Biological Technicians
In short: today's best AI models could do about 35% 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 37% by the end of 2028 if progress keeps its long-run pace. The conversations, in-person and hands-on work, about 63% of the time, stays with people.
Assist biological and medical scientists. Set up, operate, and maintain laboratory instruments and equipment, monitor experiments, collect data and samples, make observations, and calculate and record results. May analyze organic substances, such as blood, food, and drugs.
69,620 people do this job in the US. $57,510 a year.
Reviewed on October 2, 2026: what each task is made of, and what handing it over would ask.
A typical 40-hour week
- AI could take on1 h
- A person checks AI's work13 h
- Desk work AI can't do yet1 h
- Stays with people25 h
Biological Technicians, now: of a 40-hour week, AI could take on 1 hours, 13 hours become checking its work, 1 hours are desk work it can't do yet, and 25 hours stay with people.
The largest pieces: Run computerized lab equipment (about 3 h, a person checks); Collect samples and assist research (about 3 h, a person checks); Enter data (about 1 h).
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.
- 22%
- 16%
- 0%
- 3%
- 60%
of the work: Anthropic's measure of what people already bring to Claude at work (2025). It counts help with part of a task, so it can be higher than the share within reach.
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 35% 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, 0%. With Claude Mythos Preview (early), measured in April 2026, 15%. Today's estimate: 35%.
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, 0.074% went to this job's tasks in May 2026, the 194th largest of the 447 jobs that showed up at all; 3 of its 18 tasks showed up. Within each of Anthropic's methods, never across a change: 0.13% to 0.16% (released February and March 2025); 0.18% to 0.11% (August 2025 to February 2026); 0.079% to 0.074% (April to May 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.13% | 130 of 708 | 4 of 18 |
| Released March 2025 | 0.16% | 110 of 703 | 7 of 18 |
| The week of Aug 4, 2025 (released September 2025) | 0.18% | 103 of 655 | 4 of 18 |
| The week of Nov 13, 2025 (released January 2026) | 0.14% | 117 of 672 | 5 of 18 |
| The week of Feb 5, 2026 (released March 2026) | 0.11% | 144 of 677 | 3 of 18 |
| April 2026 (released June 2026) | 0.079% | 179 of 434 | 3 of 18 |
| May 2026 (released June 2026) | 0.074% | 194 of 447 | 3 of 18 |
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 79% of this job's working time as physical work. For 79% of the working time, a robot has been shown doing most of the task somewhere: 51% in a purpose-built cell, 28% in a structured facility. 1.08 of 3, the 85th highest of the 923 jobs.
- Not physical 21%
- In a purpose-built cell 51%
- In a structured facility 28%
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
62% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Collect samples and assist research, the hands-on work, 11%
- Help make pharmaceutical preparations, the hands-on work, 8%
- Run standard lab tests, the hands-on work, 7%
- Run hatchery or greenhouse programs, the in-person work, 5%
- Run computerized lab equipment, the hands-on work, 5%
- Set up and maintain equipment, the hands-on work, 5%
What becomes checking the machine
33% 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. Another 4% is desk work that is small if wrong, which can be handed over with lighter checks.
- Run computerized lab equipment, costly if wrong, 8%
- Collect samples and assist research, costly if wrong, 8%
- Analyze data and write reports, costly if wrong, 3%
- Help make pharmaceutical preparations, severe if wrong, 3%
- Watch experiments and record data, costly if wrong, 3%
- Keep the lab log, costly if wrong, 2%
What to learn
- The hands-on craft. About 60% of the time is hands-on work, which no model here does; robots are rated separately on this page.
- 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: spotting what a draft gets wrong is a skill of its own.
- Briefing a model and checking its drafts. About 22% 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.
- Running AI inside the business systems. About 16% of the time is work inside business systems, which a model can do only once it is connected: knowing the systems well enough to set that up and watch it.
- Judgment where errors are severe. Some tasks are severe if wrong. Knowing when not to trust an output matters more there than speed.
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 . 18 tasks from .
