How AI Search Is Recommending Online Doctors

Patients searching for virtual care are no longer moving exclusively from a Google results page to a brand website. They are asking AI systems to compare telehealth platforms, evaluate reputation, summarize pricing, surface alternatives, and recommend shortlists. These AI-generated responses act as de facto recommendation engines, compressing the patient consideration set to three to five brands per query and reshaping where discovery decisions are made.

The June 2026 LLM Authority Index benchmark for the Online Doctors category reveals a market where being mentioned by AI is no longer sufficient. PlushCare and Sesame have pulled ahead, capturing a combined $1.38 million in modeled monthly AI Authority Value, while the remaining eight brands share just $735,000. The most commercially significant finding is the gap between raw visibility and recommendation power: established telehealth brands like Teladoc and Amwell appear frequently in AI responses but are rarely advanced as top choices. CiteWorks Studio interprets this benchmark to help brands understand where recommendations are formed and what the public evidence layer reveals about competitive positioning.

Methodology

1. Market studied: Online Doctors, covering telehealth and virtual care platforms that offer on-demand or scheduled consultations with licensed physicians via digital channels.
2. Brands/entities included: Amwell, Doctor on Demand, HealthTap, K Health, Lemonaid Health, LiveHealth Online, MDLive, PlushCare, Sesame, Teladoc. This universe may not include every active brand in the category.
3. Data collection date/window: June 2026. Snapshot date June 16, 2026.
4. AI platforms tested: ChatGPT, Gemini, Copilot, Perplexity, Google AI Mode, Google AI Overviews.
5. Number of prompts tested: Prompt count was not provided. 829 observations were analyzed across three public high-intent buyer-stage clusters.
6. Prompt categories: Consideration (Best Telehealth Platforms and Top Virtual Care Services), Evaluation (Telehealth Platform Comparisons and Alternatives), Decision (Telehealth Pricing, Cost, and Plans).
7. Definition of a mention: A mention means the company appeared in an AI-generated response, regardless of sentiment, rank, or framing quality.
8. Definition of a valid recommendation: A valid recommendation is a positive, shortlist-quality or ranked recommendation that earns recommendation credit. Visibility is not the same as recommendation credit. Neutral, cautionary, or list-only mentions do not qualify as valid recommendations.
9. Ranking/scoring metrics used: Valid recommendation coverage, Top 3 rate, Rank 1 rate, Top 10 rate, average recommended rank, net sentiment score, monthly AI Authority Value, monthly AI Recommendation Value, monthly AI Visibility Assist Value, and captured share of AI opportunity.
10. Limitations: This is a point-in-time benchmark. AI outputs can change. Modeled values are estimates and not revenue. This report is not a full audit or full market census. Prompt count was not disclosed in the available dataset.

Key Findings

Recommendation power is concentrating around two brands. The benchmark shows PlushCare and Sesame capturing 70 percent of the total modeled monthly AI Authority Value in the Online Doctors category. PlushCare leads with $844,165 in AI Authority Value, appearing in 52.6 percent of all observations and earning valid recommendations in 18.6 percent of them. Sesame follows at $535,802 with a 13.2 percent valid recommendation rate. The remaining eight brands collectively hold 30 percent of the category's modeled value. This level of concentration means that most brands are competing for a fraction of available recommendation-stage visibility.

Visibility does not predict recommendation strength. The analysis found that Teladoc appears in 20.6 percent of observations but earns valid recommendations in only 6.2 percent of them. Amwell shows a similar pattern, with 21.2 percent mention presence but just 6.8 percent valid recommendation coverage. Both brands are being listed as reference points but are not being advanced as top choices by AI systems. On Google AI Mode specifically, Teladoc appears in 17.4 percent of responses but earns zero Top 3 recommendations, a pattern that signals the brand's presence may be serving as a comparison anchor rather than a shortlist entry.

Efficient recommendation conversion creates value independently of raw visibility. Doctor on Demand appears in only 15.3 percent of observations yet achieves a 7.5 percent valid recommendation rate and the highest net sentiment score in the category at 0.50. Its AI Authority Value of $198,752 exceeds both Teladoc and Amwell despite lower mention presence. The benchmark suggests that framing quality and source-layer consistency can drive recommendation power even when a brand is not the most frequently mentioned.

The evaluation-stage cluster is the most competitive battleground. In the Telehealth Platform Comparisons and Alternatives cluster, which carries a 1.25 buyer stage multiplier, PlushCare leads at $296,072 in AI Authority Value and Sesame follows closely at $279,636. This is the only cluster where Sesame nearly matches PlushCare in recommendation value, suggesting that comparison-stage prompts represent the most accessible entry point for challenger brands seeking to close the gap.

