Your AI Health Advice May Be Influenced by Drug Ads, Study Finds

Commercial pharmaceutical advertisements can significantly alter which medical treatments artificial intelligence models recommend, even when systems clearly label the promotional content, according to new research from the Icahn School of Medicine at Mount Sinai.

As more people turn to AI for health information, Mount Sinai investigators examined how commercial advertising affects clinical questions. They published their findings in the November 11 online issue of The Lancet Digital Health.

How Drug Ads Sway AI Clinical Recommendations

The research team tested 12 AI models from leading technology firms, including Google, a subsidiary of Alphabet Inc. (NASDAQ:GOOGL), OpenAI and Anthropic.

Investigators gave the models 33 physician-written clinical cases, either alone or immediately preceded by a clearly labeled real drug advertisement.

Across 258,559 total responses, researchers kept patient details and treatment choices unchanged while varying only the ad’s presence, evaluating both treatment selections and adherence to clinical guidance.

When an advertisement appeared, AI models chose the promoted medication in 47.6% of responses, compared with 35% without an ad.

In four cases, models jumped from selecting the advertised drug 0% of the time to 100% once researchers introduced the ad.

Furthermore, in a subset of free-text responses, models explicitly acknowledged the advertisement in only 29.9% of answers, yet they repeated claims or details from the promotional material.

Guardrails Needed for AI Health Advice

Despite these shifts, investigators noted that drug ads did not clearly increase recommendations for unsupported supplements or clearly suboptimal drugs, meaning ads do not necessarily cause unsafe advice.

The team also did not examine whether recommendation changes affected prescriptions, patient decisions, costs, or health outcomes.

To protect clinical integrity, researchers urged AI developers and health systems to test models with and without promotional content, disclose when systems receive ads, and separate advertisements from clinical advice.

The findings also prompt regulators to evaluate how pharmaceutical advertising rules apply to AI-generated health information, as the team extends its ongoing evaluation of human-AI interactions in real-world clinical cases.

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