# Chemical Technicians

> Conduct chemical and physical laboratory tests to assist scientists in making qualitative and quantitative analyses of solids, liquids, and gaseous materials for research and development of new products or processes, quality control, maintenance of environmental standards, and other work involving experimental, theoretical, or practical application of chemistry and related sciences.

- **SOC code:** 19-4031.00
- **Canonical URL:** https://singulariki.com/roles/role-19-4031-00
- **Also known as:** Chemical Technician, Laboratory Analyst (Lab Analyst), Laboratory Technician (Lab Tech), Quality Control Technician (QC Tech), Analytical Laboratory Technician (Analytical Lab Technician), Chemical Analyst, Laboratory Tester (Lab Tester), Organic Preparation Analyst (Organic Prep Analyst)
- **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):
- Conduct chemical or physical laboratory tests to assist scientists in making qualitative or quantitative analyses of solids, liquids, or gaseous materials.
- Maintain, clean, or sterilize laboratory instruments or equipment.
- Monitor product quality to ensure compliance with standards and specifications.
- Set up and conduct chemical experiments, tests, and analyses, using techniques such as chromatography, spectroscopy, physical or chemical separation techniques, or microscopy.
- Prepare chemical solutions for products or processes, following standardized formulas, or create experimental formulas.
- Compile and interpret results of tests and analyses.
- Provide and maintain a safe work environment by participating in safety programs, committees, or teams and by conducting laboratory or plant safety audits.
- Provide technical support or assistance to chemists or engineers.
- Develop or conduct programs of sampling and analysis to maintain quality standards of raw materials, chemical intermediates, or products.
- Train new employees on topics such as the proper operation of laboratory equipment.
- Write technical reports or prepare graphs or charts to document experimental results.
- Order and inventory materials to maintain supplies.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Science _(essential_skill)_
- Reading Comprehension _(essential_skill)_
- Critical Thinking _(essential_skill)_
- Written Comprehension _(ability)_
- Near Vision _(ability)_
- Active Listening _(essential_skill)_
- Writing _(essential_skill)_
- Monitoring _(essential_skill)_
- Written Expression _(ability)_
- Chemistry _(knowledge)_
- Oral Comprehension _(ability)_
- Problem Sensitivity _(ability)_

**Skills in demand:**
- Reading Comprehension _(Common Skill)_
- Critical Thinking _(Common Skill)_
- Writing _(Common Skill)_
- Active Listening _(Common Skill)_
- Chemistry _(Specialized Skill)_
- Information Ordering _(Specialized Skill)_
- Inductive Reasoning _(Common Skill)_
- Deductive Reasoning _(Common Skill)_
- English Language _(Common Skill)_
- Microsoft Outlook _(Common Skill)_
- Microsoft Excel _(Common Skill)_
- Mathematics _(Common Skill)_

**Tools & technology:**
- Microsoft Excel _(hot technology, in demand)_
- Microsoft Office software _(hot technology, in demand)_
- Microsoft Outlook _(hot technology, in demand)_
- C++ _(hot technology)_
- Linux _(hot technology)_
- Microsoft Access _(hot technology)_
- Microsoft PowerPoint _(hot technology)_
- Microsoft Word _(hot technology)_
- Oracle Database _(hot technology)_
- Oracle Java _(hot technology)_
- Python _(hot technology)_
- R _(hot technology)_

## AI exposure & outlook

- **AI task-overlap index:** 48th percentile (Moderate) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 49th percentile (Moderate) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 53rd percentile (Moderate) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 46th percentile (Moderate) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 49th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** no — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** 3.7% growth (About average); 6.7k annual openings; 57k → 59k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $57,790; 55,640 employed.

## How people actually use AI here

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

- **Automation vs augmentation:** 39% automation, 54% augmentation (usage-weighted).
- **Autonomy median:** 4.0 (higher = AI acts more independently).
- **Dominant collaboration mode:** directive.

**Tasks most handed to AI here:**
- Provide technical support or assistance to chemists or engineers. _(3.9% of measured AI use; learning)_
- Set up and conduct chemical experiments, tests, and analyses, using techniques such as chromatography, spectroscopy, physical or chemical separation techniques, or microscopy. _(2.5% of measured AI use; directive)_
- Write technical reports or prepare graphs or charts to document experimental results. _(2.2% of measured AI use; task iteration)_
- Develop new chemical engineering processes or production techniques. _(1.7% of measured AI use; learning)_
- Compile and interpret results of tests and analyses. _(0.8% of measured AI use; directive)_

**Example prompts (honest phrasings of the tasks above — starting points, not endorsed instructions):**
- Help me provide technical support or assistance to chemists or engineers.
- Help me set up and conduct chemical experiments, tests, and analyses, using techniques such as chromatography, spectroscopy, physical or chemical separation techniques, or microscopy.
- Help me write technical reports or prepare graphs or charts to document experimental results.
- Help me develop new chemical engineering processes or production techniques.
- Help me compile and interpret results of tests and analyses.

## Sources

- **O*NET** (30.3) — U.S. Department of Labor / National Center for O*NET Development. https://www.onetcenter.org/database.html
- **BLS Occupational Employment and Wage Statistics (OEWS)** (May 2024) — U.S. Bureau of Labor Statistics. https://www.bls.gov/oes/
- **BLS Employment Projections** (2024–2034) — U.S. Bureau of Labor Statistics. https://www.bls.gov/emp/
- **Anthropic Economic Index** (v4 (2026-01-15) + v2 (2025-03-27)) — Anthropic. https://www.anthropic.com/economic-index
- **Microsoft “Working with AI”** (working-with-ai) — Microsoft Research. https://www.microsoft.com/en-us/research/
- **“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-19-4031-00_