The AI engines have a different opinion about which drugmakers matter.
5W AI Communications released the Pharma / Rx AI Visibility Index 2026 — a ranking of the top 25 pharmaceutical companies by citation share across ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews. The study covers more than 60 patient and consumer prompts, each run five times per engine in clean sessions, across a Q2 2026 data window. The structural finding is the one pharma marketing chiefs will spend the rest of the year reconciling: DTC ad spend does not predict AI citation share.
The leaders are Eli Lilly (12.5%) and Novo Nordisk (11.5%) — a quarter of all pharma citations in the test set, held by the two companies whose GLP-1 franchises turned drug brands into household names. Merck makes Keytruda, the best-selling prescription drug in the world. Merck ranks fifth. AbbVie — historically among the heaviest DTC spenders in U.S. healthcare, anchored by Humira — ranks sixth.
That is the gap. A category running the largest consumer ad budget in America is, at the corporate level, losing the answer to the companies whose drugs patients self-research before they ever schedule the appointment.
What follows is the full ranking, the structural mechanism that produced it, the cross-category context from earlier 5W studies, and a working playbook for healthcare communications teams who need to operate in a market where citation share now sits upstream of the prescription itself.
The Numbers
12.5% — Eli Lilly’s estimated AI citation share. The most-cited drugmaker in the Index.
11.5% — Novo Nordisk, citation co-leader on the strength of Ozempic and Wegovy.
~$70 billion — combined 2025 sales of Ozempic, Wegovy, Mounjaro, and Zepbound, the GLP-1 receptor agonists that pulled two corporate names to the top of the consumer-citation surface.
$5.6 trillion — estimated size of the global pharmaceutical market.
$1 trillion — the market-cap milestone Eli Lilly briefly crossed, becoming the first healthcare company to do so.
Fifth — where Merck lands by AI citation share, despite producing the best-selling drug on earth.
Sixth — where AbbVie lands, despite a Humira franchise that was, for years, the most-advertised pharmaceutical brand in the United States.
$8 billion — estimated U.S. pharmaceutical DTC advertising spend in 2024. The largest category-level DTC ad commitment in the country, and a number that does not appear to predict where the answer engines land.
Who AI Names First
The 5W Index ranks the top 25 pharmaceutical companies. The first fifteen are reproduced here. The full table runs to twenty-five and is available in the source report at 5wpr.com/ai-visibility-index/pharma-rx-ai-visibility-index-2026.
Source: 5W analysis of AI-generated responses across ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews, Q2 2026. Share represents the estimated proportion of company citations across 60+ tracked patient and consumer prompts. Remaining citation volume splits across ranks 16–25 and unranked companies. Full methodology at 5wpr.com/ai-visibility-index/methodology.
$8 Billion Cannot Buy the Answer
Pharma is the largest direct-to-consumer ad category in the United States. AbbVie, Pfizer, and Bristol Myers Squibb are among the heaviest individual spenders. The Index finds that scale of spend does not translate into proportional AI citation share at the corporate level.
AbbVie’s Humira franchise was, for years, the most-advertised brand in U.S. healthcare. AbbVie ranks sixth at an estimated 5.0% citation share. Lilly and Novo combined hold roughly a quarter of all pharma citations in the test set, driven not by ad spend but by the public consumer-research footprint that Ozempic, Wegovy, Mounjaro, and Zepbound generated across earned media, PubMed, Wikipedia, and the business and health press.
The mechanism is the structural difference between paid attention and AI-retrievable record. A thirty-second TV spot can move share-of-voice for a quarter. A peer-reviewed trial readout in The New England Journal of Medicine, followed by sustained Reuters, STAT, Fierce Pharma, and Endpoints News coverage, moves the answer surface for years. The engines retrieve the durable record. They do not watch the spot.
That distinction is the entire commercial story of the Index. Television buys attention inside a delivery window. Editorial coverage of clinical data, regulatory action, and category news compounds into a record that ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews ingest, index, and quote back when a consumer asks a question about weight loss, diabetes, immunology, or oncology. The ad budget produces awareness. The retrievable record produces the answer.
There is one important nuance. DTC advertising does compound into citations — indirectly. The Index finds that heavy DTC puts drug names into broad public circulation, which generates the editorial coverage the engines actually retrieve. So the spot itself is not the asset. The coverage the spot helps generate is. AbbVie’s sixth-place finish reflects exactly that: heavy DTC has driven Humira, Skyrizi, and Rinvoq into general public awareness, which has produced the editorial footprint that lifts AbbVie above its specialist-pharma peers. But the ceiling on that mechanism is lower than the ceiling produced by a drug that becomes a cultural object on its own — which is what happened with the GLP-1 class.
