# Cytotechnologists

> Stain, mount, and study cells to detect evidence of cancer, hormonal abnormalities, and other pathological conditions following established standards and practices.

- **SOC code:** 29-2011.02
- **Canonical URL:** https://singulariki.com/roles/role-29-2011-02
- **Also known as:** Cytologist, Cytology Applications Specialist, Cytology Coordinator, Cytotechnologist, Cytology Technical Specialist, Certified Cytotechnologist, Cytopathology Technologist
- **Frame:** "AI exposure" means task overlap (how codifiable the work is), not jobs lost or a forecast. Every figure below is traced to a named public dataset.

## What this work is

**Core tasks** (O*NET):
- Examine cell samples to detect abnormalities in the color, shape, or size of cellular components and patterns.
- Document specimens by verifying patients' and specimens' information.
- Submit slides with abnormal cell structures to pathologists for further examination.
- 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.
- 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.
- Assist pathologists or other physicians to collect cell samples by fine needle aspiration (FNA) biopsy or other method.
- Prepare cell samples by applying special staining techniques, such as chromosomal staining, to differentiate cells or cell components.
- Adjust, maintain, or repair laboratory equipment, such as microscopes.
- Assign tasks or coordinate task assignments to ensure adequate performance of laboratory activities.
- Attend continuing education programs that address laboratory issues.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Biology _(knowledge)_
- Oral Comprehension _(ability)_
- Written Comprehension _(ability)_
- Near Vision _(ability)_
- Reading Comprehension _(essential_skill)_
- Inductive Reasoning _(ability)_
- Medicine and Dentistry _(knowledge)_
- Active Listening _(essential_skill)_
- Critical Thinking _(essential_skill)_
- Problem Sensitivity _(ability)_
- Deductive Reasoning _(ability)_
- Flexibility of Closure _(ability)_

**Skills in demand:**
- Biology _(Specialized Skill)_
- Reading Comprehension _(Common Skill)_
- Inductive Reasoning _(Common Skill)_
- Deductive Reasoning _(Common Skill)_
- Critical Thinking _(Common Skill)_
- Active Listening _(Common Skill)_
- Finger Dexterity _(Common Skill)_
- Information Ordering _(Specialized Skill)_
- Complex Problem Solving _(Common Skill)_
- English Language _(Common Skill)_
- Writing _(Common Skill)_
- Time Management _(Common Skill)_

**Tools & technology:**
- Ansible software _(hot technology)_
- MEDITECH software _(hot technology)_
- Microsoft Excel _(hot technology)_
- Microsoft Office software _(hot technology)_
- Microsoft Word _(hot technology)_
- Antek HealthWare LabDAQ
- Aspyra CyberLAB
- Cerner Millennium PathNet
- Clinical Software Solutions CLIN1 Suite
- ClinLab LIS
- Comp Pro Med Polytech
- CPSI CPSI System

## AI exposure & outlook

- **AI task-overlap index:** 54th percentile (Moderate) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 56th percentile (Moderate) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 54th percentile (Moderate) — source: eloundou_gamma.
- **Frey–Osborne (2013, historical computerization estimate):** 78th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** no — task structure, not who actually works remote.

## How people actually use AI here

Anthropic Economic Index — measured AI conversations mapped to this occupation's tasks:

- **Automation vs augmentation:** — automation, 16% augmentation (usage-weighted).
- **Autonomy median:** 3.0 (higher = AI acts more independently).
- **Dominant collaboration mode:** task iteration.

**Tasks most handed to AI here:**
- Examine specimens using microscopes to evaluate specimen quality. _(0.6% of measured AI use)_
- Examine cell samples to detect abnormalities in the color, shape, or size of cellular components and patterns. _(0.4% of measured AI use; task iteration)_

**Example prompts (honest phrasings of the tasks above — starting points, not endorsed instructions):**
- Help me examine specimens using microscopes to evaluate specimen quality.
- Help me examine cell samples to detect abnormalities in the color, shape, or size of cellular components and patterns.

## Sources

- **O*NET** (30.3) — U.S. Department of Labor / National Center for O*NET Development. https://www.onetcenter.org/database.html
- **Anthropic Economic Index** (v4 (2026-01-15) + v2 (2025-03-27)) — Anthropic. https://www.anthropic.com/economic-index
- **“GPTs are GPTs” (Eloundou et al.)** (arXiv 2303.10130) — OpenAI / academic. https://arxiv.org/abs/2303.10130
- **AI Occupational Exposure (AIOE)** (Felten, Raj & Seamans) — academic. https://github.com/AIOE-Data/AIOE
- **Frey & Osborne (2013)** (frey-osborne-automation) — academic. https://www.oxfordmartin.ox.ac.uk/publications/the-future-of-employment/
- **Dingel & Neiman (2020)** (dingel-neiman-workathome) — academic. https://github.com/jdingel/DingelNeiman-workathome

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_Generated from Singulariki's joined dataset; data snapshot 2026-06-02T21:00:32.945303+00:00. https://singulariki.com/roles/role-29-2011-02_