What Your Relationship With AI Will Actually Look Like in Three Years: Relationship, Oversight, and Workflow Mapped Out

I trained in emergency medicine. The ED is where I first learned that the most important clinical skill is not knowing the answer. It is knowing what we do not know, fast, and acting under uncertainty without freezing.

That instinct is exactly what physicians will need as agentic AI moves into daily clinical workflows. When I say agentic AI, I mean systems that do not just answer questions but initiate actions: drafting notes, flagging deteriorating patients, queuing orders, synthesizing longitudinal data before a clinician walks into the room. These are not future features. They are in production now, in clinics and hospitals across the country, and most physicians are navigating them without a clear frame for what the working relationship should actually look like.

I have spent the last several years working with these systems clinically, first as a user, then as a physician building physician-led, multi-agent clinical software for preventive medicine. What follows is what I actually expect the working day to look like three years from now, mapped across three dimensions: the relationship, the oversight, and the workflow.

This applies whether you work in emergency medicine, primary care, cardiology, a longevity practice, or any other corner of the house of medicine.

Relationship: The Attending-and-Resident Model

The single most useful frame I have found for working with agentic AI is the one every physician already knows: the attending-and-resident relationship.

AI is not a colleague, not a subordinate, and not an oracle. It is a capable, motivated, sometimes overconfident trainee that produces work product faster than any human, often knows the recent literature better than we do on a given Tuesday, and will occasionally tell us with full confidence that the patient in front of us needs a treatment that would harm them.

That is a resident. We have worked with that dynamic for over a century, and most of us have been that trainee ourselves. The structure is well understood. The trainee proposes, the attending decides, and the attending owns the outcome. The trainee does not get autonomy until competence is repeatedly demonstrated, and even then, the high-stakes decisions stay with the supervising physician.

This frame solves more than it gets credit for. It tells us when to trust (lower-stakes, high-frequency tasks where the system has shown consistent performance), when to push back (when the recommendation diverges from our clinical judgment), and where accountability sits (with us, every time). Residents grow. So will these systems. The relationship will evolve as competence accumulates, exactly as it does in training.

2025 PHYSICIANS AI REPORT

Access the Complete Report

✓Complete quantitative breakdown of what physicians really think about AI

✓Strategic implications for healthcare organizations and AI companies

✓Sentiment analysis of physician attitudes about AI and the future

Download full report

Oversight: Interrogation, Not Signature

Here is where our community needs to be honest with itself. The failure mode in three years will not be AI taking over. It will be physicians stopping to read.

I have seen this pattern up close. In building Longevitix, one of the earliest and most consistent problems we encountered was not that clinicians rejected AI-generated outputs. It was that they accepted them too quickly. A pre-visit brief generated at 7am, reviewed for four seconds before the patient walked in. A draft note approved without checking the assessment. A risk flag acknowledged and left unactioned because there was no workflow attached to it. Passive deferral is the real risk, and it is already here.

Research supports this. Studies show that physicians override between 90% and 96% of EHR-generated clinical alerts, and one analysis found that only 7.3% of medication-related alerts were clinically appropriate. When the signal-to-noise ratio is that low, clinicians stop reading on autopilot. That habit does not disappear just because the AI gets better.

Meaningful oversight looks like the way we already evaluate a consult note. We read it. We ask: does this clinical reasoning track? Does the recommendation match the patient in front of us, or a generalized version of them? What did this system not see? What is the differential we would consider that the algorithm did not surface?

The skeptic instinct is exactly the disposition our profession needs at scale. The clinicians who slow down, push back, and document independent reasoning are the ones who will define safe agentic medicine. We do not need fewer skeptics. We need skeptics who engage closely enough to catch what the systems miss.

Practically: when you override an AI recommendation, document the reasoning. Not "AI said X, I disagreed." A clinical sentence: "Given [patient-specific factor], elected to defer the recommended escalation pending [specific finding]." That is the documentation pattern that holds up to the patient, to the institution, and to a court.

Workflow: What the Day Actually Looks Like

Concretely, three years from now, the encounter structure will look like this for most of us.

Pre-encounter. An AI brief lands before the patient walks in. In an ED, that might be triage-flagged trends across boarded patients and a synthesized handoff from the prior shift. In primary care, it is the longitudinal trajectory: labs, vitals, adherence signals, anything new since the last visit. In the longevity and preventive practice where I now spend most of my time, this is where a platform like Longevitix surfaces the multi-domain picture: lipid trajectories including ApoB and Lp(a), wearable-derived autonomic signals, queued recommendations with the supporting reasoning attached. The brief is not the decision. It is the resident's pre-rounds presentation.

Intra-encounter. Clinical decision support triggers fire when relevant: a flagged interaction, a guideline mismatch, a missed screening, an out-of-range trend. The good systems are quiet by default and surface the right thing at the right moment. Our job is to acknowledge, accept, or override, and stay present with the patient. The encounter is still the encounter.

Post-encounter. The scribe captures the visit. A draft assessment and plan is generated, often with proposed orders and patient instructions attached. We read it the way we would read a resident's note, closely and with intent, and we edit. Documentation time drops. Reading time should not.

Three Years From Now

None of this requires becoming a system architect or a prompt engineer. It requires the same posture we already bring to clinical work: structured supervision, honest skepticism, clear ownership of the decision.

Medicine has used that frame for over a hundred years. It still works.

Download to join the waitlist

Medicine is complex enough.
Referrals shouldn't be.

Send and receive referrals, build wealth, and grow your physician community with Offcall.

Download on the

App Store

GET IT ON

Google Play