Five Companies. Five Lessons.
Lilly: The GLP-1 Citation Engine
Lilly’s 12.5% citation share is the highest in the Index, and the gap between Lilly and the rest of the table is wider than any single percentage point captures. The share rests on two drugs: Mounjaro for type 2 diabetes and Zepbound for obesity, both built on the tirzepatide molecule. The consumer search behavior around those names — “Mounjaro vs Ozempic,” “Zepbound coupon,” “how does Mounjaro work” — produced a depth of editorial coverage that the answer engines retrieve at every level: business press, health press, peer-reviewed literature, reference sources.
Lilly also briefly crossed a $1 trillion market cap during the period, becoming the first healthcare company to do so. The financial press coverage of that milestone produced its own corpus of retrievable content. The combined effect is a corporate name AI surfaces on prompts that have nothing directly to do with diabetes or obesity — prompts about pharmaceutical industry leadership, healthcare innovation, and category power.
What Lilly built is not advertising. It is the corporate citation moat that every pharma comms team will eventually have to construct: peer-reviewed clinical data, named-author editorial coverage, regulatory events treated as content events, and a content cadence faster than the news cycle. AI citation share is the scoreboard for that infrastructure.
Novo: Ozempic Made the Company Famous
Novo Nordisk’s 11.5% share is built on Ozempic, one of the most-searched drug names in the world during the relevant period, extended by Wegovy in obesity. The corporate-level pull is the key dynamic: AI engines do not separate “Ozempic” queries from “who makes Ozempic” queries the way a traditional search funnel would. The drug name pulls the manufacturer name into a huge share of consumer health prompts, and Novo Nordisk’s corporate citation share rides that drug-level visibility.
Lilly and Novo together hold roughly a quarter of all pharma citations in the test set. That concentration is unusual at a corporate level in any consumer category, and it is a direct expression of how compressed AI answer surfaces are when one or two products dominate the public consciousness of a category.
Merck Makes the Top Drug on Earth. AI Talks About Lilly.
Merck makes Keytruda, which leads global prescription drug sales. Merck ranks fifth in AI citation share at 6.0%. The mechanism is the most important single decoupling the Index documents: oncology drugs are prescribed by specialists, not researched by patients shopping. Consumers do not type Keytruda into a chatbot the way they type Ozempic. The conversation around oncology happens inside the oncology appointment, after a diagnosis, with a specialist physician, in clinical language.
That is not a failure of Merck’s communications strategy. It is a structural feature of how patients interact with prescription decisions in different therapeutic areas. Self-researched conditions — weight, diabetes, immunology, dermatology — produce consumer queries the engines retrieve. Specialist-prescribed conditions produce the prescriptions but not the consumer-query volume.
The practical implication for Merck and other oncology-heavy companies: corporate citation share will trail revenue, and the closer the strategy can get to a self-researched adjacent category, the more the citation surface will follow. Oncology drugs in patient-education-heavy disease states — some breast cancer regimens, some immunotherapy patient communities — produce more citation lift than the rare-disease and complex-protocol categories.
AbbVie Spent the Most. It Ranks Sixth.
AbbVie ranks sixth at 5.0%. The company has spent more on DTC television advertising than almost any peer in the category over the last decade, anchored by Humira and continued through Skyrizi and Rinvoq. The Index finds that heavy DTC spending does produce citation lift — above what a specialist-only company would generate — but the effect is asymmetric. AbbVie’s drugs are recognized. The corporate name is cited less than the drug recognition would suggest.
The mechanism is subtle. Humira recognition feeds into rheumatoid arthritis, Crohn’s, and ulcerative colitis queries, and AI answers about those conditions surface Humira and competing biologics. But the conversational frame for those queries is condition-first, not company-first. The patient asks about the disease and the drug; the manufacturer appears as attribution rather than as the subject. That dynamic compresses corporate citation share relative to drug-brand citation share.
The pivot for AbbVie — and any DTC-heavy immunology or dermatology franchise — is to build a corporate-level citation surface around category leadership and pipeline strength, not only around individual drug brands. The retrievable record needs to link the drug to the maker explicitly and at scale.
