Occupation · SOC 29-2012.00
Perform routine medical laboratory tests for the diagnosis, treatment, and prevention of disease. May work under the supervision of a medical technologist.
Also called: Laboratory Assistant (Lab Assistant) · Laboratory Technician (Lab Tech) · Medical Laboratory Technician (MLT) · Medical Laboratory Technicians (Medical Lab Technician) · Certified Clinical Laboratory Technician · Clinical Laboratory Technician (Clinical Lab Technician) · Medical Technician · Biotechnician · Blood Bank Laboratory Technician · Blood Typer · Blood and Plasma Laboratory Assistant · Blood or Blood Bank Technician
Job family: Healthcare Practitioners and Technical Occupations
A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch
/roles/role-29-2012-00/context.md directly.
A fast read on where AI already shows up in this occupation, where it stays a copilot, where humans remain in the loop, and what the labor market is doing. Built from observed Claude.ai conversations mapped to O*NET tasks and from published research — measures of usage and exposure, not advice or predictions that the job is going away.
Task areas most often handled directively in observed AI conversations — candidates to delegate with light review.
Task areas where a human was still judged necessary in a large share of observed conversations — not a safety ruling, an observed-need signal.
The capabilities O*NET rates most important for this occupation — the human ground the work is built on.
See all skills →Independent published positions, read together — not a forecast.
40th-percentile task overlap — yet observed AI use leans 3792% copilot, not hand-off (AEI) . What exposure means →
What today's research says about this occupation's exposure to AI, how AI is actually being used in it, and where employment is headed. These are positions within published studies — measures of exposure and usage, not predictions that this job will disappear.
Each study uses its own scale, so the raw scores are not comparable across rows — the percentile (this job's rank among all U.S. occupations with data) is the comparable figure, and sizes the bars.
| Measure | Rank vs all occupations | Percentile | Score |
|---|---|---|---|
| Overall AI exposure (Felten et al.) Moderate | 45th | -0.1 | |
| LLM task exposure, γ (OpenAI / Eloundou) Moderate | 39th | 0.4 |
OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.0), with simple added tooling (β 0.2), and including AI-powered software (γ 0.4). Higher means more of the job's tasks could be done at least twice as fast — not that they will be automated away.
This job mostly cannot be done remotely (Dingel–Neiman) — its hands-on tasks sit outside what software-based AI reaches.
A pre-LLM (2013) estimate of how automatable this job is by computerization and robotics. Shown for historical context only — it is not part of any current AI ranking.
Frey–Osborne probability 0.5 · 46th percentile among occupations · Moderate
Among measured AI assistant conversations mapped to this occupation (Anthropic Economic Index, 2026-01-15), these task types came up most. These are shares of observed AI conversations — not shares of the job, of worker time, or of what could be automated.
| Analyze and record test data to issue reports that use charts, graphs, or narratives. | 9.4% | |
| Prepare standard volumetric solutions or reagents to be combined with samples, following standardized formulas or experimental procedures. | 0.5% |
The ILO's 2025 global study scores generative-AI exposure on the international ISCO-08 occupation system, not US SOC. Bridged through the published (and approximate, many-to-many) IBS O*NET-SOC ↔ ISCO-08 crosswalk, this US occupation corresponds to the international occupation below. Exposure here means how much of the work's tasks today's AI can attempt — task overlap, not automation, adoption, or jobs lost.
| International occupation (ISCO-08) | Task exposure (2025) | Most tasks fall in |
|---|---|---|
| Medical and Pathology Laboratory Technicians · 3212 | 31% | Minimal |
Read the whole six-band gradient on the GenAI exposure gradient page. The crosswalk is approximate: a US occupation can map to several international ones, and the ILO scores describe the international occupation, not this exact US role.
How people actually apply AI to this occupation's tasks, from Claude.ai (Free and Pro) conversations in the Anthropic Economic Index, 2026-01-15. This is one AI assistant's consumer sample — not all AI, not the whole workforce. Autonomy and the collaboration mix are model-rated estimates; figures below the sample floor are hidden.
| Augmentation vs. automation | 37.9% working with AI · 49.1% handed to AI |
| Most common way people use AI here | Directive · AI does it; you give the instruction |
| Typical AI autonomy | 3.3 / 5 · higher = AI acts more independently |
| Used for work (vs. personal / coursework) | 34.2% |
The role's most common tasks in AI conversations, each tagged with how people work with the AI on it. “Usage” is the share of observed conversations, not of the job.
| Task | How | Usage |
|---|---|---|
| Analyze and record test data to issue reports that use charts, graphs, or narratives. | Directive | 1.8% |
| Prepare standard volumetric solutions or reagents to be combined with samples, following standardized formulas or experimental procedures. | Directive | 0.9% |
Tasks where the model most often judged that a person remained necessary — a useful read on the current boundary, not a guarantee.
| Prepare standard volumetric solutions or reagents to be combined with samples, following standardized formulas or experimental procedures. | 89.5% | |
| Analyze and record test data to issue reports that use charts, graphs, or narratives. | 88.0% |
Example prompts phrased from the tasks people most often delegate to AI in this occupation (Anthropic Economic Index). Each shows the underlying measured task and its share of observed AI use. They are suggested phrasings of real tasks — starting points, not endorsed instructions.
Help me analyze and record test data to issue reports that use charts, graphs, or narratives. From: Analyze and record test data to issue reports that use charts, graphs, or narratives. · 1.8% of measured AI use · directive
Help me prepare standard volumetric solutions or reagents to be combined with samples, following standardized formulas or experimental procedures. From: Prepare standard volumetric solutions or reagents to be combined with samples, following standardized formulas or experimental procedures. · 0.9% of measured AI use · directive
All 15 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.
