Online Doctors: 2026 AI Market Discovery Index

Answer Capsule

In the online doctors category for August 2026, AI systems are compressing the market into a two-way race between Doctor on Demand and Sesame, with Teladoc holding the strongest rank-one position but trailing in overall recommendation coverage. The clearest risk pattern is Amwell, which appears in over a third of AI responses but converts that presence into only 20.2% recommendation coverage, leaving it commercially exposed to more aggressive competitors.

For the strategic interpretation of this benchmark, read CiteWorks Studio's analysis of How AI Search Is Recommending Online Doctors

Executive Summary

AI recommendation systems are fundamentally restructuring how patients discover and select online doctor services. The August 2026 benchmark shows that being mentioned in AI responses no longer translates into being recommended. Across 560 observations from six major AI platforms, the gap between presence and recommendation power has become the defining competitive metric in this category.

Doctor on Demand and Sesame have emerged as the clear recommendation leaders, each capturing roughly 23% of the available AI opportunity. Teladoc holds the strongest rank-one position with an 18% rank-one rate and an average recommended rank of 1.92, but its overall recommendation coverage of 41.8% places it third in commercial terms. MDLive occupies a solid middle position with 26.3% recommendation coverage, while the remaining brands trail significantly.

The most striking finding is the visibility-to-recommendation gap. Amwell appears in 35.4% of AI responses but converts that presence into only 20.2% recommendation coverage. This disconnect means the brand is being seen but not advanced, a pattern that carries real commercial consequences as patients increasingly rely on AI-generated shortlists to make healthcare decisions.

Recommendation power matters because AI platforms are becoming the new front door for healthcare selection. When a patient asks which online doctor service to use, the AI response effectively creates a shortlist that shapes the entire consideration set. Brands that appear in these shortlists gain disproportionate access to patient demand, while brands that are merely mentioned risk being filtered out before they ever reach the patient's consideration.

The AI Discovery Shift in Online Doctors

Traditional healthcare marketing assumed that brand awareness and search visibility would translate into patient acquisition. AI platforms have broken that assumption. When a patient asks an AI assistant for the best online doctor service, the response is not a list of all available options. It is a curated shortlist, typically three to five brands, that effectively becomes the patient's consideration set.

The distinction between being mentioned and being advanced is now commercially critical. A brand can appear in an AI response as a factual reference, a comparison point, or a neutral listing, but that does not mean the AI is recommending it. Valid recommendations require positive framing, ranked placement, and shortlist-quality positioning. Several brands with meaningful presence rates are failing to convert that presence into recommendation credit.

AI platforms build their responses from public source material, and the quality, consistency, and trustworthiness of that material directly shapes which brands get recommended. Brands with strong official content, positive review signals, and consistent citation across authoritative sources are more likely to be advanced. Brands that rely on awareness alone, without the supporting evidence layer, are increasingly being left out of AI-generated shortlists.

Directional Category Leaders

1. Sesame

Sesame leads the category in valid recommendation count with 253 recommendations and 45.2% recommendation coverage, the highest coverage rate among all ten companies measured. The brand appears in 57.1% of AI responses and achieves a 26.4% top-three rate and a 34.1% top-ten rate. Its net sentiment score of 0.82 is the strongest among major players, indicating that when the brand appears, it is framed positively. Its average recommended rank of 2.52 reflects consistent top-tier placement across platforms.

The public interpretation: Sesame has built exceptional recommendation coverage with the most positive framing in the category, making it the market's most commercially dangerous challenger.

2. Doctor on Demand

Doctor on Demand leads in recommendation consistency with 230 valid recommendations and 41.1% recommendation coverage. The brand appears in 63.6% of AI responses and converts that presence into a 22.5% top-three rate and a 33% top-ten rate. Its average recommended rank of 2.83 places it consistently near the top of AI-generated shortlists. Strongest platform performance comes from Google AI Mode at 55.1% recommendation coverage and Google AI Overviews at 53.9%.

The public interpretation: Doctor on Demand has built the most consistent AI recommendation architecture in the category, converting strong presence into reliable shortlist placement across multiple platforms.

3. Teladoc

Teladoc holds the strongest rank-one position in the category with an 18% rank-one rate and 101 rank-one placements, more than double any competitor. Its average recommended rank of 1.92 is the best in the market. However, overall recommendation coverage of 41.8% places it third despite having the highest presence rate in the category at 67.3%. Teladoc is winning the top spot when advanced but is not being advanced as consistently as its two main rivals.

The public interpretation: Teladoc wins when recommended but is not being shortlisted as reliably as its presence rate would suggest, indicating a gap between brand recognition and recommendation consistency.

