Share and intensity of work current AI systems can materially affect.
Registered Nurses AI displacement risk
Documentation and administrative follow-up can change quickly, but hands-on care, clinical judgment, licensing, and patient trust constrain direct replacement.
Likely potential for exposed tasks to move to software after workflow integration.
AI can change workflow without reducing staffing needs. The highest near-term impact is documentation relief and triage support, not full role automation.
Task profile
Where AI changes the work
Draft visit notes
Exposure 56, automation 26%, augmentation 72%.
Patient education
Exposure 42, automation 16%, augmentation 58%.
Medication review
Exposure 31, automation 12%, augmentation 48%.
Direct care
Exposure 9, automation 2%, augmentation 15%.
Transition pathways
Adjacent moves that preserve existing skills
credentialed transition
Low Clinical Informatics Specialist
Training horizon: 6-18 months. Skill overlap 58. Wage preservation signal 103.
- Learn EHR workflows
- Audit AI note quality
- Bridge clinical and technical teams
role redesign
Low Care Coordination Lead
Training horizon: 3-6 months. Skill overlap 79. Wage preservation signal 98.
- Manage patient follow-up
- Use AI to flag gaps
- Coordinate interdisciplinary care
Labor-market context
Median wage: $86,070. Employment context: Persistent labor shortage with documentation burden. Typical education: Bachelor's degree or associate degree.
- Low displacement pressure
- High documentation relief
- Regulation and trust constraints
Sources
Evidence trail
International Labour Organization / 2025 Generative AI and Jobs: A Refined Global Index of Occupational Exposure OECD / 2023 Employment Outlook 2023: Artificial Intelligence and the Labour Market O*NET / current public database Occupation, task, skill, and work-activity data US Bureau of Labor Statistics / current public release Occupational Employment and Wage Statistics