Medical and Clinical Laboratory Technologists
In short: today's best AI models could do about 24% of this job's working time (projected from METR's April 2026 measurement and Epoch's November 2026 index) if the work were set up for them, and about 29% by the end of 2028 if progress keeps its long-run pace. The conversations, in-person and hands-on work, about 71% of the time, stays with people.
Perform complex medical laboratory tests for diagnosis, treatment, and prevention of disease. May train or supervise staff.
$62,930 a year (for the broader BLS group this job sits in).
Reviewed on September 30, 2026: what each task is made of, and what handing it over would ask.
A typical 40-hour week
- AI could take on0 h
- A person checks AI's work10 h
- Desk work AI can't do yet2 h
- Stays with people28 h
Medical and Clinical Laboratory Technologists, now: of a 40-hour week, AI could take on 0 hours, 10 hours become checking its work, 2 hours are desk work it can't do yet, and 28 hours stay with people.
The largest pieces: Run quality assurance programs (about 3 h, a person checks); Check findings for accuracy (about 3 h, a person checks); Develop and standardize procedures (about 2 h, a person checks).
Estimates for a typical week of this job, if progress keeps its long-run pace, counting work the best models finish four times in five. Every task is below.
of the working time. Now is projected from METR's April 2026 measurement and Epoch's November 2026 index.
- 25%
- 4%
- 2%
- 4%
- 65%
Anthropic's data does not cover this job.
On the chosen pace and reliability. Estimate.
Share of the working time within reach, now to 2030
Change assumptionsHide assumptionsLong-run pace, four in five
What each choice means: , , , , . Every pace starts from .
At this date and pace, models finish tasks up to 2.4 work days long four times in five.
What handing it over would take, now
The 24% within reach splits by what a model would need. The dates, pace and reliability follow the controls above. Estimates.
of the working time. The material can be handed to a model and the result handed back.
of the working time. The model has to be connected to the system the work lives in.
is conversation short enough by length. This site leaves conversation with people, so it is not in the total.
How far this has come
With GPT-4, measured in March 2023, 0% of this job's working time was within reach at . With Claude 3.7 Sonnet, measured in February 2025, 1%. With Claude Mythos Preview (early), measured in April 2026, 14%. Today's estimate: 24%.
A backcast: today's task data with the best model METR had measured by each date. It shows how fast the models have moved, not what anyone forecast at the time.
Measured use over time
Of the Claude.ai conversations Anthropic sampled and tied to a work task, no reportable share went to this job's tasks in May 2026; 0 of its 15 tasks showed up. Within each of Anthropic's methods, never across a change: 0.048% to 0.06% (released February and March 2025); 0.036% to 0.017% (August 2025 to February 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.048% | 281 of 708 | 4 of 15 |
| Released March 2025 | 0.06% | 238 of 703 | 4 of 15 |
| The week of Aug 4, 2025 (released September 2025) | 0.036% | 283 of 655 | 4 of 15 |
| The week of Nov 13, 2025 (released January 2026) | 0.015% | 423 of 672 | 4 of 15 |
| The week of Feb 5, 2026 (released March 2026) | 0.017% | 423 of 677 | 4 of 15 |
| April 2026 (released June 2026) | none | n/a | 0 of 15 |
| May 2026 (released June 2026) | none | n/a | 0 of 15 |
Measured, not estimated: Anthropic's samples of Claude.ai conversations, each tied by a model to an O*NET task, from the Anthropic Economic Index. It says where Claude's use goes, not how much of this job's working time it covers, so it is not on the same scale as the reach above. The releases differ in their sample, their classifier and the smallest share they report (the June 2026 file rounds each task to a hundredth of a percent, so a smaller task reads as none), which is why a change of method starts a new line. At least 96% of each older release's task-tied use matched this site's tasks, and all of the newest. Claude.ai only, so use through other tools and other companies' models is not in it. Every job ranked.
Robots and the physical work
Anthropic rates 65% of this job's working time as physical work. For 60% of the working time, a robot has been shown doing most of the task somewhere: 30% in a purpose-built cell, 30% in a structured facility. 0.90 of 3, the 180th highest of the 923 jobs.
- Not physical 35%
- No robot shown 5%
- In a purpose-built cell 30%
- In a structured facility 30%
Anthropic's rating, not this site's estimate: Claude Opus 5, searching the web, rated each physical O*NET task by the kind of setting in which a robot it could cite (deployed, sold or demonstrated) does most of the task, weighted by its own estimate of each task's share of the time (What work can robots do?, September 30, 2026, data CC BY 4.0; every job ranked). A robot shown somewhere is not a robot in your building: cost, setup and safety decide that. The share within reach on this page still counts no body work. The robot behind each rated task is under the task below.
