Nurse Practitioners
HealthcareAI exposure
- Data source: BLSPublished: 2026-08
High· relative
LowFour relative bandsVery highGroup-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
- Data source: AnthropicPublished: 2026-03
0.094
0.000Range of values carried here0.745Scale, basis and source
- Data source: ILOPublished: 2025
0.25
0.09Range of values carried here0.70Group-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, 77% score at or above this value.
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 onlyValues 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.
| Task | βE1 + 0.5 × E2 |
|---|---|
Maintain complete and detailed records of patients' health care plans and prognoses.O*NET Task ID 18399 | 1.0 |
Educate patients about self-management of acute or chronic illnesses, tailoring instructions to patients' individual circumstances.O*NET Task ID 18378 | 0.5 |
Schedule follow-up visits to monitor patients or evaluate health or illness care.O*NET Task ID 18379 | 0.5 |
Counsel patients about drug regimens and possible side effects or interactions with other substances, such as food supplements, over-the-counter (OTC) medications, or herbal remedies.O*NET Task ID 18380 | 0.5 |
Order, perform, or interpret the results of diagnostic tests, such as complete blood counts (CBCs), electrocardiograms (EKGs), and radiographs (x-rays).O*NET Task ID 18381 | 0.5 |
Analyze and interpret patients' histories, symptoms, physical findings, or diagnostic information to develop appropriate diagnoses.O*NET Task ID 18382 | 0.5 |
Diagnose or treat acute health care problems, such as illnesses, infections, or injuries.O*NET Task ID 18383 | 0.5 |
Diagnose or treat chronic health care problems, such as high blood pressure and diabetes.O*NET Task ID 18384 | 0.5 |
Diagnose or treat complex, unstable, comorbid, episodic, or emergency conditions in collaboration with other health care providers as necessary.O*NET Task ID 18385 | 0.5 |
Treat or refer patients for primary care conditions, such as headaches, hypertension, urinary tract infections, upper respiratory infections, and dermatological conditions.O*NET Task ID 18386 | 0.5 |
Perform primary care procedures such as suturing, splinting, administering immunizations, taking cultures, and debriding wounds.O*NET Task ID 18390 | 0.0 |
Perform routine or annual physical examinations.O*NET Task ID 18391 | 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