For many patients, AI is not a novelty. It is a workaround. I know AI has been an instrumental part of my care journey with a complex chronic condition, so the obvious question is why patients are flocking to AI in their care journey.

Patients are using AI because it is fast, non-judgmental (it just feels private even though we all know it's not), and also because they want to check themselves before bothering anyone. Also, patients use AI because the care system is hard to enter. For example, if I schedule an appointment with a new specialist, it is not uncommon for it to take between three to six months. Delays in care mean I look for answers elsewhere while I wait for the critical next step. My challenges mirror those of many of your patients. In other words, the behavior often reflects friction in the system, not just curiosity about technology.

The Patient Use of AI - Looking at Pre-Visit Data & Insights

To understand why patients turn to LLMs before a consultation, look at the reality of the modern 15-minute visit:

1. The Clock Strain: Research shows clinicians interrupt patients within an average of 11 to 18 seconds of opening remarks. Patients feel immense pressure to state their case quickly and clearly before the clinical encounter moves on. This strain demands organization.

2. The "Curiosity Engine": Search engines historically yielded thousands of terrifying, disjointed links (driving "cyberchondria"). Generative AI acts as a nonjudgmental dialogue partner. It translates complex medical jargon into plain language and helps patients organize their thoughts without fear of sounding silly or wasting a clinician's time.

• 24–32% didn't tell their clinician when they didn't understand instructions.
• 36–45% held back so they wouldn't take up more of the clinician's time.
• 64–82% held back because they didn't want to be judged or lectured.

Source: https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2716996

3. The Data Explosion: Recent national data from Wolters Kluwer Health found that 42% of patients frequently or very frequently bring AI-generated information to their appointments. Furthermore, 70% of clinicians and patients agree that AI can dramatically improve patient health literacy and engagement.

Patients aren't trying to challenge clinical authority; they are trying to gain legibility.

The main reasons patients use AI first

• Speed & Accessiblity. Patients want quick answers while they are deciding what to do next.
• Privacy. Some questions feel easier to ask a chatbot than a clinician, friend, or family member.
• Access friction. Patients may be facing long waits, appointment barriers, or cost pressure.
• Pre-visit research. Many want to understand symptoms or treatment options before they contact a provider.

These challenges are often exacerbated for those finding it the most difficult to enter the healthcare system, such as those in marginalized groups. Their numbers show they are among the largest groups flocking to AI.

KFF found that quick or immediate advice is a major reason people use AI for health information, and that many users are trying to decide whether they need to see a provider. Pew found that speed is a major motivation as well. Rock Health adds an important detail: many users do not stop with AI; they later consult a provider.

Why that matters for hospitals and clinics

If AI is helping patients work around friction, then AI use is a signal. It means the patient experience is leaving gaps that a chatbot can fill faster than the system can.

That does not mean AI is bad. It means health systems should ask what problem AI is solving for the patient. Often the answer is one of these:

• they could not get care fast enough
• they did not want to share something sensitive
• they wanted a second opinion before acting
• they wanted to avoid wasting time or money

What to do with that insight

Organizations should not treat AI use as a side issue. They should treat it as feedback about access, communication, and trust.

Practical responses include faster explanation of test results, better visit-prep language, more visible patient education, and clearer advice on when a symptom needs clinical review.

Related reading

• Adoption vs. Trust: Clinicians Lean In; Patients Stay Cautious
• How to Talk To Your Patient About AI
• Healthcare AI Governance Is a Sovereignty Problem, Not a Compliance Problem

Sources: KFF, Pew Research Center, Rock Health.