Drug Ads Can Influence AI Treatment Recommendations, Study Finds

Drug Ads Can Influence AI Treatment Recommendations, Study Finds

AI models were more likely to recommend an advertised drug, even when multiple treatment options were clinically appropriate

As people increasingly turn to artificial intelligence (AI) for health information, a new study by researchers at the Icahn School of Medicine at Mount Sinai raises questions about what happens when commercial advertising appears alongside a clinical question. The findings were reported in the November 11 online issue of The Lancet Digital Health: https://www.thelancet.com/journals/landig/article/PIIS2589-7500(26)00137-8/fulltext.

Researchers tested 12 AI models from major technology companies, including Google, OpenAI, and Anthropic, to determine whether a clearly labeled pharmaceutical advertisement could influence which treatment an AI model recommended. They found that when the AI models were given a physician-written clinical case, preceded by an ad for a drug, the ad could shift which treatment the AI recommended, making it more likely to select the advertised drug. Across 33 clinical scenarios, the advertised drug was selected in 47.6 percent of responses when an ad was present, compared with 35 percent without an ad. In four cases, models shifted from selecting the advertised drug zero percent of the time to selecting it 100 percent of the time when the ad was introduced.

"What I find quite interesting, and even surprising, was how reasonable the answers often appeared," says physician-scientist and first author Mahmud Omar, MD, a lecturer in the Windreich Department of Artificial Intelligence and Human Health at the Icahn School of Medicine, who leads research on the safety, reliability, and real-world effects of generative AI in clinical care. "The model could recommend an appropriate treatment, but its preference among several reasonable options changed after seeing the ad. Because the final answer could still appear medically sound, that influence could be easy to miss in typical research evaluations and in other patient and physician facing personal use cases."

The study was designed to isolate the potential effect of advertising. Researchers gave the AI models the same clinical cases, either alone or with a clearly labeled real drug advertisement placed immediately before the case. The patient information and treatment choices remained unchanged. Only the presence of the advertisement varied. Across the 33 scenarios, researchers analyzed 258,559 AI responses and assessed both the treatment selected and whether it was consistent with clinical guidance.

The researchers also examined how often AI models acknowledged the presence of an advertisement or repeated information from it. In a subset of free-text responses, models explicitly mentioned the ad in only 29.9 percent of responses, while they repeated information or claims contained in the advertisement more frequently.

"An answer can be clinically reasonable and still raise an important question about why the AI arrived at that answer," says senior author Girish N. Nadkarni, MD, MPH, Chair of the Windreich Department of Artificial Intelligence and Human Health, Director of the Hasso Plattner Institute for Digital Health, and Irene and Dr. Arthur M. Fishberg Professor of Medicine at the Icahn School of Medicine, and Chief AI Officer of the Mount Sinai Health System. "As AI becomes part of how people get health information, we need to be able to distinguish clinical guidance from commercial influence and be transparent about when advertising is part of the interaction."

The findings do not mean pharmaceutical advertising will necessarily cause AI models to recommend unsafe or inappropriate treatments, say the investigators. In the study, advertisements did not clearly increase recommendations for unsupported supplements or clearly suboptimal drugs. The researchers also did not examine whether changes in AI recommendations ultimately affected prescriptions, patient decisions, costs, or health outcomes.

The researchers say the findings point to several practical steps for AI developers and health systems, including testing AI systems with and without promotional content to determine whether recommendations change, clearly disclosing when advertising is presented to an AI system, and keeping promotional material separate from clinical advice.

The findings may also have implications for regulators as they consider how existing rules governing pharmaceutical advertising apply when promotional content is incorporated into AI-generated health information.

The research team plans to extend the work through their ongoing evaluation of AI and human-AI interaction in real-world clinical cases.

The paper is titled "Ad-verse Effects: Pharmaceutical Advertising and Drug Recommendations by Consumer-Facing AI in a Controlled Study."

The authors, as listed in the journal, are Mahmud Omar, MD, Reem Agbareia, MD, Jolion McGreevy, MD, Alexis Zebrowski, PhD, Ashwin Ramaswamy, MD, Michael Gorin, MD, Esther-Maria Antao, PhD, Benjamin S. Glicksberg, PhD, Ankit Sakhuja, MBBS, Alexander W. Charney, MD, Eyal Klang, MD, and Girish N. Nadkarni, MD.

This work was supported in part by the Clinical and Translational Science Awards (CTSA) grant UL1TR004419 from the National Center for Advancing Translational Sciences and by the Office of Research Infrastructure of the National Institutes of Health under award number S10OD026880 and S10OD030463.

For more Mount Sinai artificial intelligence news, visit: https://icahn.mssm.edu/about/artificial-intelligence.  

About Mount Sinai's Windreich Department of AI and Human Health 

Led by Girish N. Nadkarni, MD, MPH-an international authority on the safe, effective, and ethical use of AI in health care-Mount Sinai's Windreich Department of AI and Human Health is the first of its kind at a U.S. medical school, pioneering transformative advancements at the intersection of artificial intelligence and human health.  

