Gen Z, ChatGPT Health, and the 15-minute visit: A new counseling playbook
Industry Buzz
What I'm really concerned about is the idea of turning over our agency to these AI models. We should be aware that they are still fallible, and clinicians and patients always need to be the final arbiters of care, not computers.
—Dhruv Khullar, MD
Symptom checkers and health chatbots are no longer fringe tools; they are embedded in many patients’ everyday lives. For healthcare providers, this signals a fundamental shift: Increasingly, patients arrive to your office after consulting a chatbot, forming interpretations of their symptoms, and developing expectations about diagnosis and next steps.[]
While AI can’t replace clinical judgment, it’s already shaping patient perceptions and behavior. The ability to recognize this influence, and to adapt counseling strategies accordingly, is essential.
Related: AI and malpractice risk: Are you exposed?Clinicians have long navigated the downstream effects of internet-based health searches. WebMD, online forums, and social media have frequently amplified worst-case scenarios, fueling patient anxiety, and left clinicians to spend visit time devoted to correcting misinformation.
As AI becomes a more commonly-cited resource among patients, it’s important to understand how it’s helping (and hindering) valuable time in the clinic.
It feels conversational and personalized: Patients are no longer passively consuming static information. They can ask follow-up questions, refine symptom descriptions, and receive tailored responses that feel individualized.
It sounds confident and authoritative: Even when information is incomplete or incorrect, AI often communicates with clarity and certainty. These are qualities that can be highly persuasive to patients.
It is available 24/7: Patients may disclose symptoms or concerns to AI that they hesitate to share with clinicians, particularly in areas involving mental health, sexual health, or social stigma.
While patients may arrive at appointments more informed, they may also arrive more anxious, firmly anchored to a specific diagnosis, or falsely reassured about the seriousness of their condition.
What to expect in the clinic
Earlier presentation for some patients
AI tools may prompt earlier care-seeking, particularly when red-flag symptoms are highlighted, not unlike WebMD and other web-based symptom checkers.
This is particularly true for younger patients, as 66% of Gen Z patients have indicated their use of AI tools for symptom checking and nearly one in three Americans say they would delay seeking medical care if an AI tool indicated their symptoms were low-risk.[] Clinicians may increasingly hear statements such as, “The AI said I should get this checked urgently,” which should be acknowledged rather than dismissed.
Delayed care for others
Reassurance from AI can foster false confidence. Patients may delay evaluation after hearing, “It’s probably stress,” or “Home care should be enough.” Because AI lacks physical examination, diagnostic testing, and clinical context, such reassurance may delay assessment of evolving or atypical presentations.
Workflow strategies
Clinicians can adopt various practices to integrate AI into their interactions with patients.[]
Ask about AI use without judgment: Discussions about AI should be normalized, much like conversations about supplements or alternative therapies. Simple prompts such as, “Have you looked anything up or used any tools to learn more about this?” or “Did anything you read stand out to you?” can open dialogue and surface misconceptions early.
Validate the behavior, not necessarily the conclusion: Patients are not wrong for seeking information; in many cases, they are actively engaging in their own care. Statements such as, “It makes sense you’d want to understand this better,” or “I’m glad you’re asking questions,” help build rapport. Clinicians can then redirect the discussion toward what applies specifically to the individual patient.
Clarify what AI can—and cannot—do: Clinicians should emphasize that AI does not perform physical exams, and it relies on pattern recognition rather than clinical nuance. It may miss rare or serious conditions, and it does not assume professional accountability. Framing AI as a starting point for inquiry, rather than a diagnostic endpoint, helps preserve trust.
Reinforcing the value of doctor-patient relationships
Explicitly articulating the unique elements physicians bring to patient care, including physical examination, psychosocial context, and risk stratification, helps patients understand where AI ends and clinical care begins.
“In medicine, of course, patients don't always read the textbook before they come in with a particular medical condition,” Dhruv Khullar, MD, practicing physician and associate professor at the Weill Cornell School of Medicine, said in a recent Stanford Medicine podcast. “What I'm really concerned about is the idea of turning over our agency to these AI models. We should be aware that they are still fallible, and clinicians and patients always need to be the final arbiters of care, not computers."
A handy guide for your next patient visit
Patient: I asked ChatGPT Health about my symptoms. It said it might be X.
Physician: I’m glad you’re looking for information and trying to understand what’s going on. Tools like that can be helpful for general education, but they don’t replace medical care.
Patient: I trust it, because it's been right before.
Physician: An AI tool works from patterns in data. It doesn’t examine you, and it doesn’t know you. When I evaluate you, I’m not just matching symptoms to a list. I’m doing a physical exam, looking for subtle findings, considering your past medical history, your medications, your family history, and how this fits into your overall health over time. In medicine, patients don’t show up exactly like they do in textbooks. Real cases are messy. My job is to interpret the gray areas and adjust as new information comes in.