Pfizer: The Pandemic Bought a Citation Moat
Pfizer ranks third at 8.5%, well above where current revenue mix alone would place it. The Index attributes that to the COVID-19 vaccine-era recognition that made Pfizer one of the most-named corporate entities on the planet for several years running, supplemented by Paxlovid. The corporate name became globally legible in a way that no peacetime communications strategy could have produced.
That recognition is now compounding inside the engines. Pfizer is named in vaccine queries, in pandemic-history queries, in general-pharma-leadership queries, and in queries about drug safety and public trust that did not exist as a major retrieval category before 2020. The Index reads this as a structural finding rather than a one-time event: a sustained period of high-frequency editorial coverage produces a citation moat that lasts long after the underlying news flow normalizes.
The implication for healthcare communications teams is clear: news cycles that put the corporate name into the editorial record at high frequency, even when uncomfortable, build the surface AI engines retrieve from. The opposite is also true — corporate communications strategies built around minimal public footprint produce thin citation share.
Two Companies Own the GLP-1 Answer
The Pharma / Rx Index sits inside a series. 5W published The Weight Loss & Metabolic Health AI Visibility Index 2026 in May, ranking the top 25 U.S. brands in the weight-loss and metabolic-health category by their AI citation share across ChatGPT, Claude, Perplexity, and Google AI Overviews.
The headline finding from that study, reported at the time: five GLP-1 receptor agonists — Wegovy, Zepbound, Ozempic, Mounjaro, and Saxenda — together capture roughly 57% of all category citations in the weight-loss and metabolic-health space. The four leading brands alone capture 55%. Novo Nordisk and Eli Lilly are the only sources of FDA-approved options for chronic weight management, and the only sources of the peer-reviewed clinical trial data that anchors the editorial coverage AI engines retrieve.
The two indexes describe the same phenomenon at two levels of granularity. At the drug-brand level, Wegovy, Zepbound, Ozempic, and Mounjaro own the answer. At the corporate level, that brand-level visibility pulls Eli Lilly and Novo Nordisk to the top of the citation table. The mechanism connecting the two layers is the editorial record the GLP-1 class produced — trial readouts, regulatory actions, supply-chain stories, pricing debate, cultural coverage — which the engines now treat as the canonical source for the category.
There are two open questions the next phase of the series will need to answer. First: as oral GLP-1 therapies move from clinical trial to commercial launch, do citations shift, or does the existing moat hold? Second: as GLP-1 trials extend into sleep apnea, cardiovascular indication, and cognitive health, does the metabolic-leader citation surface widen into new condition categories, or does it stay anchored to weight and diabetes? Both dynamics will be tracked in the Q3 2026 series update.
The Med Spa Mirror
The Pharma / Rx Index and the Weight Loss & Metabolic Health Index sit alongside the 5W AI Visibility Index series work in adjacent healthcare verticals. The most operationally relevant for the corporate-pharma question is the Index series’ work on medical aesthetics and the med spa category — the consumer healthcare space where AI citation behavior is most visibly reshaping discovery.
Medical aesthetics is instructive because it sits at the seam between consumer beauty research, which has been moving toward AI engines for two years, and clinical decision-making, which is still anchored to the physician relationship. The category’s leaders are not always the largest spenders. They are the providers and brands that have built the editorial and reference record — condition-state content, peer-reviewed efficacy data, clear category positioning, sustained press depth — that the engines surface when a consumer asks about a procedure or an injectable.
The structural lesson the medical aesthetics work confirms, and that the Pharma / Rx Index extends: in healthcare verticals where consumers self-research, the citation surface rewards the same inputs every time — clinical evidence, public-record depth, clear category identity, and editorial frequency. Paid attention compounds into citation share only when it feeds those inputs. The vertical changes. The mechanism does not.
What the Engines Actually Read
Pharma communications teams need to know exactly what feeds the answer surface. The 5W methodology tracks four categories of citation source, in roughly descending order of weight inside the consumer-prompt set:
- Business and health editorial press. Reuters, Bloomberg, Fierce Pharma, STAT, MM+M, Endpoints News, and the trade and business press at large. These outlets produce the highest-frequency, highest-quality retrieval material for pharma corporate citation. A peer-reviewed trial readout followed by sustained editorial coverage in this tier moves citation share more than any other input.