4. MDLive

MDLive occupies a solid second tier with 147 valid recommendations and 26.3% recommendation coverage. The brand appears in 40.4% of AI responses and achieves a 15.7% top-three rate. Its net sentiment score of 0.72 indicates positive framing when mentioned, and its strongest performance comes from Google AI Overviews at 31.5% recommendation coverage.

The public interpretation: MDLive has established a credible mid-market position but lacks the recommendation density to challenge the top three.

5. Amwell

Amwell represents the category's most significant visibility-to-recommendation gap. The brand appears in 35.4% of AI responses but converts that presence into only 20.2% recommendation coverage. Its top-three rate of 8.2% and rank-one rate of 0.5% are dramatically below its presence rate. Amwell's average recommended rank of 3.37 places it in the middle of shortlists when it does appear, but the brand is frequently mentioned without being advanced.

The public interpretation: Amwell is being seen by AI systems but is not earning shortlist placement, creating a commercial vulnerability that is disproportionate to its brand recognition.

6. LiveHealth Online

LiveHealth Online shows modest presence with a 9.1% appearance rate and 6.1% recommendation coverage. The brand achieves a 2% top-three rate and a 5% top-ten rate, with an average recommended rank of 3.93. Its strongest performance comes from Google AI Mode at 8.9% recommendation coverage.

The public interpretation: LiveHealth Online maintains a marginal AI presence but lacks the recommendation density to compete for patient consideration at scale.

7. K Health

K Health appears in 6.3% of AI responses with 4.3% recommendation coverage. The brand achieves no rank-one placements and a 0.7% top-three rate, with an average recommended rank of 4.8.

The public interpretation: K Health has minimal AI recommendation presence and is not currently competing for shortlist placement in this category.

8. HealthTap

HealthTap appears in 4.6% of AI responses with 2.5% recommendation coverage. The brand achieves a 0.5% top-three rate and a 1.8% top-ten rate. Despite low overall coverage, HealthTap does earn occasional rank-one placements, suggesting narrow niche strength.

The public interpretation: HealthTap has sporadic AI presence and limited shortlist eligibility, though its occasional rank-one appearances indicate some platform-specific traction.

9. Lemonaid Health

Lemonaid Health shows 4.1% presence with 3.4% recommendation coverage. The brand achieves a 0.9% top-three rate and a 2.9% top-ten rate. Its net sentiment score of 0.83 is among the highest in the category, indicating strong positive framing on the rare occasions it appears.

The public interpretation: Lemonaid Health generates positive sentiment but appears too infrequently to build meaningful recommendation power at the category level.

The Buying Moments That Now Decide the Category

Best Online Doctors & Top Telehealth Services

This consideration-stage cluster generated all 560 observations in the public benchmark and represents the highest-intent buying moment in the category. Patients asking for the best online doctor service or top telehealth provider are actively evaluating options and are closest to conversion. The cluster spans prompts including "online doctor," "virtual doctor visit," "telehealth app," and "online prescription," all of which signal immediate healthcare need rather than casual research.

Doctor on Demand, Sesame, and Teladoc dominate this cluster, collectively capturing the majority of shortlist placements. MDLive holds a credible secondary position, while the remaining brands appear too infrequently to influence patient decisions at meaningful scale.

The commercial weight of this cluster is significant. Patients in this buying moment are not browsing; they are making care decisions. AI-generated shortlists for these prompts function as the first and often final filter. Brands that appear consistently in these shortlists gain direct access to high-intent patient demand. Brands that are mentioned without being advanced, or absent entirely, are effectively invisible to this segment.

Why Recommendation Power Is Concentrating

Recommendation power is concentrating because AI platforms require evidence, not just awareness, before advancing a brand. Doctor on Demand, Sesame, and Teladoc have all built citation architectures that AI systems can retrieve, verify, and trust. That foundation translates directly into shortlist eligibility.

The evidence layer operates across several content types. Official brand content, including service descriptions, provider credentials, and pricing transparency, helps AI systems understand what a brand offers and whether it is credible. Comparison content that positions a brand in relation to alternatives helps AI systems place it in context. Review and community signals provide social proof that AI systems weigh when making recommendations. In healthcare specifically, regulatory signals and trust indicators carry additional weight, and brands with clear licensing, accreditation, and provider verification information are structurally advantaged.

Brands that lack depth in any of these content categories face a structural disadvantage regardless of their awareness levels. Amwell's presence-to-recommendation gap almost certainly reflects a citation architecture that supports factual reference but not recommendation-level trust. The brand is being seen in market-description contexts but not being advanced in recommendation contexts.

The concentration effect compounds over time. Brands recommended by AI systems gain patient traffic, which generates more reviews, more comparison content, and stronger brand signals. This reinforces their recommendation eligibility in future responses. Brands excluded from shortlists lose this compounding effect, creating a gap that widens with each passing month.

