Pharmacy Technicians
In short: today's best AI models could do about 34% 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 the same by the end of 2028 if progress keeps its long-run pace. The conversations, in-person and hands-on work, about 66% of the time, stays with people.
Prepare medications under the direction of a pharmacist. May measure, mix, count out, label, and record amounts and dosages of medications according to prescription orders.
471,680 people do this job in the US. $45,750 a year.
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 work14 h
- Desk work AI can't do yet0 h
- Stays with people26 h
Pharmacy Technicians, now: of a 40-hour week, AI could take on 0 hours, 14 hours become checking its work, 0 hours are desk work it can't do yet, and 26 hours stay with people.
The largest pieces: Process insurance claims (about 3 h, a person checks); Receive supplies and check for outdated stock (about 2 h, a person checks); Maintain patient medication profiles (about 2 h, a person checks).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.
- 8%
- 26%
- 2%
- 4%
- 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 34% 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, 10%. With Claude Mythos Preview (early), measured in April 2026, 33%. Today's estimate: 34%.
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 21 tasks showed up. Within each of Anthropic's methods, never across a change: 0.0026% to 0.018% (released February and March 2025); 0.051% to 0.021% (August 2025 to February 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.0026% | 673 of 708 | 1 of 21 |
| Released March 2025 | 0.018% | 435 of 703 | 3 of 21 |
| The week of Aug 4, 2025 (released September 2025) | 0.051% | 242 of 655 | 2 of 21 |
| The week of Nov 13, 2025 (released January 2026) | 0.017% | 415 of 672 | 2 of 21 |
| The week of Feb 5, 2026 (released March 2026) | 0.021% | 396 of 677 | 1 of 21 |
| April 2026 (released June 2026) | none | n/a | 0 of 21 |
| May 2026 (released June 2026) | none | n/a | 0 of 21 |
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 52% of this job's working time as physical work. For 52% of the working time, a robot has been shown doing most of the task somewhere: 42% in a purpose-built cell, 10% in a structured facility. 0.62 of 3, the 276th highest of the 923 jobs.
- Not physical 48%
- In a purpose-built cell 42%
- In a structured facility 10%
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
66% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Receive supplies and check for outdated stock, the hands-on work, 11%
- Mix pharmaceutical preparations, the hands-on work, 8%
- Keep drugs stored securely, the hands-on work, 8%
- Clean equipment and sterilize glassware, the hands-on work, 6%
- Draw medication into sterile syringes, the hands-on work, 5%
- Prepare IV packs under sterile conditions, the hands-on work, 5%
What becomes checking the machine
34% 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.
- Process insurance claims, costly if wrong, 8%
- Receive supplies and check for outdated stock, severe if wrong, 5%
- Maintain patient medication profiles, severe if wrong, 5%
- Order, label and count stock, costly if wrong, 3%
- Receive and check prescriptions, a licensed person signs, 3%
- Enter prescriptions into the computer, a licensed person signs, 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 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 or sign: spotting what a draft gets wrong is a skill of its own.
- 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.
- Running AI inside the business systems. About 26% 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.
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 . 21 tasks from .