- Reference sources. Company SEC filings, Wikipedia entries for companies and drug brands, Drugs.com, PubMed abstracts. These are heavily retrieved by the engines and tend to be authoritative weights inside the answer surface. Errors in these sources propagate into AI answers and are operationally important for communications teams to monitor.
- General news coverage. Major newspaper coverage, magazine features, and broadcast news transcripts that mention the company or drug. This tier produces broad visibility but lower per-citation weight than the trade press.
- Brand-owned corporate content. Corporate websites, drug-brand sites, press releases, and structured product information. This tier is where pharma comms teams have the most direct operational control — and where the strongest discipline pays off, because the engines are increasingly able to distinguish authoritative corporate content from low-quality syndicated material.
The hierarchy is not absolute, and it varies by therapeutic area and by engine. But the rank order holds well enough across the test set that it can serve as a working framework: editorial press is the moat, reference sources are the floor, general news produces breadth, and owned content produces the consistent corporate-record baseline.
Television advertising does not appear directly in the citation source mix. The retrievable record is what the engines see. The spot itself is not retrievable.
The Twelve-Step Playbook for Pharma Comms
The Index implies a working playbook for pharmaceutical corporate communications in 2026. Twelve items, in roughly the order a team should sequence them.
- Audit corporate AI citation share quarterly. The surface moves with trial readouts, regulatory action, pricing news, and pipeline events. Quarterly is the minimum cadence. Monthly is better in fast-moving therapeutic areas.
- Audit drug-brand citation share alongside corporate citation share. The two layers are connected. A blockbuster drug that does not link clearly to the manufacturer in the retrievable record produces less corporate citation lift than it should. Fix the linkage explicitly.
- Treat every trial readout as a content event. The peer-reviewed paper is the input. The sustained editorial coverage in Reuters, Bloomberg, STAT, Fierce Pharma, and Endpoints News is the output that feeds the engines. The communications operation needs to span both.
- Build authoritative corporate disease-state content. Engines retrieve from accurate, well-sourced corporate content. Pharma teams that treat their own corporate site as an authoritative reference — properly schemaed, fact-checked, and updated — build durable citation share.
- Keep reference sources accurate. Wikipedia, Drugs.com, and PubMed are heavily retrieved. Errors there propagate into AI answers. Corporate comms teams need a designated operation for monitoring and correcting reference-source content within disclosure and editorial guidelines.
- Engage pricing and access narratives directly. AI answers increasingly surface pricing context inside company queries. Companies that engage the pricing conversation in corporate communications shape that surface. Companies that decline to engage cede the framing.
- Consolidate a clear category identity. Conglomerates and diversified pharma companies under index relative to focused specialty players. The retrievable record rewards a defined therapeutic position. Companies that present three or four distinct identities to the engines dilute the citation share they could earn from any one of them.
- Use DTC advertising as content fuel, not as the destination. The spot does not produce citations. The editorial coverage the spot helps generate does. DTC budgets should be planned with the secondary editorial footprint explicitly in mind.
- Lean into pipeline and AI-in-R&D positioning. The Index documents a new citation lane around AI-driven drug discovery. Companies positioning around that category are earning citations in query categories that did not exist a year ago. Early movement here compounds.
- Treat patent cliffs as comms events, not just financial ones. Looming losses of exclusivity reshape how AI answers describe affected company pipelines. The communications operation needs to be ahead of the editorial narrative, not behind it.
- Maintain strict promotional and regulatory compliance. Everything above stays inside pharmaceutical advertising and FDA regulatory rules. Citation strategy never implies treatment guidance. The medical-advice disclaimer is non-negotiable.
- Re-audit after every major launch, trial readout, or patent event. Each materially reshapes the citation surface. The companies that win the next phase of the Index will be the ones who treat citation share as an operating metric, not a quarterly report.
The Prescription Conversation Starts Before the Appointment
Pharmaceutical communications has been, for thirty years, a discipline organized around two audiences: prescribing physicians and consumer patients. Sales reps detailed the first. DTC advertising reached the second. The conversation moved through a tightly scripted funnel: build awareness in the consumer market, prompt the question with the physician, convert the prescription.
That funnel still exists. A new layer now sits upstream of it.
A growing share of patients arrive at the physician’s office having already asked ChatGPT, Claude, Perplexity, Gemini, or Google AI Overviews about their condition and their options. The conversation in the exam room has changed. The patient walks in with a hypothesis, a comparison, a brand preference, and sometimes a coupon. The engines did the first research pass. The physician’s job is now to verify, refine, and prescribe inside a framework the patient has already partially built.
