Emergency Medical Technicians

Healthcare

AI exposure

  • Data source: BLSPublished: 2026-08

    Low· relative

    LowFour relative bandsVery high

    Group-level value

    Scale, basis and source

    Four relative bands (Low / Moderate / High / Very high)

    831 detailed occupations in the BLS Employment Projections table. Assigned per National Employment Matrix (NEM) code, so occupations sharing a NEM code carry the same band

    Source dataset (XLSX download)

  • Data source: AnthropicPublished: 2026-03

    0.000

    0.000Range of values carried here0.745
    Scale, basis and source

    Observed exposure index, 0–1 as published

    Mapped onto O*NET tasks

    Source dataset

  • Data source: ILOPublished: 2025

    0.22

    0.09Range of values carried here0.70

    Group-level value

    Scale, basis and source

    Generative AI exposure index, 0–1 as published

    ISCO-08 unit group — every occupation sharing the code gets this value

    Computed by this site, not published by the ILO: of the 1,012 occupations this site links to the ILO dataset, 81% score at or above this value.

    Source dataset

What kind of figure this source publishes

The BLS category is a relative rank, not an absolute level, and it is not a first-hand measurement: it groups an occupation's percentile ranks across several published studies into four bands. It is not an employment or wage forecast, not a probability of adoption, and it does not separate automation from augmentation.

Task-level exposure

Exposed tasks only

Values in this tab are predicted labels, not observations. Eloundou et al. (2023) published two rating regimes — human raters and GPT-4 — and the β shown here is derived from the GPT-4 rater basis alone; the same task can take a different value under the other regime. The unit and the meaning differ from the observed shares (%) in the other tabs, so do not place them on the same axis.

TaskβE1 + 0.5 × E2
Attend training classes to maintain certification licensure, keep abreast of new developments in the field, or maintain existing knowledge.

O*NET Task ID 22854

1.0
Observe, record, and report to physician the patient's condition or injury, the treatment provided, and reactions to drugs or treatment.

O*NET Task ID 22862

1.0
Communicate with dispatchers or treatment center personnel to provide information about situation, to arrange reception of victims, or to receive instructions for further treatment.

O*NET Task ID 22856

0.5
Administer first aid treatment or life support care to sick or injured persons in prehospital settings.

O*NET Task ID 22852

0.0
Assess nature and extent of illness or injury to establish and prioritize medical procedures.

O*NET Task ID 22853

0.0
Comfort and reassure patients.

O*NET Task ID 22855

0.0
Coordinate work with other emergency medical team members or police or fire department personnel.

O*NET Task ID 22857

0.0
Decontaminate ambulance interior following treatment of patient with infectious disease, and report case to proper authorities.

O*NET Task ID 22858

0.0
Drive mobile intensive care unit to specified location, following instructions from emergency medical dispatcher.

O*NET Task ID 22859

0.0
Immobilize patient for placement on stretcher and ambulance transport, using backboard or other spinal immobilization device.

O*NET Task ID 22860

0.0
Maintain vehicles and medical and communication equipment, and replenish first aid equipment and supplies.

O*NET Task ID 22861

0.0
Perform emergency diagnostic and treatment procedures, such as stomach suction, airway management, or heart monitoring, during ambulance ride.

O*NET Task ID 22863

0.0

β = E1 + 0.5 × E2 · E1 = tasks where direct LLM access alone cuts time by at least 50%, E2 = tasks where software built on top of an LLM cuts time by at least 50%. Values take only 0 / 0.5 / 1.0.

Data sources & licenses — O*NET®, Eloundou et al. (2023): see full notices on the Credits page

Occupation information