Newer responsibilities O*NET has flagged as growing for this occupation.
O*NET importance rating, from 1 (not important) to 5 (extremely important).
| Near Vision | 4.0 | |
| Oral Expression | 3.9 | |
| Problem Sensitivity | 3.9 | |
| Information Ordering | 3.9 | |
| Oral Comprehension | 3.8 | |
| Written Comprehension | 3.6 | |
| Finger Dexterity | 3.6 | |
| Written Expression | 3.1 | |
| Deductive Reasoning | 3.1 | |
| Category Flexibility | 3.1 | |
| Flexibility of Closure | 3.1 | |
| Selective Attention | 3.1 | |
| Arm-Hand Steadiness | 3.1 | |
| Manual Dexterity | 3.1 | |
| Control Precision | 3.1 | |
| Visual Color Discrimination | 3.1 | |
| Speech Recognition | 3.1 | |
| Speech Clarity | 3.1 |
| Active Listening | 3.9 | |
| Reading Comprehension | 3.5 | |
| Speaking | 3.4 | |
| Critical Thinking | 3.4 | |
| Science | 3.3 | |
| Writing | 3.1 | |
| Monitoring | 3.1 | |
| Active Learning | 3.0 |
| Chemistry | 3.7 | |
| Biology | 3.7 | |
| English Language | 3.6 | |
| Mathematics | 3.5 | |
| Customer and Personal Service | 3.5 | |
| Public Safety and Security | 3.4 | |
| Administrative | 3.3 | |
| Medicine and Dentistry | 3.3 |
| Instructing | 3.1 | |
| Complex Problem Solving | 3.1 | |
| Operations Monitoring | 3.1 | |
| Quality Control Analysis | 3.1 | |
| Time Management | 3.1 | |
| Social Perceptiveness | 3.0 |
Skills employers ask for in job postings for this occupation (Lightcast), with whether each is a common or specialized skill.
Showing the top 40 of 42.
How characteristic each condition is of the job, on O*NET's 1–5 context scale (higher = more present in day-to-day work). Each condition links to how it varies across all occupations.
What to study: Health Professions and Related Programs . Fields of study crosswalked to this occupation (NCES CIP–SOC), not a requirement.
Share of people in this occupation at each level of education.
| Bachelor's Degree | 45.9% | |
| Associate's Degree (or other 2-year degree) | 30.9% | |
| Post-Baccalaureate Certificate | 10.5% | |
| Master's Degree | 6.8% | |
| High School Diploma | 4.2% | |
| Some College Courses | 0.9% | |
| Post-Secondary Certificate | 0.4% | |
| First Professional Degree | 0.3% |
The interests and personal qualities O*NET associates with people who do this work.
| Realistic | 6.0 | |
| Investigative | 5.9 | |
| Conventional | 4.8 | |
| Social | 2.9 |
| Health Care Service | 5.5 | |
| Medical Science | 5.3 | |
| Life Science | 5.3 | |
| Physical Science | 4.0 | |
| Mathematics/Statistics | 3.0 | |
| Mechanics/Electronics | 2.8 | |
| Engineering | 2.6 | |
| Physical/Manual Labor | 2.2 |
| Dependability | 4.0 | |
| Attention to Detail | 3.0 | |
| Cautiousness | 2.5 | |
| Integrity | 2.1 |
Side-by-side comparisons place two occupations’ pay, preparation, skills, and AI exposure on the same page — same data, same scale, no forecast.
Options the data surfaces for Medical and Clinical Laboratory Technicians — not advice or a forecast. Each is a real cross-link you can follow into the evidence.
Capabilities this work builds that are used across many other occupations.
Occupations O*NET rates as related — the nearby moves on the map.
How people typically prepare for this work.
On the global GenAI exposure gradient this work sits around the 58th percentile of 427 international occupations.
Medical and Clinical Laboratory Technicians sit at the 40th percentile of AI task overlap among U.S. occupations
Medical and Clinical Laboratory Technicians sit at the 40th percentile of AI task overlap among U.S. occupations • Medical and Clinical Laboratory Technicians rank in the 40th percentile (Moderate band) for AI task overlap across U.S. occupations — a measure of how much of the work today's AI can attempt, not how much is automated. (Eloundou et al. (GPTs are GPTs) + Felten AIOE) • Of the AI use actually observed for this work, 38% looks like augmentation (drafting, iterating, checking) rather than hands-off automation — from a Claude.ai usage sample, not a census. (2026-01-15-v4-plus-2025-03-27-v2) Source: Singulariki — "Medical and Clinical Laboratory Technicians". https://singulariki.com/roles/role-29-2012-00 Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.
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Every line is built only from figures this page already shows and cites. AI task overlap means what today's AI can attempt — not automation, job loss, or a forecast.
Every figure above traces to a named public dataset and the exact release below — not hand-written opinion. See the full methodology for what each measure does and does not mean.
Data compiled June 2, 2026. Figures are estimates, not advice.
Singulariki. "Medical and Clinical Laboratory Technicians." Singulariki: a source-backed encyclopedia of work. Built from O*NET 30.3; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026. https://singulariki.com/roles/role-29-2012-00
Singulariki. (2026). Medical and Clinical Laboratory Technicians. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-29-2012-00
@misc{singulariki-role-29-2012-00,
title = {Medical and Clinical Laboratory Technicians},
author = {{Singulariki}},
year = {2026},
note = {O*NET 30.3; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026},
url = {https://singulariki.com/roles/role-29-2012-00}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.