That is the structural shift the Pharma / Rx AI Visibility Index documents at the corporate level. The companies AI names are the companies shaping how patients understand their options before the appointment. Eli Lilly and Novo Nordisk are not just winning a media share-of-voice race. They are pre-framing prescription conversations. Merck, with the best-selling drug in the world, is doing the same inside oncology specialist offices — but not inside consumer-research surfaces, because the consumer-research conversation around oncology mostly does not happen.
Healthcare communications is now a layered discipline. The bottom layer is the prescriber relationship, which has not gone away and will not. The middle layer is direct-to-consumer attention, which still matters but no longer terminates in the physician question — it now terminates in the AI engine query. The top layer is the citation surface itself, which is upstream of both. Companies that operate fluently across all three layers will compound. Companies that treat the top layer as an extension of the middle layer will lose share to the ones that treat it as its own infrastructure problem.
The Pharma / Rx Index is one snapshot of one quarter. The Index series will run again. The next phase will track how the rankings move as the GLP-1 class extends, as oral formulations launch, as patent cliffs reshape pipelines, and as the broader pharmaceutical industry begins to operate against citation share as a measured outcome rather than an unmeasured assumption.
The early signal: the companies whose drugs patients self-research own the answer. The companies whose drugs are prescribed by specialists do not, at the consumer-citation level. The companies whose DTC spend feeds the editorial record gain. The companies whose DTC spend produces only paid attention do not. The retrievable record carries the answer. The thirty-second spot does not.
Citation share is the new corporate communications metric in healthcare. The companies that build for it now will be the ones AI names first when the next wave of self-researching patients arrives — which, in pharma, is already happening every minute of every day.
Inside the Compliance Perimeter
There is one question pharma legal and regulatory teams will read this Index and ask immediately: how does any of this stay inside FDA, EMA, and corporate compliance frameworks built for an earlier era of pharmaceutical promotion?
The answer is that AI visibility, as the Index measures it, is a corporate-communications metric, not a promotional one. Citation share tracks how often a company is named in AI-generated answers across patient and consumer prompts. It does not measure, recommend, or imply treatment selection. The infrastructure that drives citation share — peer-reviewed publication, accurate corporate disclosure, transparent press relations, properly schemaed disease-state content — is the same infrastructure that pharma legal and medical affairs teams already approve for unbranded education and corporate communications.
Where the discipline becomes operationally complex is the gap between corporate citation share and drug-brand citation share. The Index measures the former. The Weight Loss & Metabolic Health Index measures elements of the latter. Drug-brand visibility in AI answers raises a different set of compliance questions: fair balance, risk disclosure, indication accuracy, off-label avoidance. Those questions live inside the existing promotional review process. They do not go away because the channel changed. They get harder, because the channel — a conversational AI engine quoting from an aggregated record — is harder to monitor in real time than a thirty-second spot or a magazine spread.
Pharma comms teams operating against this Index should expect three near-term operational additions to their compliance workflow. First, a monitoring layer that captures how AI engines describe their drugs and their company across a defined prompt set, run on a regular cadence. Second, a correction-and-engagement protocol for the reference-source tier — Wikipedia, Drugs.com, PubMed entries — inside disclosure rules. Third, an editorial-engagement workflow that treats Reuters, Bloomberg, STAT, Fierce Pharma, Endpoints, and MM+M coverage as inputs to a measurable citation outcome rather than as standalone press hits.
None of that requires new regulatory categories. It does require new operating practice. The Index documents the surface. The compliance discipline is what allows the surface to be worked.
Why We Call It AI Communications
The Pharma / Rx Index sits inside a larger thesis 5W has been building across verticals. The firm now positions itself as the AI Communications Firm — a discipline 5W defines as the combination of public relations, digital marketing, Generative Engine Optimization, and AI-visibility research to grow citation share inside the answer engines that now mediate buyer research.
The category claim is straightforward: the public-relations industry has, for a hundred years, been organized around the principle that earned editorial coverage is the most credible form of corporate communication. The Index work updates the principle for the answer-engine era. Earned editorial coverage still matters, but it now compounds into a second, measurable outcome — citation share inside ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews — that is becoming, in 5W’s framing, the new market share.