The Category's Most Visible Warning Sign

Amwell is the category's most visible warning sign, and the gap in its data is precise enough to demand attention. The brand appears in 35.4% of AI responses, placing it fourth in presence among all ten companies. Yet its recommendation coverage of 20.2% represents a conversion gap of more than 15 percentage points. Its rank-one rate of 0.5% means it is almost never the first recommendation. Its top-three rate of 8.2% means it rarely appears in the positions that drive patient action.

This is not a borderline underperformance. It is a structural disconnect between how AI systems categorize Amwell and how they evaluate it for recommendation. The brand is being included in AI responses as a market participant, but something in its evidence layer is preventing AI systems from advancing it with confidence.

For a company with Amwell's market history and brand recognition, this pattern represents a significant commercial vulnerability. The warning for the broader category is equally clear: presence without recommendation power is not a sustainable competitive position as AI platforms become the primary discovery mechanism for healthcare services.

What This Means for the Category

The online doctors category is experiencing shortlist compression. AI platforms are consistently recommending a small set of brands across a wide range of patient prompts, and that set is tightening. The gap between the top three and the rest of the market is not incremental. It reflects fundamentally different levels of AI readiness, and the brands at the bottom of these rankings are not simply underperforming. They are being structurally excluded from the consideration set.

Competitor displacement is accelerating. As Sesame and Doctor on Demand strengthen their recommendation architectures, they are not just winning more shortlist placements. They are reducing the space available for brands like Amwell and MDLive to appear. Every shortlist position captured by a leader is a position unavailable to a challenger.

Trust-source dependency is becoming the defining competitive variable. AI platforms do not recommend brands based on advertising spend, domain authority, or brand longevity. They recommend brands whose public evidence supports confident endorsement. The healthcare brands that win in AI-driven discovery will be those that build comprehensive citation architectures across official content, comparison sources, review platforms, and trust signals relevant to patient safety and care quality.

AI discovery is not a future consideration for healthcare brands. It is the mechanism by which a growing share of patients find and select care today. Brands that treat AI recommendation as a strategic priority will capture disproportionate share of high-intent patient demand. Brands that continue to rely on traditional visibility metrics will find themselves increasingly absent from the moments that matter.

What This Public Benchmark Does Not Include

This public benchmark provides a directional view of AI recommendation power in the online doctors category. The full paid report includes:

• Full cluster dataset across all 10 buyer-intent clusters
• Prompt-level response tables showing exactly how each brand appears
• Citation-source failure maps identifying which evidence sources are missing
• Platform-by-platform recovery priorities for each brand
• Entity and schema diagnostics for technical readiness
• Source-layer gap analysis showing which content types are underweight
• Company-specific content recommendations for improving recommendation eligibility
• Exact competitor threat profiles for each brand
• Full paid opportunity model with commercial prioritization

This page shows the market shape. The paid report shows the repair map.

Methodology and Disclaimers

Market studied: Online doctors and telehealth services, including virtual consultations, online prescriptions, and digital healthcare platforms.

Brands included: Amwell, Doctor on Demand, HealthTap, K Health, Lemonaid Health, LiveHealth Online, MDLive, Sesame, Teladoc, and PlushCare. The universe may not include all market participants.

Data collection window: August 2026, with extraction on August 1, 2026.

AI platforms tested: ChatGPT, Copilot, Gemini, Google AI Mode, Google AI Overviews, and Perplexity.

Prompts evaluated: 800 total prompts were submitted. 560 eligible prompts generated the observations analyzed in this report.

Prompt categories: The public benchmark covers the consideration-stage cluster "Best Online Doctors & Top Telehealth Services." The full report includes evaluation-stage comparison prompts and decision-stage pricing and access prompts.

Definition of a mention: A mention is recorded when a company appears in an AI-generated response, regardless of framing, position, or sentiment.

Definition of a valid recommendation: A valid recommendation is a positive, shortlist-quality placement that earns recommendation credit. Appearance in a response and receipt of a valid recommendation are distinct outcomes. This benchmark measures both separately.

Metrics used: Valid recommendation coverage, top-three rate, rank-one rate, top-ten rate, average recommended rank, and net sentiment score. Monetary opportunity metrics from the source data are excluded from this public version.

Limitations: This is a point-in-time benchmark. AI outputs can change based on platform updates, source material changes, and user context. The public version omits monetary metrics present in the full dataset. This report is not a comprehensive audit or complete market census, and findings should be interpreted as directional rather than definitive.

For a company-specific Authority Index report, the deeper analysis would show which prompts each company wins or loses, which AI platforms are under-recognizing the brand, which source layers are shaping recommendations, and what changes may improve AI shortlist eligibility.