Decision-stage prompts reveal the sharpest separation between leaders and followers. In the Telehealth Pricing, Cost, and Plans cluster, which carries the highest buyer stage multiplier at 1.5, PlushCare leads at $122,628 and Sesame follows at $107,218. Teladoc drops to $8,725 in this cluster. K Health and Lemonaid Health capture zero recommendation value here. Because decision-stage prompts represent the highest patient purchase intent, the gap between leaders and the rest of the category is most commercially significant in this cluster.

What Changed in the Market

Patients searching for online doctors are no longer only moving from a search engine to a brand website. They are asking AI systems direct questions: which telehealth platform is best, how does MDLive compare to Teladoc, what does Sesame charge for a visit, and which online doctor service is right for uninsured patients. These are not informational queries. They are high-intent discovery queries, and AI systems are answering them with shortlists, comparisons, and ranked recommendations.

This shift matters more in healthcare than in many other categories. Patients choosing an online doctor are making trust-dependent decisions. They are evaluating legitimacy, credentials, reviews, pricing transparency, and risk. AI systems are synthesizing available public evidence to answer these questions, and the brands that appear in the top positions of those answers are gaining a structural advantage over brands that appear lower or not at all.

The benchmark reveals two distinct tiers in this market. Brands in the first tier, PlushCare and Sesame, are being actively recommended across buyer stages and platforms. Brands in the second tier are visible but not recommended, or are being mentioned primarily as comparison anchors and alternatives rather than as the preferred choice. Patients making decisions based on AI answers are disproportionately directed toward the first tier.

The evaluation stage is where this dynamic is most visible. When patients ask AI systems to compare telehealth platforms or find alternatives to a service they already know, the AI response largely determines which brands enter the consideration set. A brand that is absent from those comparison responses, or that appears with neutral framing, is not competing for that patient at the moment of decision.

What the Benchmark Found

Recommendation Leaders

PlushCare is the dominant recommendation leader in the Online Doctors category across all three buyer-stage clusters. The analysis found PlushCare appearing in 52.6 percent of all observations and earning valid recommendations in 18.6 percent of them, a Top 3 rate of 14.5 percent, and a Rank 1 rate of 8.8 percent. On Google AI Overviews, PlushCare reaches a 30.3 percent recommendation rate with an average rank of 1.59. Its AI Authority Value of $844,165 is more than 1.5 times the next closest competitor. Across all six platforms measured, PlushCare consistently appears as the default first recommendation for high-intent online doctor queries.

Sesame is the strongest challenger brand and the clearest threat to PlushCare's position, particularly in the evaluation and decision clusters. Sesame achieves a 10.9 percent Top 3 rate, a 4.6 percent Rank 1 rate, and an average recommended rank of 2.13. On Google AI Overviews, Sesame reaches a 27.7 percent recommendation rate and a 25.6 percent Top 3 rate, its strongest platform performance. Its AI Authority Value of $535,802 places it firmly in the second position in the category. The benchmark suggests Sesame's citation architecture and pricing transparency are contributing to strong performance in the evaluation and decision clusters where comparison content and cost information are most relevant.

Visible but Under-Recommended

Teladoc is the clearest example of a brand with strong mention presence but weak recommendation conversion. Appearing in 20.6 percent of observations, Teladoc is among the most frequently mentioned brands in the dataset. Its valid recommendation coverage of 6.2 percent, Top 3 rate of 4.8 percent, and Rank 1 rate of 1.8 percent are disproportionately low relative to that presence. Its AI Authority Value of $151,808 is less than one-fifth of PlushCare's. Teladoc's best platform is Gemini at an 11.4 percent recommendation rate, but on Google AI Mode it appears in 17.4 percent of responses while earning zero Top 3 recommendations. The benchmark marks this as a cautionary visibility pattern: the brand is being used as a reference point rather than as a recommendation.

Amwell follows a similar pattern. Appearing in 21.2 percent of observations, Amwell is the second most frequently mentioned brand in the dataset. Its valid recommendation coverage of 6.8 percent, Top 3 rate of 5.1 percent, and Rank 1 rate of 1.1 percent reflect a similar gap between mention presence and recommendation power. Its AI Authority Value of $155,703 is comparable to Teladoc's. Amwell performs best on ChatGPT at a 15.5 percent recommendation rate but underperforms on Gemini and Google AI Mode. These two brands together illustrate how established category recognition can generate AI mentions without generating AI recommendations.

Efficient Recommendation Converter

Doctor on Demand demonstrates that lower visibility does not prevent strong recommendation performance. Appearing in 15.3 percent of observations, Doctor on Demand achieves a 7.5 percent valid recommendation rate, a 4.7 percent Top 3 rate, and the highest net sentiment score in the category at 0.50. Its AI Authority Value of $198,752 exceeds both Teladoc and Amwell. On Google AI Overviews, Doctor on Demand reaches a 19.5 percent recommendation rate with an average rank of 1.55. The benchmark suggests this brand's framing quality and source consistency are driving recommendation conversion at an above-average rate for its visibility level.