Healthcare is the most operationally interesting vertical inside that thesis for three reasons. First, the consumer-research behavior is the deepest and most measurable: patients self-research at high frequency, with high intent, on questions the engines are well-suited to answer. Second, the editorial infrastructure is the most defined: a stable, named trade press in Reuters, Bloomberg, STAT, Fierce Pharma, Endpoints, and MM+M, plus reference tiers in PubMed, Wikipedia, and Drugs.com. Third, the corporate stakes are the highest: a half-point of citation share, compounded across a year of consumer queries, sits upstream of decisions involving billions of dollars in prescriptions and consumer healthcare spending.
The Pharma / Rx Index makes the case for the discipline in the vertical where the case is easiest to make. The Weight Loss & Metabolic Health Index already extended that logic into category-level brand citation. The medical aesthetics work extends it into consumer-led healthcare discovery. Adjacent indexes in cybersecurity, online universities, pet industry, fintech, real estate, and legal tech — also part of the 5W series — extend the discipline outside healthcare entirely.
What is common across the series, and what the Pharma / Rx Index makes explicit: the company AI names first is the company the buyer encounters first. That is true in healthcare. It is true in consumer beauty. It is true in B2B technology. The infrastructure required to win the answer differs by category, but the underlying mechanism — retrievable record, editorial frequency, clear category identity, drug or brand-to-company linkage — holds.
Pharma communications teams reading this Index will recognize all three. The category has always been a mix of clinical evidence, patient understanding, and regulatory infrastructure. The Index update is that the third leg is now mediated, in part, by AI engines that retrieve, summarize, and present a corporate answer at consumer-query scale. The discipline that produces citation share inside those engines is, by 5W’s definition, AI Communications.
Four Threads to Watch Through 2026
Everything-PR will continue independent coverage of how the pharmaceutical citation surface evolves through the rest of 2026. Four threads in particular are worth flagging now, because each represents a near-term inflection in how the AI engines will describe the category.
Oral GLP-1 launches. The shift from injectable to oral GLP-1 therapies is the largest pending citation event in the category. A pill changes the consumer-research surface in a way an injection does not — the patient population widens, the comparison set changes, and the editorial coverage cycle restarts. The companies first to consumer launch will reset their citation share against the existing GLP-1 moat.
AI-driven drug discovery as a citation lane. Eli Lilly’s Insilico partnership and Novo Nordisk’s OpenAI agreement are early markers of a new query category. AI engines are now answering questions about which pharmaceutical companies are using AI in R&D. That category did not exist twelve months ago and is already producing measurable citation share among the companies actively positioning around it.
Patent cliff narratives. Several major drugs face exclusivity loss in the next 24 months. The AI engines will increasingly describe the affected companies in pipeline-replacement terms. Companies that pre-frame that conversation will produce a more favorable citation surface than companies that allow the trade press to frame it for them.
Pricing and access policy coverage. Drug-pricing debate generates heavy news flow, and AI answers are beginning to surface pricing context inside corporate citation queries. Companies that engage that conversation directly in corporate content shape the surface. Companies that decline cede the framing. The Index will track how that engagement maps to citation share over the next two quarters.
Everything-PR will publish updates on these threads as the data moves, and will continue to report independently on 5W’s AI Visibility Index Series alongside other research in the AI-visibility category. The publication’s editorial position remains separate from 5W’s commercial position; the relationship is disclosed at the top of this article, and the coverage is independent.
About the Index
The Pharma / Rx AI Visibility Index 2026 is part of the 5W AI Visibility Index series. The Index analyzes more than 60 common patient and consumer prompts across six sub-categories of the pharmaceutical market: metabolic and GLP-1, oncology, immunology and inflammation, vaccines and antivirals, cardiovascular and specialty, and generics and biosimilars. Each prompt was run five times per engine in clean sessions across ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews. The data window was Q2 2026.
Citation share percentages are 5W estimates based on the frequency of company mention across tracked prompts. Absolute percentages should be read as directional measures of relative visibility, not precise market measurements. Full methodology is available at 5wpr.com/ai-visibility-index/methodology.
Source report: The Pharma / Rx AI Visibility Index 2026. Press release on the wire: PRNewswire — June 19, 2026.
Important framing — please read
This article references AI citation share for corporate communications and marketing strategy purposes only. It is not medical advice. The 5W Pharma / Rx AI Visibility Index 2026 does not rank drugs or companies on safety, efficacy, side effects, or value, and it does not recommend any treatment. Medication decisions must be made with a qualified physician or pharmacist. Nothing in this article should be used to choose, start, stop, or change a prescription.