| Task | ||||
|---|---|---|---|---|
| Conduct research, or assist in the conduct of research, including the collection of information and samples, such as blood, water, soil, plants and animals.Gathering samples in the field and the lab, and working up the information.Done hourly or more by most who do it. Robots: in a structured facility, Mobile robotic chemist (Burger et al., University of Liverpool) (demonstrated). Anthropic's rating. | 19% | 3.3 h50 min to 6.7 h | Hands-on 60%, documents 40% | 37%Desk part half by now |
| Use computers, computer-interfaced equipment, robotics or high-technology industrial applications to perform work duties.Operating the instruments through their consoles and handling the samples.Done several times a day by most who do it. Robots: in a purpose-built cell, Mobile robotic chemist (KUKA KMR iiwa based) (University of Liverpool) (demonstrated). Anthropic's rating. | 13% | 1.7 h25 min to 3.3 h | Systems 60%, hands-on 40% | 59%Desk part half by now |
| Participate in the research, development, or manufacturing of medicinal and pharmaceutical preparations.Bench and production work on medicines, with the records.Done daily by most who do it.Robots: in a purpose-built cell, AstraZeneca / HighRes Biosolutions modular unguarded HTS automation platforms (deployed). Anthropic's rating. | 11% | 3.3 h50 min to 1 work day | Hands-on 70%, documents 30% | 26%Desk part half by now |
| Conduct standardized biological, microbiological or biochemical tests and laboratory analyses to evaluate the quantity or quality of physical or chemical substances in food or other products.Standard assays at the bench, with the results worked up.Done more than weekly by most who do it. Robots: in a purpose-built cell, BD Kiestra TLA (3rd generation) (Becton, Dickinson and Company) (sold). Anthropic's rating. | 8% | 2.5 h50 min to 6.7 h | Hands-on 80%, documents 20% | 19%Desk part half by now |
| Conduct or supervise operational programs, such as fish hatcheries, greenhouses and livestock production programs.Running the facility: on the floor with the crew and the stock, with the plan behind it.Done daily by most who do it. | 7% | 6.7 h1.7 h to 1.7 work days | In person 40%, hands-on 40%, documents 20% | 14%Desk part half by now |
| Monitor and observe experiments, recording production and test data for evaluation by research personnel.Watching the runs at the bench and entering the readings.Done several times a day by most who do it. Robots: in a structured facility, Mobile robotic chemist (Burger et al.) (University of Liverpool) (demonstrated). Anthropic's rating. | 6% | 1.3 h25 min to 3.3 h | Hands-on 60%, systems 40% | 40%Desk part half by now |
| Monitor laboratory work to ensure compliance with set standards.Watching the bench work and reading the records against the standards.Done daily by most who do it. | 5% | 1.3 h25 min to 2.5 h | Hands-on 60%, documents 40% | 40%Desk part half by now |
| Set up, adjust, calibrate, clean, maintain, and troubleshoot laboratory and field equipment.Hands on the instruments: calibrating, cleaning and fixing.Done daily by most who do it. Robots: in a purpose-built cell, METTLER TOLEDO Robotic Mass Comparators (a10XL, e5, e100, a107) (Mettler-Toledo) (sold). Anthropic's rating. | 5% | 1.7 h25 min to 4.2 h | Hands-on 100% | Stays with people |
| Provide technical support and services for scientists and engineers working in fields such as agriculture, environmental science, resource management, biology, and health sciences.Bench work and data for the scientists, as asked.Done more than weekly by most who do it.Robots: in a purpose-built cell, Ginkgo Cloud Lab / Reconfigurable Automation Carts (RACs) (sold). Anthropic's rating. | 4% | 1.7 h25 min to 5 h | Hands-on 60%, documents 40% | 38%Desk part half by now |
| Examine animals and specimens to detect the presence of disease or other problems.Looking over the animals and specimens at the bench for signs of disease.Done daily by most who do it. Robots: in a purpose-built cell, VETSCAN IMAGYST (Grundium Ocus scanner + AI) (Zoetis) (sold). Anthropic's rating. | 4% | 50 min17 min to 2.5 h | Hands-on 100% | Stays with people |
| Clean, maintain and prepare supplies and work areas.Cleaning benches and readying supplies.Done daily by most who do it. Robots: in a purpose-built cell, UVD Robot (deployed). Anthropic's rating. | 4% | 50 min17 min to 2.5 h | Hands-on 100% | Stays with people |
| Isolate, identify and prepare specimens for examination.Bench work isolating and readying specimens.Done more than weekly by most who do it. Robots: in a purpose-built cell, Copan WASP / WASPLab / Colibrí / PhenoMATRIX (sold). Anthropic's rating. | 4% | 1.3 h25 min to 3.3 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).
Where the most of these jobs are
The metro areas with the most people in it (BLS, May 2025).
Questions about this job
- How much of the work of Biological Technicians is within reach of AI now?
- An estimated 35% of the working time is within reach of AI models now and 37% 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 Biological Technicians 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 computerized lab equipment (59% of the task's time now); Collect samples and assist research (37% of the task's time now); and Enter data (100% of the task's time now).
- Which tasks of Biological Technicians stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Set up and maintain equipment; Examine animals and specimens; and Clean and prepare the lab. Together such tasks are about 17% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Biological Technicians learn as AI takes on more of the work?
- By the job's own task-by-task review, the first things to learn are the hands-on craft; reviewing work you did not do yourself; and briefing a model and checking its drafts. By the end of 2028 on the long-run pace at four in five, about 62% of the working time stays with people, 33% becomes checking a model's work and 4% 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 Biological Technicians?
- In the Claude.ai conversations Anthropic sampled for May 2026 and tied to a work task, 0.074% went to this job's tasks, the 194th largest share of the 447 jobs that showed up; 3 of its 18 tasks appeared. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 6%. 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 Biological Technicians?
- Anthropic's robot exposure rating (September 2026) finds 79% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 79% of the working time, 28% in a structured facility. Its index is 1.08 of 3. One example: Mobile robotic chemist (Burger et al., University of Liverpool) for "collect samples and assist research". 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 18 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 October 2, 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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