Resilient
Last Update: 7/31/2026
AI Resilience Score for Nurse Anesthetists:
73.8%
Median Score
Meaningful human contribution
Measures the parts of the occupation that still require a human touch. This score averages data from up to four AI exposure datasets, focusing on the role’s resilience against automation.
High
Long-term employer demand
Predicts the health of the job market for this role through 2034. Using Bureau of Labor Statistics data, it balances projected annual job openings (60%) with overall employment growth (40%).
Med
Sustained economic opportunity
Measures future earning potential and career flexibility. This score is a blend of total projected labor income (67%) and the role’s inherent ability to adapt to economic and technological shifts (33%).
High
This reflects the reliability of your score based on the number of data sources available for this career and how closely those sources agree on the outlook. A higher confidence means more consistent evidence from labor experts and AI models.
Most data sources align, with only minor variation. This is a well-supported result.
Contributing sources
AI Resilience Report forNurse Anesthetists
$236,590 median salary•2,700 annual openings•SOC Code: 29-1151.00
Nurse Anesthetists are more resilient to AI impacts than most occupations, according to our analysis of 6 sources.
Nurse anesthetists earn a "Resilient" label because the core of their work is deeply physical and human, placing breathing tubes, performing nerve blocks, and monitoring patients in real time in ways that AI simply cannot replicate on its own. While AI tools are getting better at tracking sedation depth and suggesting anesthetic techniques (matching expert decisions about 84.6% of the time in recent studies), researchers and professional organizations agree these tools should support CRNAs, not replace them.
Learn more about how you can thrive in this position
View analysis
Chat with Coach
Latest news
More career infoAnalysisChatNewsMoreThis role is resilient
Nurse anesthetists earn a "Resilient" label because the core of their work is deeply physical and human, placing breathing tubes, performing nerve blocks, and monitoring patients in real time in ways that AI simply cannot replicate on its own. While AI tools are getting better at tracking sedation depth and suggesting anesthetic techniques (matching expert decisions about 84.6% of the time in recent studies), researchers and professional organizations agree these tools should support CRNAs, not replace them.
Read full analysisLearn more about how you can thrive in this position
View analysisChat with CoachLatest newsMore career infoAnalysisChatNewsMoreAnalysis of Current AI Resilience
Nurse Anesthetists
Updated Quarterly
How is AI changing Nurse Anesthetists jobs?
Right now, AI is mostly augmenting nurse anesthetists rather than replacing them. The hands-on parts of the job — placing breathing tubes, performing nerve blocks, watching a patient breathe in real time — still need a skilled human in the room. Where AI shows up is in the background: a 2025 review in Frontiers in Medicine [1] describes machine-learning models that automatically adjust sedation, predict drug levels, and track depth of anesthesia from EEG signals with nearly 89% accuracy.
A 2026 multicenter study in the Journal of Personalized Medicine [2] found ChatGPT's anesthetic technique recommendations matched expert clinician decisions about 84.6% of the time — promising, but the authors stress AI should "complement, not replace" providers. Hospitals are also using AI for predictive staffing and OR coordination [3], not bedside care. The AANA's EDGE 2026 conference [4] recently urged programs to teach AI literacy across all three years of training, signaling that the profession sees AI as a tool to learn, not a threat.
Sources
How fast is AI adoption growing for Nurse Anesthetists?
Adoption is moving carefully and slowly at the bedside, but faster behind the scenes. A huge driver is the workforce gap: Stout's 2026 staffing analysis [5] counts about 67,700 practicing CRNAs with demand outpacing supply, and the Bureau of Labor Statistics projects 38% job growth by 2032 [3] — so any tool that helps overworked CRNAs is welcome. Brakes on adoption include strict FDA oversight, patient-safety liability, and the fact that core tasks are physical.
A 2025 JNAE survey of 455 students and 58 CRNA faculty [6] also found students less familiar and less optimistic about AI than faculty, pointing to a learning curve before clinical use scales up. The encouraging takeaway: human judgment, communication, and steady hands remain the heart of this career.
Sources
Will AI replace Nurse Anesthetists?
No. We don't think AI will replace Nurse Anesthetists, but the job will keep evolving as these tools become more capable.
