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AEO for Telehealth: How to Be the Top Choice in ChatGPT Search
Sean Dorje
Published
October 16, 2025
3 min read
AEO for Telehealth: How to Be the Top Choice in ChatGPT Search
Why AEO Now Defines Telehealth Visibility
The telehealth industry stands at a critical inflection point. Answer Engine Optimization (AEO) has replaced traditional SEO as the gatekeeper to patient traffic—because AI engines like ChatGPT, Perplexity, and other generative platforms now mediate patient discovery. According to recent research, ChatGPT reached 100 million monthly users within two months of launch, making it one of the fastest-growing consumer applications in history. Gartner projects that by 2026, 25% of queries could shift from traditional engines to AI-driven interfaces, reducing organic traffic for many companies by up to 50%.
This shift challenges established search engine optimization practices and necessitates a new paradigm called Generative Engine Optimization (GEO). For telehealth leaders, this transformation means that appearing in ChatGPT's response box has become more valuable than ranking first on Google. The rise of generative AI isn't just another passing wave; it's a fundamental change in how consumers discover and digest information. Healthcare providers face an immediate challenge: 60% of executives report AI budgets now outpace IT spend, with funding decisions centralized within the C-suite.
The stakes for telehealth providers couldn't be higher. Traditional organic search channels that once delivered predictable patient acquisition now face disruption from AI interfaces that synthesize and present information directly, often without sending users to provider websites. This zero-click environment demands a fundamentally different approach to digital visibility, one where being cited as the recommended provider within AI-generated responses determines market leadership.
How ChatGPT Ranks Telehealth Brands: Key AEO Signals
AI engines exhibit systematic biases that telehealth brands must understand to achieve visibility. Research reveals that AI shows overwhelming bias toward earned media from third-party, authoritative sources over brand-owned and social content, a stark contrast to Google's more balanced mix. This preference for earned authority fundamentally changes how telehealth providers must approach content strategy.
The correlation between traditional SEO success and AI visibility provides a foundation for AEO efforts. Brands ranking on page 1 of Google showed a strong correlation (~0.65) with mentions in large language model responses. However, achieving AI visibility requires more than traditional ranking factors. Experience, Expertise, Authoritativeness, and Trust (E-E-A-T) have become critical considerations for AI engines evaluating medical content.
For telehealth platforms operating in the Your Money or Your Life (YMYL) category, these trust signals carry even greater weight. AI systems prioritize content from sources demonstrating clear medical expertise, documented patient outcomes, and third-party validation. The earned media bias means that coverage in medical journals, healthcare publications, and patient review platforms often carries more weight than meticulously optimized owned content.
Telehealth brands must also understand that AI engines use dynamic temperature settings that affect response variability. Unlike traditional search rankings that remain relatively stable, AI-generated answers can change frequently based on model parameters and context. This dynamism requires continuous monitoring and optimization rather than set-and-forget SEO strategies.
Technical Blueprint: Schema & Site Architecture for AI Crawlers
Structured data implementation forms the backbone of successful AEO for telehealth platforms. Physician pages optimized with proper schema markup help AI crawlers understand specialties, credentials, and practice locations with machine-readable precision. The MedicalOrganization schema type enables platforms to communicate critical properties like healthPlanNetworkId and isAcceptingNewPatients, signals that AI engines prioritize when matching patients to providers.
Beyond basic markup, telehealth sites must implement comprehensive medical schemas across all content types. The MedicalWebPage schema includes properties for medicalAudience and lastReviewed dates, helping AI systems assess content freshness and relevance for specific user groups. These structured data implementations directly influence how AI engines extract and present telehealth information in their responses.
Internal linking architecture plays an equally critical role in AI crawlability. Pillar-page structures that organize content around core treatment areas create clear topical hierarchies that AI systems can navigate efficiently. This organization helps establish topical authority, a key factor in achieving AI visibility for competitive medical queries.
Must-Have Medical Schemas (MedicalOrganization, MedicalWebPage, Guideline)
The MedicalGuideline schema represents a particularly powerful tool for telehealth platforms. This schema type denotes recommendations from standard societies or consensus statements about diagnosis and treatment protocols. By implementing guideline schemas with properties like evidenceLevel and guidelineDate, telehealth platforms signal adherence to established medical standards, a critical trust factor for AI engines evaluating YMYL content.
