Will AI replace Nurse Anesthetists?
Most of the work in Nurse Anesthetists still leans on things AI struggles with — research rates its theoretical AI reach at only ~17%, and real-world use lower still.
O*NET-SOC 29-1151
How your 24 core tasks split
Top = what GPT-4 judged AI could speed up. Bottom = how much AI was actually used for these tasks (Anthropic's March 2026 report, usage from Aug & Nov 2025). The gap is the real story.
Back in 2023, GPT-4 judged AI could, in theory, assist with a relatively low share of this job's tasks (~17%). By late 2025, real-world AI use had reached about 0% of its task activity (still rare). The gap between that 2023 forecast and today is the real story.
Where this job sits among 738 jobs
Each dot is one of 738 U.S. jobs. Right = AI can do more of it. Up = AI is actually used more.
The signals here line up
Theoretical reach (~17%), real-world use (~0%) and the task-level picture mostly agree — so this read is more reliable than for jobs where the signals contradict each other. Even so, AI-risk estimates shift by model (a 2026 study saw the "high-risk" share swing 2.7%–51.5%), so treat these as directional, not destiny.
See all 24 tasks, ratedBased on real task-level AI scores — click to collapse
- None — AI cannot fully do any core task alone yet.
- Assess patients' medical histories to predict anesthesia response.
- Develop anesthesia care plans.
- Perform pre-anesthetic screenings, including physical evaluations and patient interviews, and document results.
- Select and prescribe post-anesthesia medications or treatments to patients.
- Perform or evaluate the results of diagnostic tests, such as radiographs (x-rays) and electrocardiograms (EKGs).
- Select, order, or administer pre-anesthetic medications.
- Read current literature, talk with colleagues, and participate in professional organizations or conferences to keep abreast of developments in nursing.
- Instruct nurses, residents, interns, students, or other staff on topics such as anesthetic techniques, pain management and emergency responses.
- Manage patients' airway or pulmonary status, using techniques such as endotracheal intubation, mechanical ventilation, pharmacological support, respiratory therapy, and extubation.
- Respond to emergency situations by providing airway management, administering emergency fluids or drugs, or using basic or advanced cardiac life support techniques.
- Monitor patients' responses, including skin color, pupil dilation, pulse, heart rate, blood pressure, respiration, ventilation, or urine output, using invasive and noninvasive techniques.
- Select, order, or administer anesthetics, adjuvant drugs, accessory drugs, fluids or blood products as necessary.
- Select, prepare, or use equipment, monitors, supplies, or drugs for the administration of anesthetics.
- Perform or manage regional anesthetic techniques, such as local, spinal, epidural, caudal, nerve blocks and intravenous blocks.
- Obtain informed consent from patients for anesthesia procedures.
- Prepare prescribed solutions and administer local, intravenous, spinal, or other anesthetics, following specified methods and procedures.
- Calibrate and test anesthesia equipment.
- Evaluate patients' post-surgical or post-anesthesia responses, taking appropriate corrective actions or requesting consultation if complications occur.
- Administer post-anesthesia medications or fluids to support patients' cardiovascular systems.
- Insert peripheral or central intravenous catheters.
- Insert arterial catheters or perform arterial punctures to obtain arterial blood samples.
- Discharge patients from post-anesthesia care.
- Request anesthesia equipment repairs, adjustments, or safety tests.
- Disassemble and clean anesthesia equipment.
How we measured this — and how fresh it is
AI's theoretical reach data: 2023
From GPTs-are-GPTs (Eloundou et al.), where GPT-4 rated how much of each task an AI tool could meaningfully speed up. This is the most recent open, commercially-usable occupation-level potential dataset — it dates to 2023. Newer multi-model re-runs exist but swing wildly (one 2026 study saw "high-risk" jobs range 2.7%–51.5% by model) and aren't openly licensed, so we show the stable 2023 baseline and pair it with newer real-world data.
Real-world AI use 2026 report
From the Anthropic Economic Index, which observes how real Claude conversations map onto each occupation's tasks. Published in Anthropic's March 2026 labor-market report, based on usage measured in Aug & Nov 2025 (Sonnet 4 / 4.5).
Task list & ratings O*NET 30.3
Tasks come from O*NET 30.3. Each task's "AI can do / speeds up / still on you" tier uses the real task-level exposure scores from GPTs-are-GPTs (E1 / E2 / E0) — not a guess from keywords.
Sources: O*NET 30.3 (CC BY 4.0) · GPTs-are-GPTs (MIT, 2023) · Anthropic Economic Index (CC BY, Aug & Nov 2025). Page compiled June 2026. "O*NET" is a trademark of the U.S. Department of Labor.
This page is for general informational purposes only and is not career, financial, or employment advice. AI exposure reflects research estimates of task overlap, not predictions about any individual's job, employer, or future employment.