That small win reminded me that artificial intelligence is already shaping the way our patients (and our families) search for health advice. I believe that as clinicians, educators and supervisors, we are called to guide this shift. Below, I share three reasons why.

Three reasons why learning Artificial Intelligence in health care may be a responsibility and not an option:

1. Our Patients Are Already Using AI

Many people now ask their first health question to a chatbot rather than to a clinician. Traylor and colleagues (2025) show that generative‑AI tools can boost health literacy by translating medical jargon into plain language. Yet the same study warns of misinformation and the risk of eroding trust when answers feel generic or contradictory. As healthcare professionals we can:

• ask during history taking what the patient has already searched or generated with AI,
• clarify when an AI answer is helpful and when a live conversation is safer, and
• show patients how to write better prompts so they receive accurate, actionable advice.

The smoothie prompt above is a simple example. A personalized AI interaction turned a dietary goal into a recipe my daughter loved.

2. Bridging the 17‑Year Research–Practice Gap

Implementation scientists estimate that it takes about seventeen years for new evidence to become routine care (Rubin, 2023). AI has the potential to compress that timeline. Tools such as Elicit and SciSpace surface the most relevant papers in seconds. Notebook‑style assistants convert PDFs into bullet‑point digests or audio summaries you can review between patients. Also, a good prompt can return guideline‑consistent recommendations tailored to a patient’s age, culture and co‑morbidities.

This semester a graduate student of mine used an AI assistant to explore the link between high IQ and ADHD‑like symptoms. Within minutes he integrated the latest findings into practical recommendations for the family. Evidence‑informed care was literally at his fingertips.

3. Reclaiming Time and Attention

Primary care professionals may log more than eleven hours a day, over half of it in the electronic health record (Menchaca, 2025). Administrative overload fuels burnout and pushes us away from our patients. When used intentionally, AI can help us:

• draft progress notes or referral letters,
• suggest evidence‑based interventions or psycho‑educational handouts, and
• organize task lists, reminders and teaching materials so we can focus on patients and learners.

At a recent conference, a neurologist demonstrated an AI tool that captured and structured his clinical notes while he was able to be present and maintain eye contact with the patient. For me, his excitement represented a glimpse of technology restoring, not replacing, the human connection at the heart of care.

Final Reflection

AI is not a magic wand, but it offers a possible path to more humane and evidence‑driven practice. If we stay passive, we run the risk of delegating the agenda to profit‑centered actors. By engaging now, critically and collaboratively, we can contribute to the development of tools that elevate patient wellbeing and clinician joy. How are you integrating AI into your clinical, teaching or supervisory work? 

References

Menchaca, J. T. (2025). For AI in Primary Care, Start With the Problem. Annals of Family Medicine, 23(1), 5–6.

Rubin, R. (2023). It Takes an Average of 17 Years for Evidence to Change Practice—The Burgeoning Field of Implementation Science Seeks to Speed Things Up. JAMA, 329(16), 1333–1336.

Traylor, D. O., Kern, K. V., Anderson, E. E., & Henderson, R. (2025). Beyond the Screen: The Impact of Generative Artificial Intelligence on Patient Learning and the Patient‑Physician Relationship. Cureus, 17(1), e76825.

Photo by Steve Johnson on Unsplash