals, clear positioning, and tight category focus. Those brands will dominate conversational answers, especially for high-intent, highly specific queries where real buying decisions start.

The takeaway

You can’t game GPT, but you can be the best source for what it needs. The companies that win will look less like content farms and more like organizers of clear, verifiable information.
AI tools reward the same things real clinicians do: precision, consistency, clarity, and evidence.

Build your content and positioning around those fundamentals, and you’ll start to show up (maybe even sooner than you think).

How healthtech companies are shifting marketing tactics for AI search