| Task | ||||
|---|---|---|---|---|
| Receive and store incoming supplies, verify quantities against invoices, check for outdated medications in current inventory, and inform supervisors of stock needs and shortages.Counting deliveries against invoices and checking dates on the shelves.Done daily by most who do it. Robots: in a purpose-built cell, BD Rowa EasyLoad / Vmax pharmacy storage robot (sold). Anthropic's rating. | 15% | 50 min17 min to 1.7 h | Hands-on 70%, documents 30% | 30%Desk part half by now |
| Maintain proper storage and security conditions for drugs.Checking storage and locks, with the log kept.Done hourly or more by most who do it. Robots: in a purpose-built cell, BD Rowa EasyLoad / ProLog (input system for Rowa Vmax and Smart) (sold). Anthropic's rating. | 10% | 25 min13 min to 50 min | Hands-on 80%, systems 20% | 20%Desk part half by now |
| Mix pharmaceutical preparations, according to written prescriptions.Compounding by hand to the prescription.Done hourly or more by most who do it. Robots: in a purpose-built cell, RIVA automated IV compounding system (ARxIUM) (deployed). Anthropic's rating. | 8% | 25 min8 min to 50 min | Hands-on 100% | Stays with people |
| Prepare and process medical insurance claim forms and records.Claim entry and follow-up in the system.Done hourly or more by most who do it. | 8% | 21 min8 min to 42 min | Systems 80%, documents 20% | 100%Half by now |
| Order, label, and count stock of medications, chemicals, or supplies and enter inventory data into computer.Counting by hand, and the inventory entry.Done daily by most who do it. Robots: in a purpose-built cell, BD Rowa Vmax with ProLog/iProLog automatic input (sold). Anthropic's rating. | 7% | 29 min13 min to 1.3 h | Hands-on 60%, systems 40% | 40%Desk part half by now |
| Clean and help maintain equipment or work areas and sterilize glassware, according to prescribed methods.Cleaning by hand.Done daily by most who do it. Robots: in a purpose-built cell, Rosie (CleanBotix) (sold). Anthropic's rating. | 6% | 21 min8 min to 38 min | Hands-on 100% | Stays with people |
| Transfer medication from vials to the appropriate number of sterile, disposable syringes, using aseptic techniques.Hands-on work under aseptic technique.Done hourly or more by most who do it.Robots: in a purpose-built cell, IntelliFill i.v. (ForHealth Technologies / Baxa / ARxIUM) (deployed). Anthropic's rating. | 5% | 21 min8 min to 50 min | Hands-on 100% | Stays with people |
| Prepack bulk medicines, fill bottles with prescribed medications, and type and affix labels.Counting and bottling by hand, with the label printed.Done hourly or more by most who do it. Robots: in a purpose-built cell, ScriptPro SP 200 / CRS 150 Robotic Prescription Dispensing System (sold). Anthropic's rating. | 5% | 13 min4 min to 29 min | Hands-on 80%, systems 20% | 20%Desk part half by now |
| Restock intravenous (IV) supplies and add measured drugs or nutrients to IV solutions under sterile conditions to prepare IV packs for various uses, such as chemotherapy medication.Hands-on sterile compounding.Done hourly or more by most who do it.Robots: in a purpose-built cell, RIVA (Robotic IV Automation) (ARxIUM) (deployed). Anthropic's rating. | 5% | 38 min17 min to 1.3 h | Hands-on 100% | Stays with people |
| Establish or maintain patient profiles, including lists of medications taken by individual patients.Entries in each patient's profile.Done hourly or more by most who do it. | 5% | 10 min4 min to 21 min | Systems 100% | 100%Half by now |
| Supply and monitor robotic machines that dispense medicine into containers and label the containers.Loading the machine by hand and watching its readout.Done hourly or more by most who do it.Robots: in a purpose-built cell, Parata Max / Max 2 high-speed vial-filling robot (deployed). Anthropic's rating. | 5% | 21 min8 min to 50 min | Hands-on 70%, systems 30% | 30%Desk part half by now |
| Receive written prescription or refill requests and verify that information is complete and accurate.Reading the prescription for gaps, a word with the customer, and the entry.Done hourly or more by most who do it. | 3% | 6 min3 min to 13 min | Documents 50%, systems 30%, in person 20% | 80%Desk part half by now |
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 Pharmacy Technicians is within reach of AI now?
- An estimated 34% of the working time is within reach of AI models now and 34% 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 Pharmacy 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: Process insurance claims (100% of the task's time now); Receive supplies and check for outdated stock (30% of the task's time now); and Maintain patient medication profiles (100% of the task's time now).
- Which tasks of Pharmacy Technicians stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Mix pharmaceutical preparations; Clean equipment and sterilize glassware; and Draw medication into sterile syringes. Together such tasks are about 33% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Pharmacy 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 judgment where errors are severe; the hands-on craft; and reviewing work you did not do yourself. By the end of 2028 on the long-run pace at four in five, about 66% of the working time stays with people, 34% 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 Pharmacy Technicians?
- In the Claude.ai conversations Anthropic sampled for May 2026, no reportable share went to this job's tasks. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 7%. 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 Pharmacy Technicians?
- Anthropic's robot exposure rating (September 2026) finds 52% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 52% of the working time, 10% in a structured facility. Its index is 0.62 of 3. One example: Moxi for "deliver medications". 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 21 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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