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Comparison · dataset August 2026

Emergency Medical Technician vs Registered Nurse: which is more exposed to AI?

Registered Nurse carries 11 points more AI exposure than Emergency Medical Technician.

Registered Nurse sits at 33% time-weighted AI exposure against 22% for Emergency Medical Technician, an 11-point gap driven by the 0% of registered nurse work time that current models can already substitute outright. Emergency Medical Technician holds a larger human-critical core — 80% of the role's time sits in work like "operate under hazards and time pressure" that models score poorly on. Both roles sit inside Healthcare, so the exposure difference reflects task design rather than a change of field.

11PP GAP

Seven dimensions, side by side.

METRICEMERGENCY MEDICAL TECHNICIANREGISTERED NURSEDELTA
AI exposure22%33%11pp gap
Resilience score91/10086/1005pt gap
Substitutable work time0%0%Fully automatable today
Human-critical work time80%70%Models score poorly here
Median salary$42k$81k$39k apart
10-year growth5%6%Registered Nurse
US workforce268k3.1MBLS OEWS
Task level

What actually creates the gap.

Both roles hand a similar slice of the week to substitutable work — 0% for Emergency Medical Technicians, 0% for Registered Nurses — but it is different work. Emergency Medical Technician exposure concentrates in "write patient care reports"; Registered Nurse exposure concentrates in "clinical documentation and charting". Two roles can share a score and face completely different disruption timelines.

Emergency Medical Technician
MOST EXPOSED TASKS
    HUMAN-CRITICAL CORE
    • Operate under hazards and time pressure4% · 8% time
    • Provide emergency medical interventions6% · 24% time
    • Transport patients safely10% · 12% time
    Registered Nurse
    MOST EXPOSED TASKS
      HUMAN-CRITICAL CORE
      • Emotional support and counseling6% · 3% time
      • Administer medications and treatments8% · 16% time
      • Emergency response and triage12% · 7% time
      What transfers

      Both roles lean on manual, social, judgement — that is the part of your experience that travels intact. Beyond that, the two capability profiles are unusually close: no dimension separates them by more than 15 points, which is why the switch difficulty below reads the way it does.

      Switching between them
      LowDIFFICULTY

      Registered Nurse appears in our dataset as a mapped adjacent career for Emergency Medical Technicians: the move raises exposure by 11 points, landing at 33%. Switch difficulty reads low — capability profiles are 6 points apart on average and both sit in the same family.

      Score your own exposure in 8 questions →

      Common questions.

      Is Emergency Medical Technician or Registered Nurse more at risk from AI?

      Registered Nurse. It scores 33% time-weighted AI exposure against 22% for Emergency Medical Technician — an 11-point gap. 0% of registered nurse work time is already fully substitutable by current models, versus 0% for Emergency Medical Technicians.

      Which pays more, Emergency Medical Technician or Registered Nurse?

      Registered Nurse, by roughly $39k at the median ($81k versus $42k). Note that the higher-paying role here is also the more AI-exposed one, which matters if you are weighing pay against durability.

      Can a emergency medical technician switch to being a registered nurse?

      Registered Nurse appears in our dataset as a mapped adjacent career for Emergency Medical Technicians: the move raises exposure by 11 points, landing at 33%. Switch difficulty reads low — capability profiles are 6 points apart on average and both sit in the same family.

      Which role is growing faster, Emergency Medical Technician or Registered Nurse?

      Registered Nurse, at 6% projected ten-year growth versus 5% — a 1-point difference. Growth and AI exposure are separate signals: a role can grow in headcount while the content of the work is substantially rewritten.

      Career families
      Healthcare
      Methodology
      Scores are time-weighted across each role's canonical O*NET tasks, graded against current frontier-model capability. How we score.