Nurse Anesthetists earn a 73.8% AI Resilience Score from us, and the core reason is physical presence. Placing a breathing tube, performing a nerve block, watching a patient's color change in real time: these tasks require a skilled human in the room, full stop. AI is showing up in the background, not at the bedside. Machine-learning models can predict drug levels and track anesthesia depth from EEG signals [1], and AI-generated technique recommendations matched expert decisions about 84.6% of the time in one multicenter study [2]. Useful, but the authors themselves say AI should complement providers, not replace them.
Demand also supports staying in this field. There are roughly 67,700 practicing CRNAs with demand already outpacing supply [5], and the Bureau of Labor Statistics projects 38% job growth by 2032 [3]. That kind of workforce gap means AI is far more likely to help overworked CRNAs than to push them out. The AANA is already building AI literacy into training programs [4], which is exactly the right move: learn the tools, keep the judgment, and stay indispensable.
Sources
Help us improve this report.
Tell us if this analysis feels accurate or we missed something.
Share your feedback
Latest AI news for Nurse Anesthetists
These articles highlight the evolving role of AI in anesthesia, emphasizing both opportunities and challenges for nurse anesthetists. For instance, AI advancements could streamline workflows, but concerns about job security arise, as seen with the $9/hour "AI nurse" mentioned in the second article. Additionally, a case where AI failed to detect drug diversion underscores the importance of human oversight in patient safety. Understanding these dynamics will help aspiring nurse anesthetists adapt and thrive in a landscape where AI plays an increasingly significant role.
AI Failed to Catch a Nurse Anesthetist Stealing Drugs for Months, Coworkers Stepped In
nurse.org • 6/20/2026
AI medication-monitoring software failed to flag a Tennessee nurse anesthetist who diverted fentanyl for months. Here is what nurses need to...
At a Tennessee hospital, a nurse stole fentanyl and AI missed it, state records say
www.cbsnews.com • 6/20/2026
About a year ago at Erlanger Baroness, the largest hospital in Chattanooga, anesthesia staff noticed that a nurse was slurring his words and...
Will This Recession Be Different for Nurses? AI Is Rewriting Every Rule We Thought We Had
allnurses.com • 6/20/2026
Nurses have always outlasted recessions. But AI is rewriting the rules. With a $9/hour "AI nurse" on the market and hospitals already...
AI Falls Short in Emergency Triage—Nurses and Doctors Still Lead the Way
nurse.org • 10/9/2025
New research from Vilnius University shows that AI tools like ChatGPT underperform compared to nurses and doctors in emergency department...
How AI is reshaping the anesthesia workforce
kevinmd.com • 8/29/2024
Emerging AI and technology advancements in anesthesia may enhance care but also pose potential workforce challenges, necessitating proactive...
More Career Info
Career: Nurse Anesthetists
They help patients stay pain-free during surgeries by giving anesthesia and monitoring their vital signs to ensure their safety.
Parent Careers
Employment & Wage Data
Median Wage
$236,590
Jobs (2024)
53,800
Growth (2024-34)
+8.6%
Annual Openings
2,700
Education
Master's degree
Experience
None
Source: Bureau of Labor Statistics, Employment Projections 2024-2034
Task-Level AI Resilience Scores
AI-generated estimates of task resilience over the next 3 years
1
Select, order, or administer anesthetics, adjuvant drugs, accessory drugs, fluids or blood products as necessary.
2
Monitor patients' responses, including skin color, pupil dilation, pulse, heart rate, blood pressure, respiration, ventilation, or urine output, using invasive and noninvasive techniques.
3
Prepare prescribed solutions and administer local, intravenous, spinal, or other anesthetics following specified methods and procedures.
4
Respond to emergency situations by providing airway management, administering emergency fluids or drugs, or using basic or advanced cardiac life support techniques.
5
Insert peripheral or central intravenous catheters.
6
Instruct nurses, residents, interns, students or other staff on topics such as anesthetic techniques, pain management and emergency responses.
7
Administer post-anesthesia medications or fluids to support patients' cardiovascular systems.
Tasks are ranked by their AI resilience, with the most resilient tasks shown first. Core tasks are essential functions of this occupation, while supplemental tasks provide additional context.