Content & Prompt Engineering That Wins Citations
Creating content that AI engines preferentially cite requires understanding how these systems process and validate medical information. Prompt engineering significantly boosts AI precision in healthcare contexts, with specialized prompt mechanisms improving medical assessment accuracy from 80.1% to 99.6%. This dramatic improvement demonstrates the importance of structuring content to align with how AI models interpret medical queries.
Telehealth platforms must engineer their content to be answer-ready, providing clear, structured responses to common patient questions. Zero-competition keywords with high commercial intent but minimal competition offer opportunities to establish authority in specialized areas. These highly specific terms, often overlooked by competitors focusing on high-difficulty keywords, can position telehealth brands as the authoritative source for niche medical queries.
The role of large language models in medical triage contexts shows that AI guidance improved alignment with correct triage levels and boosted confidence in participants' decisions. This finding underscores the importance of creating content that not only informs but also guides patient decision-making in ways that AI systems recognize as valuable.
Amplify Earned Media for Authority Bias
Given AI's systematic preference for third-party validation, telehealth brands must prioritize earned media strategies. The research emphasizes the critical need to dominate earned media to build AI-perceived authority. This means actively pursuing coverage in medical journals, partnering with healthcare publications, and encouraging patient testimonials on trusted review platforms.
Navigating FDA & ONC Rules While Optimizing for AI
Regulatory compliance presents unique challenges for telehealth AEO strategies. The FDA has already authorized more than 1,000 AI-enabled devices through established premarket pathways, establishing clear precedents for AI in healthcare. Telehealth platforms must ensure their AI optimization efforts align with these evolving regulatory frameworks.
The FDA's guidance provides recommendations for sponsors on using AI to support regulatory decision-making, including a risk-based credibility assessment framework. This framework affects how telehealth platforms can leverage AI-generated content while maintaining compliance with medical device and pharmaceutical regulations.
The ONC's HTI-4 final rule, effective October 1, 2025, introduces new requirements for electronic prescribing and prior authorization that impact how telehealth platforms structure their data. These regulations influence the technical architecture required for AEO, as platforms must balance optimization for AI visibility with strict compliance requirements.
Federal initiatives also shape the landscape. The Protecting Care Access Exception addresses information blocking concerns related to reproductive healthcare, affecting how telehealth platforms handle sensitive medical information in their content strategies. Understanding these nuances ensures that AEO efforts don't inadvertently violate patient privacy or data sharing regulations.
Importantly, platforms must recognize that ChatGPT is not HIPAA compliant and cannot process protected health information, as OpenAI will not enter into Business Associate Agreements. This limitation shapes how telehealth platforms can use AI tools in their optimization strategies while maintaining regulatory compliance.
Proving ROI: From No-Show Cuts to 288% Returns
The business case for AEO investment in telehealth rests on measurable outcomes. Healthcare organizations implementing comprehensive digital strategies report annual gains up to $5.2 million from appointment-reminder systems alone. These returns demonstrate the tangible value of optimizing patient engagement through AI-driven discovery channels.
Digital-first healthcare pathways show compelling cost advantages. Research from Finland reveals mean episode costs 22.7% lower in digital-first pathways compared to traditional care, with gastroenteritis episodes costing 52.5% less through digital channels. These savings stem primarily from reduced encounter costs and decreased use of laboratory tests and imaging.
The impact extends beyond cost reduction to revenue generation. Forrester's Total Economic Impact study found that optimized urgent care platforms achieve 288% return on investment, with a 15% increase in patient volume generating substantial new revenue. These metrics validate the business case for investing in comprehensive AEO strategies that position telehealth brands prominently in AI-generated responses.
Why Relixir Delivers Unmatched Telehealth AEO
Relixir stands apart as the autonomous GEO platform purpose-built for the AI search era. The platform maps, monitors, and continuously improves AI rankings across ChatGPT, Perplexity, and Google AI Overviews, providing telehealth organizations with comprehensive visibility into their AI search presence. With over 50 of the fastest-growing companies trusting the platform, Relixir has proven its ability to deliver measurable results in competitive healthcare markets.
