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Beyond Google: Managing your healthcare reputation in the age of AI

Beyond Google: Managing your healthcare reputation in the age of AI GettyImages 1447133504

For years, healthcare reputation strategy centered around Google reviews. And that’s a strategy that made complete sense in a traditional search-driven world.

But increasingly, patients are turning to AI assistants—like ChatGPT, Gemini, Copilot, Claude, and Perplexity—to ask questions directly. “Who is the best cardiologist near me?” “Tell me about the best rated orthopedic surgeons in my area.”

Press Ganey’s latest research shows that one in five consumers uses AI answer engines for provider research. That number has only grown year over year. As of January 2026, over 40 million people daily use ChatGPT for health-related queries.

In the AI discovery era, reputation must be multisource by design.

AI systems do not rely on a single review platform when generating recommendations. Instead, they aggregate, normalize, and cross-validate signals from multiple healthcare reputation sources.

The shift from consumer search to AI discovery

Traditional digital strategy optimized for:

  • Google Maps visibility (i.e., the Google Map Pack)
  • Positive star ratings and review volume
  • Local SEO positioning

AI answer engines are looking to synthesize data across multiple types of platforms:

  • Healthcare-specific directories (like Healthgrades, WebMD, Vitals, RateMDs)
  • Hospital and health-system websites and directories
  • Verified patient survey data
  • General review platforms (like Google, Yelp)
  • Professional directories
  • Institutional affiliations and board certifications

AI systems are designed to combine diverse signals to improve recommendation quality and surface answers to user queries.

This means no single platform serves as the sole authority.

How AI answer engines evaluate reputation

1. A return to consumer-first language

    How should organizations optimize their sites for answer engines? It turns out, it’s not that different from traditional technical SEO practices. Since traditional search is not dead, organizations should include both. AI engines favor a more conversational, plainly worded knowledge graph. Instead of focusing on credible backlinks, organizations should monitor and generate positive brand mentions on third-party sites like review sites, directories, publications, and forums.

    AI validates information across multiple sources, which for healthcare includes Google, Healthgrades, Vitals and WebMD, to create a more complete view of provider reputation.

    2. Each platform is different. A good marketer diversifies.

      While AI answer engine developers do not disclose the exact details of how their engines return answers and recommendations, it’s clear that citations span a variety of sites. However, you might be surprised to find that each engine has a slightly different approach to how they return recommendations.

      While our research finds that the majority of provider searches are happening on free tools like ChatGPT and Gemini (and its application in Google search), other platforms like Claude and Perplexity still make the list.

      Google’s Gemini relies heavily on its search index and the Knowledge Graph, and Google has blurred the line between traditional search and AI answers with its AI Overviews. It’s common to see sources cited and how they fold into results. However, ChatGPT, which doesn’t always crawl the live web, isn’t as likely to cite sources.

      To meet the needs of consumers using a variety of search tools, focus on the following hierarchy, which is ordered to prioritize highly credible sources first.

      Top priority:

      • Hospital or health system physician profiles
      • Healthcare-specific directories (e.g., Healthgrades)
      • Verified patient survey data

      Critical, but diversity is key:

      • Google (particularly for volume and recency).
      • WebMD, Vitals, Sharecare, etc.

      Lower priority:

      • Smaller or niche platforms with limited review volume

      3. When it comes to reviews, volume and recency matter

        AI systems are trained to provide balanced recommendations and therefore weigh outlier opinions and information similar to how consumers would as well. In short, having a few negative reviews amid largely positive sentiment isn’t necessarily a dealbreaker.

        They favor:

        • Larger review volumes over small samples
        • Consistent sentiment across platforms
        • Recent reviews
        • Repeated positive themes

        They discount:

        • 5-star ratings based on one or two reviews
        • Isolated platform dominance
        • Outdated feedback

        Why Google-only strategies are so risky

        Consider this scenario: A provider has ~400 Google reviews, but minimal presence on healthcare-specific directories. Since they are new to a hospital, they have weak hospital profile visibility—their profile is not built out yet and they don’t have many patient reviews.

        An AI system may interpret this as single-source concentration. There is limited third-party site validation of any of the consumer sentiment expressed on Google. Since this information cannot be validated, or substantiated, it signals reduced credibility for this provider.

        When weighing this provider against one with a balanced presence across Google and healthcare directories, strong institutional affiliation, and consistent ratings across platforms, the second provider’s reputation signals as more highly credible to AI engines.

        The second provider may surface higher in AI-generated recommendations—even with fewer total Google reviews.

        AI does not simply replicate Google rankings. It synthesizes broader credibility signals.

        6 tips for healthcare organizations to stand out in AI searches

        Here are some things that healthcare organizations can do now to stay visible in AI searches:

        1. Actively manage healthcare-specific directories
        2. Monitor cross-platform consistency
        3. Encourage balanced review distribution
        4. Strengthen hospital and system profiles with information and reviews
        5. Track review recency and volume trends
        6. Ensure institutional credibility is visible and accurate

        Healthcare organizations that proactively strengthen their reputation across the entire digital ecosystem will be more visible, not only in search results, but in AI-generated recommendations that increasingly guide patient decisions.

        To learn more about how Press Ganey can help you strategize a brand and reputation strategy that encompasses all of the ways consumers search for care, reach out to one of our experts.