What changes for the people in this job
From the task-by-task review, by the end of 2028 on the long-run pace at four in five. It says which parts of the work stay with people and which change, not whether anyone keeps a job: that depends on decisions no data set can see.
What stays with people
70% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Analyze biological samples, the hands-on work, 11%
- Analyze body fluids, the hands-on work, 10%
- Study blood samples, the hands-on work, 10%
- Cultivate and identify microorganisms, the hands-on work, 7%
- Develop and standardize procedures, the hands-on work, 7%
- Operate and calibrate analyzers, the hands-on work, 6%
What becomes checking the machine
29% of the working time: desk work a model could do by then, in tasks where a mistake costs something or a licensed person signs. A person checks it.
- Develop and standardize procedures, severe if wrong, 11%
- Run quality assurance programs, severe if wrong, 8%
- Check findings for accuracy, severe if wrong, 7%
- Enter test results, severe if wrong, 2%
- Supervise and train lab staff, costly if wrong, 2%
What to learn
- Judgment where errors are severe. Some tasks are severe if wrong. Knowing when not to trust an output matters more there than speed.
- The hands-on craft. About 65% of the time is hands-on work, which no model here does; robots are rated separately on this page.
- Signing off under your license. Some tasks need a licensed, certified or sworn person to do or sign them. The license, and the judgment it stands for, stays with the person.
- Reviewing work you did not do yourself. The tasks under What becomes checking the machine, where a mistake costs something, stay a person's to check or sign: spotting what a draft gets wrong is a skill of its own.
- Briefing a model and checking its drafts. About 25% of the time is documents and data, the part models reach first: writing a clear brief, giving the right material, and checking what comes back.
Your own version of this job: read it against your job description. The headline is free; the full personal report, every task with its timeline and what to learn, is $19 (a sample).
The tasks
Sorted by . 15 tasks from .
| Task | ||||
|---|---|---|---|---|
| Develop, standardize, evaluate, or modify procedures, techniques, or tests used in the analysis of specimens or in medical laboratory experiments.Working out new procedures on paper and proving them at the bench.Done more than yearly by most who do it. AI observed on this task.Robots: in a purpose-built cell, Perkin-Elmer MultiProbe II robotic liquid handler with LC-MS/MS (Perkin-Elmer; Quest Diagnostics) (sold). Anthropic's rating. | 18% | 6.7 h1.7 h to 2.5 work days | Documents 60%, hands-on 40% | 33%Desk part half by now |
| Analyze samples of biological material for chemical content or reaction.Chemical analysis of samples at the bench.Done hourly or more by most who do it. Robots: in a structured facility, Tempus600 pneumatic transport with Sysmex GLP robot reception system (TIMEDICO / Sysmex) (deployed). Anthropic's rating. | 11% | 38 min13 min to 1.3 h | Hands-on 100% | Stays with people |
| Conduct chemical analysis of body fluids, including blood, urine, or spinal fluid, to determine presence of normal or abnormal components.Chemical analysis of blood, urine and spinal fluid.Done hourly or more by most who do it. Robots: in a purpose-built cell, Total laboratory automation lines (Abbott ACCELERATOR, Roche cobas connection modules, Siemens Aptio, Beckman Power Express) (Abbott, Roche, Siemens Healthineers, Beckman Coulter) (deployed). Anthropic's rating. | 10% | 50 min17 min to 1.7 h | Hands-on 100% | Stays with people |
| Collect and study blood samples to determine the number of cells, their morphology, or their blood group, blood type, or compatibility for transfusion purposes, using microscopic techniques.Counting and typing cells under the microscope.Done hourly or more by most who do it. Robots: in a structured facility, Sysmex XN-9100 (XN modules + SP-50 slidemaker/stainer + DI-60 digital cell imaging + TS-10 sorter) (sold). Anthropic's rating. | 10% | 50 min17 min to 2.5 h | Hands-on 100% | Stays with people |
| Establish or monitor quality assurance programs or activities to ensure the accuracy of laboratory results.Designing and monitoring the quality program, with the records.Done daily by most who do it. | 8% | 1.7 h25 min to 3.3 h | Documents 70%, systems 30% | 99%Half by now |
| Cultivate, isolate, or assist in identifying microbial organisms or perform various tests on these microorganisms.Culturing and testing organisms at the bench.Done daily by most who do it.Robots: in a purpose-built cell, Copan WASP / WASPLab full laboratory automation (deployed). Anthropic's rating. | 7% | 1.7 h50 min to 3.3 h | Hands-on 100% | Stays with people |
| Analyze laboratory findings to check the accuracy of the results.Reading the findings for errors before release.Done hourly or more by most who do it. AI observed on this task. | 7% | 25 min8 min to 50 min | Documents 100% | 100%Half by now |
| Supervise, train, or direct lab assistants, medical and clinical laboratory technicians or technologists, or other medical laboratory workers engaged in laboratory testing.Leading and teaching the lab staff, with the planning behind it.Done daily by most who do it. | 6% | 50 min25 min to 2.5 h | In person 70%, documents 30% | 30%Desk part half by now |