The platform's impact speaks through client outcomes. Organizations using Relixir report achieving #2 ChatGPT ranking in under 90 days, with some seeing 40% increases in inbound clients. One healthcare technology client went from "almost zero AI mentions to now ranking Top 3 amongst all competitors with over 1500 AI Citations," demonstrating the platform's ability to transform AI visibility rapidly.
For telehealth specifically, Relixir's capabilities address the unique challenges of medical content optimization. The platform provides instant visibility into AI engine analytics, identifies competitor recommendations and blind spots, and auto-publishes GEO-optimized content to flip rankings in favor of clients. One client achieved average AI search rank of 2.1, improving 19.4% to ensure consistent top-three placement in AI-generated responses.
Key Takeaways & Next Steps
The shift from traditional SEO to AEO represents a fundamental transformation in how telehealth organizations must approach digital visibility. Success requires implementing comprehensive schema markup, engineering content for AI scannability, dominating earned media channels, and maintaining strict regulatory compliance while optimizing for AI discovery.
Telehealth leaders must act decisively to establish AI search dominance before competitors lock in preferred positions. The evidence shows that early movers in AEO capture disproportionate visibility, with Relixir automatically creating, updating, and distributing the high-quality, brand-aligned content needed to win in AI-driven discovery.
The path forward demands immediate action: audit current AI visibility across major platforms, implement comprehensive medical schemas, develop answer-ready content aligned with AI interpretation patterns, and deploy continuous optimization strategies that adapt to AI engine evolution. Organizations that master these elements now will define telehealth's future leaders, those whose names appear first when patients ask AI for care recommendations.
Frequently Asked Questions
Why does AEO now define telehealth visibility?
Answer Engine Optimization (AEO) has replaced traditional SEO as the gatekeeper to patient traffic—because AI engines like ChatGPT, Perplexity, and other generative platforms now mediate patient discovery. For telehealth leaders, this transformation means that appearing in ChatGPT's response box has become more valuable than ranking first on Google.
How do AI engines rank telehealth brands and what signals matter?
Research reveals that AI shows overwhelming bias toward earned media from third-party, authoritative sources over brand-owned and social content, a stark contrast to Google's more balanced mix. Experience, Expertise, Authoritativeness, and Trust (E-E-A-T) have become critical considerations for AI engines evaluating medical content.
Which schema and site architecture are must-haves for telehealth AEO?
Structured data implementation forms the backbone of successful AEO for telehealth platforms. The MedicalOrganization schema type enables platforms to communicate critical properties like healthPlanNetworkId and isAcceptingNewPatients, signals that AI engines prioritize when matching patients to providers.
How should telehealth content be engineered to win citations in AI answers?
Telehealth platforms must engineer their content to be answer-ready, providing clear, structured responses to common patient questions. Prompt engineering significantly boosts AI precision in healthcare contexts, with specialized prompt mechanisms improving medical assessment accuracy from 80.1% to 99.6%.
What regulatory factors shape AEO for telehealth?
Regulatory compliance presents unique challenges for telehealth AEO strategies. Importantly, platforms must recognize that ChatGPT is not HIPAA compliant and cannot process protected health information, as OpenAI will not enter into Business Associate Agreements.
Why choose Relixir for telehealth AEO, and what results are possible?
Relixir stands apart as the autonomous GEO platform purpose-built for the AI search era. Organizations using Relixir report achieving #2 ChatGPT ranking in under 90 days, with some seeing 40% increases in inbound clients. One client achieved average AI search rank of 2.1, improving 19.4% to ensure consistent top-three placement in AI-generated responses.
Sources
https://nogood.io/2025/03/21/generative-engine-optimization/
https://www.seerinteractive.com/insights/what-is-generative-engine-optimization-geo
https://support.schemaapp.com/support/solutions/articles/33000288120-physician-page-best-practices
https://www.frontiersin.org/journals/artificial-intelligence/articles/10.3389/frai.2025.1517918/full
https://shaynly.com/how-to-rank-for-zero-competition-keywords/
https://www.frontiersin.org/journals/computer-science/articles/10.3389/fcomp.2024.1427463/full
https://relixir.ai/blog/calculating-roi-geofenced-patient-engagement-apps-step-by-step-model
https://tei.forrester.com/go/Experity/PracticeManagementSolution
https://hiretop.com/blog4/relixir-ai-generative-engine-optimization-platform