Brands with Limited Recommendation Presence

LiveHealth Online appears in 8.0 percent of observations but earns valid recommendations in only 0.6 percent of them. Its net sentiment score of 0.08 is the lowest in the category, indicating that mentions are predominantly neutral. Its AI Authority Value of $15,030 reflects limited recommendation-stage influence.

MDLive appears in 6.0 percent of observations with a 0.8 percent valid recommendation rate. Its AI Authority Value of $22,308 is the second lowest in the category among brands with measurable visibility.

Lemonaid Health appears in 5.1 percent of observations with a 0.8 percent valid recommendation rate. It captures zero recommendation value in the decision-stage pricing cluster, the highest-intent buyer cluster in the dataset.

K Health appears in 3.4 percent of observations with a 0.6 percent valid recommendation rate. Its AI Authority Value of $50,469 is driven primarily by visibility assist value rather than recommendation credit.

HealthTap appears in 4.0 percent of observations with a 1.0 percent valid recommendation rate and an AI Authority Value of $8,053, the lowest in the category.

Why Visibility Is Not Enough

A brand can appear in AI answers and still fail to win the patient shortlist. This is the structural finding the benchmark demonstrates most clearly, and it changes how category leaders need to think about AI-led discovery.

Raw mention presence measures how often a company is named in AI responses. Valid recommendation coverage measures how often that company is actually recommended or advanced as a top choice. These are different signals with different commercial consequences. Teladoc and Amwell are both named in more than one in five AI responses in this category. Their valid recommendation rates are roughly one-third of their mention rates. The gap is not a rounding error. It represents the difference between being listed and being chosen.

Top 3 placement is where the commercial dynamic sharpens further. PlushCare achieves a 14.5 percent Top 3 rate. Teladoc achieves 4.8 percent. Most patients reading an AI recommendation do not scroll past the first three options. A brand outside the top three is present but not competitive at the moment of decision.

Rank 1 placement matters most. PlushCare leads with an 8.8 percent Rank 1 rate. Amwell achieves 1.1 percent. When AI systems consistently place one brand first and another brand fourth or fifth, the patient experience reflects that hierarchy.

Neutral framing compounds the problem for under-recommended brands. LiveHealth Online's net sentiment score of 0.08 means the brand is almost always mentioned in neutral rather than positive terms. Neutral mentions create awareness but do not build the trust signal that moves a patient toward selection. In a category where trust is a primary purchase driver, neutral framing is a meaningful competitive disadvantage.

Modeled benchmark value reflects recommendation influence, not revenue. The AI Authority Values in this dataset are estimates designed to represent the relative commercial weight of recommendation-stage visibility. They are not booked sales, pipeline figures, or conversion guarantees. But they are directionally meaningful: the brands capturing the most modeled value are the brands AI systems are most consistently recommending, and that pattern shapes the options patients see.

The Citation Layer

AI platforms build recommendations from available public evidence. The brands leading in this benchmark share a pattern: strong official website content, broad editorial and comparison coverage, positive patient sentiment signals, clear pricing information, and consistent entity representation across sources.

PlushCare and Sesame both maintain high net sentiment scores of 0.41 and 0.42 respectively and high positive visibility rates of 21.6 percent and 14.1 percent. Doctor on Demand reaches a net sentiment score of 0.50. These scores reflect framing quality in AI responses, and they correlate with AI Authority Value leadership. The public evidence layer available to AI systems for these brands appears to provide more persuasive and consistent source material than what is available for the brands that appear with neutral or mixed framing.

The source types that appear to shape AI answers in this category include official brand sites with structured pricing and service information, editorial review articles on health and consumer publications, comparison pages that rank telehealth platforms by feature or cost, directory listings, patient review platforms, and forum discussions where patients describe experiences with specific services. Sources that address pricing transparency, provider credentials, and insurance compatibility are particularly relevant in this category because those are the attributes patients most commonly ask AI systems about.

The citation architecture matters structurally. A brand with strong official content, broad comparison-page coverage, and consistent positive review signals gives AI systems more retrievable, synthesizable material to draw from when constructing a shortlisted recommendation. A brand with brand recognition but thin source architecture is more likely to appear as a mention than as a recommendation.

The platform-level data reinforces this. Google AI Overviews and Google AI Mode show different recommendation patterns than ChatGPT, Gemini, Copilot, and Perplexity. Brands that lead on Google AI platforms may benefit from search-visible content that Google's systems are more likely to retrieve, while brands that lead on conversational AI platforms may benefit from broader editorial and review coverage. Consistent performance across platforms requires source-layer strength that is broad rather than concentrated in a single channel.