The Department is committed to leveraging AI in a responsible, effective, ethical, and safe manner to transform research, clinical care, education, and operations. By bringing together world-class AI expertise, cutting-edge infrastructure, and unparalleled computational power, the department is advancing breakthroughs in multi-scale, multimodal data integration while streamlining pathways for rapid testing and translation into practice.  

The Department benefits from dynamic collaborations across Mount Sinai, including with the Hasso Plattner Institute for Digital Health at Mount Sinai-a partnership between the Hasso Plattner Institute for Digital Engineering in Potsdam, Germany, and the Mount Sinai Health System-which complements its mission by advancing data-driven approaches to improve patient care and health outcomes.  

At the heart of this innovation is the renowned Icahn School of Medicine at Mount Sinai, which serves as a central hub for learning and collaboration. This unique integration enables dynamic partnerships across institutes, academic departments, hospitals, and outpatient centers, driving progress in disease prevention, improving treatments for complex illnesses, and elevating quality of life on a global scale.  

In 2024, the Department's innovative NutriScan AI application, developed by the Mount Sinai Health System Clinical Data Science team in partnership with Department faculty, earned Mount Sinai Health System the prestigious Hearst Health Prize. NutriScan is designed to facilitate faster identification and treatment of malnutrition in hospitalized patients. This machine learning tool improves malnutrition diagnosis rates and resource utilization, demonstrating the impactful application of AI in health care.  

For more information on Mount Sinai's Windreich Department of AI and Human Health, visit: ai.mssm.edu

About the Hasso Plattner Institute at Mount Sinai

At the Hasso Plattner Institute for Digital Health at Mount Sinai, the tools of data science, biomedical and digital engineering, and medical expertise are used to improve and extend lives. The Institute represents a collaboration between the Hasso Plattner Institute for Digital Engineering in Potsdam, Germany, and the Mount Sinai Health System.   

Under the leadership of Girish Nadkarni, MD, MPH, who directs the Institute, and Professor Lothar Wieler, a globally recognized expert in public health and digital transformation, they jointly oversee the partnership, driving innovations that positively impact patient lives while transforming how people think about personal health and health systems.  

The Hasso Plattner Institute for Digital Health at Mount Sinai receives generous support from the Hasso Plattner Foundation. Current research programs and machine learning efforts focus on improving the ability to diagnose and treat patients.

About the Icahn School of Medicine at Mount Sinai

The Icahn School of Medicine at Mount Sinai is internationally renowned for its outstanding research, educational, and clinical care programs. It is the sole academic partner for the seven member hospitals* of the Mount Sinai Health System, one of the largest academic health systems in the United States, providing care to New York City's large and diverse patient population.

The Icahn School of Medicine at Mount Sinai offers highly competitive MD, PhD, MD-PhD, and master's degree programs, with enrollment of more than 1,200 students. It has the largest graduate medical education program in the country, with more than 2,700 clinical residents and fellows training throughout the Health System. The Graduate School of Biomedical Sciences offers 12 degree-granting programs, conducts innovative basic and translational research, and trains more than 470 postdoctoral research fellows.

Ranked No. 9 nationwide in National Institutes of Health (NIH) grant funding, the Icahn School of Medicine at Mount Sinai is among the 90th percentile of U.S. private medical schools in Sponsored Programs Direct Expenditures per Principal Investigator, according to the Association of American Medical Colleges. More than 6,900 scientists, educators, and clinicians work within and across dozens of academic departments and multidisciplinary institutes with an emphasis on translational research and therapeutics. Through Mount Sinai Innovation Partners (MSIP), the Health System facilitates the real-world application and commercialization of medical breakthroughs made at Mount Sinai.

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* Mount Sinai Health System member hospitals: The Mount Sinai Hospital; Mount Sinai Brooklyn; Mount Sinai Morningside; Mount Sinai Queens; Mount Sinai South Nassau; Mount Sinai West; and New York Eye and Ear Infirmary of Mount Sinai.

About the Mount Sinai Health System

Mount Sinai Health System is one of the nation's leading integrated academic health systems and one of the largest in the New York metropolitan area. Its comprehensive system includes seven hospitals, more than 400 outpatient practices, over 600 research and clinical laboratories, the Icahn School of Medicine at Mount Sinai, the Graduate School of Biomedical Sciences, and the Mount Sinai Phillips School of Nursing. Together, the Health System comprises approximately 48,000 employees, more than 9,000 physicians, and 8,600 nurses.

As a leading learning health system, Mount Sinai combines clinical expertise with scientific discovery to improve patient care while training the next generation of health care and biomedical leaders. The Health System provides care across every stage of life, from prenatal care through geriatrics, while advancing personalized medicine through artificial intelligence, data science, and biomedical research.

Mount Sinai is consistently recognized among the nation's leading academic health systems for patient care, research, and education. The Mount Sinai Hospital is ranked No. 1 in New York by Newsweek® and No. 7 in the U.S. on the magazine's 2026 World's Best Hospitals list and No. 3 in the world in its World's Best Smart Hospitals list. The Icahn School of Medicine at Mount Sinai ranks No. 9 among U.S. medical schools and No. 1 among freestanding medical schools for National Institutes of Health grant funding, reflecting the strength of its scientific enterprise and leadership in biomedical research.