Will AI replace Cytotechnologists?
AI reaches little of this job’s work.
16/100
Low exposure
More exposed to AI than 29% of US workers.
- AI already used in
- 12% of the work
- As AI tools mature: up to
- 33% of the work
What the job involves
Stain, mount, and study cells to detect evidence of cancer, hormonal abnormalities, and other pathological conditions following established standards and practices.
Where AI reaches the work
The job’s main tasks, heaviest first, by how far AI reaches them.
Already happening(2)
- Examine cell samples to detect abnormalities in the color, shape, or size of cellular components and patterns.
- Examine specimens to detect abnormal hormone conditions.
Within reach(4)
- Submit slides with abnormal cell structures to pathologists for further examination.
- Maintain effective laboratory operations by adhering to standards of specimen collection, preparation, or laboratory safety.
- Provide patient clinical data or microscopic findings to assist pathologists in the preparation of pathology reports.
- Attend continuing education programs that address laboratory issues.
Out of reach(7)
- Document specimens by verifying patients' and specimens' information.
- Prepare and analyze samples, such as Papanicolaou (PAP) smear body fluids and fine needle aspirations (FNAs), to detect abnormal conditions.
- Examine specimens, using microscopes, to evaluate specimen quality.
- Assist pathologists or other physicians to collect cell samples by fine needle aspiration (FNA) biopsy or other method.
- Adjust, maintain, or repair laboratory equipment, such as microscopes.
and 2 more
Also called
Cytotechnologist · Cytologist · Cytology Applications Specialist · Cytology Coordinator · Cytology Technical Specialist · Certified Cytotechnologist · Cytopathology Technologist
Related jobs
What these numbers mean
The score is the share of this job’s work, weighted by how important and frequent each task is, that AI could do in half the time: tasks an AI model could do alone count in full, tasks that need software built on AI count half.
“AI already used” is the share of the work in tasks where people are recorded using AI today. “As AI tools mature” counts every task AI could halve, with or without extra software.
The percentile compares the score with every job’s, weighted by how many people in the US do each one. Exposure means AI could change how the work is done, not that the job goes away. These are estimates for the typical job, not predictions.
Sources
- O*NET 31.0 Database, U.S. Department of Labor, Employment and Training Administration
- GPTs are GPTs: Labor market impact potential of LLMs (task labels), Eloundou, Manning, Mishkin & Rock (2023), OpenAI and University of Pennsylvania
- Anthropic Economic Index: labor market impacts (task penetration), Anthropic
- Occupational Employment and Wage Statistics, May 2025 (national and metropolitan areas), U.S. Bureau of Labor Statistics