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Nurse practitioner
A registered nurse with advanced training who sees patients on their own: taking histories, examining, ordering and reading tests, diagnosing and prescribing, and counselling patients. AI is reaching the paperwork around the visit rather than the visit: in a pilot of an ambient AI tool that drafts clinical notes for review, burnout among physicians and advanced practice providers fell from 69% to 43%, and at Stanford clinicians used AI-drafted replies to patient messages for 20% of replies without saving time. Rules keep the clinician responsible: British Columbia's nursing regulator holds nurses solely accountable for AI-assisted notes, and California requires AI-generated patient messages to say so unless a licensed provider reviewed them. The US projects 41% growth, driven by demand and wider practice authority, with no mention of technology.
Ask your employer whether an AI documentation tool is approved where you work and what review it requires.
This is not a probability of losing your job. It combines how much of the role's task load is exposed to automation with how far adoption has actually gone — useful for comparing occupations on one consistent basis, and for nothing else.
Written for nurse practitioners, mainly in the US and Canada; registered nurses and general practitioners have their own pages. The evidence is a US labour projection, a Canadian nursing regulator's documentation standard, two US studies of AI documentation and message drafting that included advanced practice providers alongside physicians, and a California law; no source studies nurse practitioners alone, and it establishes how AI enters the paperwork around visits and who stays responsible, not how nurse practitioners' work or numbers have changed.
What is actually changing#
The unit of analysis is the task, not the job title. A role is not replaced — its task mix shifts.
Each tile is one task. Its size is how much of the job it is; its colour is where the task is heading. Click a tile to see what the judgement does not establish.
A small pilot without a control group that mixed physicians and advanced practice providers, and one province's standard; they do not show how much documentation time nurse practitioners save.
A projection and the absence of a record; they do not measure how examinations are changing.
An inference without a dated record; it does not measure how diagnosis is changing.
A statement in a projection; it does not show how prescribing decisions are made.
One medical centre's five-week pilot and one state's law; they do not show how many messages nurse practitioners answer with AI.
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A job title is a bundle of tasks bought together, and no two people hold the same bundle. Nothing is sent anywhere — it stays in this browser.
Read all 5 tasks in full — direction, reasoning and limits →
Recent changes#
United States. The statistics bureau projects employment of nurse practitioners to grow from 336,300 in 2025 to 474,100 in 2035, 41 percent. It attributes growth to increased demand for healthcare services, the ageing population and growing prevalence of chronic disease, and says that as states change their laws governing practice authority, advanced practice registered nurses are being allowed to perform more services. It does not mention technology.
A named person with standing publicly predicted something, on a date, in an attributable statement. It is recorded so that who said what, and when, stays checkable — and it never moves a task's assessment, because a prediction is not an observation. Its value arrives later: the record sits on the same page as the evidence about that occupation, so anyone reading the forecast reads the record of what happened next beside it. That is the reckoning; this site publishes no verdict on whether a forecast came true.
British Columbia, Canada. The regulator’s documentation standard, which applies to nurse practitioners, says nurses only use artificial intelligence to assist with documentation when, among other conditions, their organisation or employer has approved its use, and that they remain solely accountable for the accuracy, objectivity and completeness of their documentation entry.
Failure, rollback, regulation or cost is suppressing adoption. Can lower an assessment or widen its uncertainty.
University of Iowa Health Care, United States. A pre-post observational study in which 38 volunteer physicians and advanced practice providers used a commercial ambient AI tool for five weeks in ambulatory clinics; the tool transcribed patient–clinician conversations and generated preliminary notes for review and entry into the record. Burnout rates fell from 69% to 43%; work exhaustion did not change significantly. The abstract does not say how many participants were nurse practitioners, and there was no control group.
Small-scale trial in a real setting. Tells us the deployment conditions are being tested, not that they hold — so one pilot is never enough on its own; two independent ones are.
California, United States. A health facility, clinic, physician’s office or group practice that uses generative AI to generate written or verbal patient communications about clinical information must include a disclaimer that the communication was generated by AI and instructions for reaching a human provider. The requirement does not apply if a licensed or certified health care provider read and reviewed the communication.
Failure, rollback, regulation or cost is suppressing adoption. Can lower an assessment or widen its uncertainty.
Stanford Health Care, United States. A five-week quality improvement study in 2023 enrolled all attending physicians, advanced practice practitioners, clinic nurses and clinical pharmacists in primary care and gastroenterology; 162 clinicians were analysed. A language model integrated in the health record drafted replies to patient portal messages. The mean draft utilisation rate was 20%; reply, write and read times did not change, while reported task load and work exhaustion fell. It does not report results for nurse practitioners separately.
Small-scale trial in a real setting. Tells us the deployment conditions are being tested, not that they hold — so one pilot is never enough on its own; two independent ones are.
What this means for you#
If you are starting out, expect AI to draft some notes and message replies that you must check and sign. Build what stays with you: examination, diagnosis and the judgement behind a prescription.
Expect documentation tools to arrive through your employer, with the rules keeping you responsible for what they write. Your practice authority is widening, not shrinking.
Your options#
Four directions, each with its real constraints and one thing you can test this week. Continuing as you are is a legitimate choice — it just has to be a chosen one.
Learn to supervise AI documentation
Ambient AI tools draft notes for review, and regulators keep the clinician accountable for what is entered.
Whether you may use these tools depends on your employer and your regulator.
Ask your employer whether an AI documentation tool is approved where you work and what review it requires.
Stay in hands-on primary care
The US projects 41% growth for nurse practitioners, and no record shows machines examining or diagnosing in their place.
Practice authority differs by state and country.
Check what your state or country lets nurse practitioners do without a physician's supervision.
Move towards clinical informatics
Health systems introducing AI drafting and documentation tools need clinicians who can evaluate them.
These roles usually need informatics training and are fewer than clinical posts.
Find out who evaluates AI tools in your health system and whether clinicians sit on that group.
Common questions#
Not on present evidence. AI drafts notes and message replies for clinicians to review, but no record shows machines examining, diagnosing or prescribing in their place, and the US projects 41% growth for the occupation.
We do not answer that with a number of years. Watch whether the rules where you work let AI tools make decisions without a clinician's review. That tells you more than any date.
The evidence that includes them is about burden more than time. In a pilot with physicians and advanced practice providers, burnout fell from 69% to 43%; at Stanford, AI-drafted message replies did not shorten reply time.
The US labour statistics agency projects 41% growth from 2025 to 2035, citing demand for healthcare, an ageing population and wider practice authority, and does not mention technology.
What these judgements rest on#
2 of 5 task judgements on this page are backed by a verified event and 3 are platform inference, each labelled where it appears. Behind them sit 3 technology dimensions, a reconstructed trajectory since language models reached the public, and 5 verified events.
See which technologies, how it got here, and the method →
Where it sits in the official classification: skills, knowledge, related jobs →
Other roles in the same function#
A company divides its work into functions before it divides it into jobs. These sit in Core delivery (industry-specific) alongside this one — a fact about org charts, not a judgement that they are similar or that they are changing in the same direction.
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