| Operate, calibrate, or maintain equipment used in quantitative or qualitative analysis, such as spectrophotometers, calorimeters, flame photometers, or computer-controlled analyzers.Running and calibrating spectrophotometers and analyzers.Done daily by most who do it. Robots: in a structured facility, Total laboratory automation (Abbott/Roche/Siemens/Beckman track systems); cobots; AMRs (Multiple) (deployed). Anthropic's rating. | 6% | 38 min17 min to 1.3 h | Hands-on 100% | Stays with people |
| Set up, clean, and maintain laboratory equipment.Setting up and cleaning the equipment.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 5% | 38 min13 min to 1.7 h | Hands-on 100% | Stays with people |
| Select and prepare specimens and media for cell cultures, using aseptic technique and knowledge of medium components and cell requirements.Aseptic preparation of specimens and media.Done hourly or more by most who do it. Robots: in a purpose-built cell, Copan WASP (sold). Anthropic's rating. | 5% | 42 min21 min to 1.4 h | Hands-on 100% | Stays with people |
| Obtain, cut, stain, and mount biological material on slides for microscopic study and diagnosis, following standard laboratory procedures.Cutting, staining and mounting material on slides.Done several times a day by most who do it. Robots: in a structured facility, Sysmex SP-50 slidemaker-stainer (with XN-3100/XN-9100) (sold). Anthropic's rating. | 3% | 33 min17 min to 1.1 h | Hands-on 100% | Stays with people |
Within reach, per task: the share of the task's time whose instances are short enough for a model to finish at the chosen date, pace and reliability. Half by: the date half of that time comes within reach. Made of: how the task's time splits among five kinds of doing. Only the documents and systems parts can count as within reach, so a task that is 30% documents can be at most 30% within reach.
Jobs that share skills with this one
From O*NET's related occupations. Within reach now and by the end of 2028, long-run pace, four in five.
Where this job works
The industry groups that employ the most of it (BLS, May 2025). Counts are for the broader BLS group this job sits in.
Where the most of these jobs are
The metro areas with the most people in it (BLS, May 2025). Counts are for the broader BLS group this job sits in.
Questions about this job
- How much of the work of Medical and Clinical Laboratory Technologists is within reach of AI now?
- An estimated 24% of the working time is within reach of AI models now and 29% by the end of 2028, on METR's long-run pace at four in five. Within reach means a model could finish work that long at that reliability. It is not a forecast of jobs lost or of savings.
- Which tasks of Medical and Clinical Laboratory Technologists come within reach first?
- Weighted by the time each takes, the tasks with the most within reach now (projected from METR's April 2026 measurement and Epoch's November 2026 index) are: Run quality assurance programs (99% of the task's time now); Check findings for accuracy (100% of the task's time now); and Develop and standardize procedures (33% of the task's time now, 60% by the end of 2028).
- Which tasks of Medical and Clinical Laboratory Technologists stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Analyze biological samples; Analyze body fluids; and Study blood samples. Together such tasks are about 59% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Medical and Clinical Laboratory Technologists learn as AI takes on more of the work?
- By the job's own task-by-task review, the first things to learn are judgment where errors are severe; the hands-on craft; and signing off under your license. By the end of 2028 on the long-run pace at four in five, about 70% of the working time stays with people, 29% becomes checking a model's work and 0% could be handed over with lighter checks. It says which parts of the work change, never whether anyone keeps a job.
- Do people already use AI for the work of Medical and Clinical Laboratory Technologists?
- In the Claude.ai conversations Anthropic sampled for May 2026, no reportable share went to this job's tasks. These are measures of use, not of how much of the work AI could finish, and they cover Claude only.
- Can robots do the physical work of Medical and Clinical Laboratory Technologists?
- Anthropic's robot exposure rating (September 2026) finds 65% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 60% of the working time, 30% in a structured facility. Its index is 0.90 of 3. One example: Tempus600 pneumatic transport with Sysmex GLP robot reception system for "analyze biological samples". A robot shown somewhere is not one in every workplace; this site's own estimates still count no physical work as within reach.
- How is this estimated?
- From the 15 tasks O*NET lists for the occupation, each with an estimated length checked against GDPval and a share of the working time, reviewed one task at a time on September 30, 2026 for what each is made of (documents, business systems, conversation, in person, hands-on), and METR's measurements of how long a task the best AI models can finish, carried forward to the date from the latest, Claude Mythos Preview (early) in April 2026. Data checked November 10, 2026.
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