What Brands Need to Fix

Weak valid recommendation coverage. Brands like Teladoc and Amwell need to address the gap between mention presence and recommendation conversion. Appearing in AI answers without earning recommendation credit means losing patients at the decision moment. The fix is not to pursue more mentions. It is to improve the quality and framing of the source layer that AI systems synthesize.

Low Top 3 and Rank 1 presence. Even brands with moderate valid recommendation rates often appear outside the top three positions. Improving rank requires source-layer evidence that gives AI systems a basis for advancing a brand ahead of established alternatives. Comparison content, structured feature information, and authoritative third-party coverage are relevant here.

Poor decision-stage cluster coverage. Several brands with moderate consideration-stage performance collapse in the Telehealth Pricing, Cost, and Plans cluster. Teladoc drops from $86,247 in consideration value to $8,725 in decision value. Brands that lack clear, accessible pricing content are less likely to be recommended when patients ask direct cost questions.

Neutral or weak framing. LiveHealth Online and Lemonaid Health carry low net sentiment scores. Neutral framing does not disqualify a brand from mentions, but it significantly reduces the likelihood of positive recommendation credit. Improving framing requires a stronger source layer: better editorial coverage, more consistent patient review signals, and clearer positioning in comparison and directory content.

Thin source footprint. Brands with limited comparison coverage, weak review presence, or inconsistent entity information have less retrievable material for AI systems to work with. Strengthening the public evidence layer across editorial, review, forum, directory, and owned content is the foundational fix for under-recommended brands.

Inconsistent platform performance. Several brands perform well on one AI platform but poorly on others. Amwell achieves a 15.5 percent recommendation rate on ChatGPT but underperforms on Gemini and Google AI Mode. Platform-specific gaps suggest inconsistency in the source types those platforms prioritize, and addressing the source layer broadly tends to improve cross-platform consistency.

How CiteWorks Studio Helps

1. Map AI recommendation visibility. Track prompts, platforms, company presence, valid recommendations, Top 3 and Rank 1 performance, framing quality, and citation sources across the Online Doctors category and the specific buyer-stage clusters that matter most to your brand.
2. Identify the sources shaping AI answers. Find the editorial, review, forum, directory, comparison, and owned sources that appear to be influencing brand framing and recommendation positioning in AI responses across all measured platforms.
3. Build the citation architecture plan. Strengthen the public evidence layer so AI systems have more accurate, consistent, and persuasive source material to synthesize when constructing recommendations at the consideration, evaluation, and decision stages.

Commercial Takeaway

AI-led discovery is changing where patient shortlists are formed in the Online Doctors category. The June 2026 benchmark shows that two brands, PlushCare and Sesame, capture 70 percent of the modeled monthly AI recommendation value while the remaining eight brands compete for the rest. Established telehealth brands with strong unaided brand recognition are appearing in AI answers but are not being advanced as top choices, which means they are losing patients at the decision moment to brands with stronger citation architecture and better framing quality.

Brands can lose recommendation-stage visibility even when they are frequently visible in AI answers. The benchmark demonstrates this clearly in the Teladoc and Amwell data. Competitors can intercept demand in high-intent prompt clusters, and the evaluation and decision stages are where interception risk is highest. A patient who asks an AI system to compare telehealth options or identify the lowest-cost online doctor service is receiving a shortlist that the patient did not construct and that the brand being overlooked had no direct input into.

Traditional search and source visibility still matter because they contribute to the public evidence layer that AI systems retrieve and synthesize. Building stronger citation architecture, more consistent editorial and review coverage, and clearer pricing and comparison content creates a source footprint that serves both traditional search and AI recommendation systems. The opportunity is not to chase mentions. The opportunity is to improve recommendation-stage visibility at the buyer stages where patients are making decisions.

See Where AI Is Recommending Your Brand

The benchmark identifies which brands are winning AI recommendations in the Online Doctors category. The more important question for any brand in this space is where it stands relative to the leaders and what the source-layer evidence reveals about its recommendation risk.

CiteWorks Studio can show where your brand appears in AI responses, where competitors are being recommended instead, which prompt clusters carry the most commercial risk, which sources appear to be shaping AI answers, and what changes to the public evidence layer could improve your recommendation-stage visibility.

Request an AI Visibility Audit or AI Company Discovery Report to map your brand's current position in AI-generated shortlists across the Online Doctors category.

Benchmark Source

This analysis is based on the 2026 AI Market Discovery Index for Online Doctors, published by LLM Authority Index. The full benchmark dataset and methodology are available through LLM Authority Index.