Ophthalmic Medical Technicians
In short: today's best AI models could do about 14% 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 86% of the time, stays with people.
Assist ophthalmologists by performing ophthalmic clinical functions. May administer eye exams, administer eye medications, and instruct the patient in care and use of corrective lenses.
71,010 people do this job in the US. $45,570 a year.
Reviewed on October 1, 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 work5 h
- Desk work AI can't do yet0 h
- Stays with people35 h
Ophthalmic Medical Technicians, now: of a 40-hour week, AI could take on 0 hours, 5 hours become checking its work, 0 hours are desk work it can't do yet, and 35 hours stay with people.
The largest pieces: Take medical histories (about 1 h, a person checks); Test eye muscle function (under an hour, a person checks); Measure lens power (under an hour, 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.
- 0%
- 14%
- 0%
- 9%
- 77%
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 14% 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, 6%. With Claude Mythos Preview (early), measured in April 2026, 14%. Today's estimate: 14%.
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
None of this job's 20 tasks showed up in the Claude.ai conversations Anthropic sampled in any of its 7 releases, from February 2025 to May 2026.
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 82% of this job's working time as physical work. For 55% of the working time, a robot has been shown doing most of the task somewhere: 19% in a purpose-built cell, 36% in a structured facility. 0.90 of 3, the 176th highest of the 923 jobs.
- Not physical 18%
- No robot shown 27%
- In a purpose-built cell 19%
- In a structured facility 36%
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
85% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Operate ophthalmic equipment, the hands-on work, 14%
- Test eye muscle function, the hands-on work, 8%
- Measure eye pressure, the hands-on work, 7%
- Measure visual acuity, the hands-on work, 6%
- Take medical histories, the in-person work, 6%
- Test fields of vision, the hands-on work, 6%
What becomes checking the machine
13% 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.
- Take medical histories, severe if wrong, 3%
- Test eye muscle function, severe if wrong, 2%
- Measure lens power, costly if wrong, 2%
- Measure eye pressure, severe if wrong, 2%
- Measure visual acuity, severe if wrong, 2%
- Test fields of vision, severe if wrong, 1%
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 77% of the time is hands-on work, which no model here does; robots are rated separately on this page.
- Handling protected records. Much of the work touches protected personal records: knowing what may be shared with a model, and how, is part of the job.
- 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.
- Running AI inside the business systems. About 14% 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 . 20 tasks from .
| Task | ||||
|---|---|---|---|---|
| Operate ophthalmic equipment, such as autorefractors, phoropters, tomographs, or retinoscopes.Running the instruments on the patient.Done hourly or more by most who do it. Robots: in a structured facility, Eyebot S1 vision-test kiosk (deployed). Anthropic's rating. | 14% | 13 min4 min to 25 min | Hands-on 100% | Stays with people |
| Conduct ocular motility tests to measure function of eye muscles.Motility tests with the patient, charted.Done hourly or more by most who do it. Robots: in a purpose-built cell, Strabismus video goggles (infrared video goggles with laser target projection and LCD shutters) (University of Bern / Inselspital and collaborators) (demonstrated). Anthropic's rating. | 10% | 13 min4 min to 25 min | Hands-on 80%, systems 20% | 20%Desk part half by now |
| Conduct tonometry or tonography tests to measure intraocular pressure.Tonometry at the instrument, charted.Done hourly or more by most who do it. Robots: no robot shown. Anthropic's rating. | 9% | 8 min4 min to 17 min | Hands-on 80%, systems 20% | 20%Desk part half by now |
| Take and document patients' medical histories.Asking the patient and entering the history.Done hourly or more by most who do it. AI observed on this task. | 9% | 8 min4 min to 17 min | In person 70%, systems 30% | 30%Desk part half by now |
| Measure visual acuity, including near, distance, pinhole, or dynamic visual acuity, using appropriate tests.Running the acuity tests with the patient and charting the result.Done hourly or more by most who do it. Robots: in a structured facility, NIDEK/Marco TS-610 with Fully Assisted Refraction System (FARS) (sold). Anthropic's rating. | 8% | 7 min3 min to 13 min | Hands-on 80%, systems 20% | 20%Desk part half by now |
| Conduct visual field tests to measure field of vision.Visual field testing at the instrument, charted.Done several times a day by most who do it. Robots: in a purpose-built cell, ZEISS Humphrey Field Analyzer 3 (HFA3) with automated eye alignment and Liquid Trial Lens (Carl Zeiss Meditec) (sold). Anthropic's rating. | 7% | 17 min8 min to 33 min | Hands-on 80%, systems 20% | 20%Desk part half by now |
| Take anatomical or functional ocular measurements of the eye or surrounding tissue, such as axial length measurements.Measurements at the instrument, charted.Done several times a day by most who do it. Robots: in a structured facility, ARGOS Optical Biometer (Alcon) (sold). Anthropic's rating. | 7% | 13 min4 min to 25 min | Hands-on 80%, systems 20% | 20%Desk part half by now |
| Measure and record lens power, using lensometers.Reading the lenses on the lensometer and noting the power in the chart.Done hourly or more by most who do it. Robots: in a purpose-built cell, Automation & Robotics AutoMapper V3 (with integrated Dual LensMapper) (sold). Anthropic's rating. | 6% | 6 min3 min to 13 min | Hands-on 70%, systems 30% | 30%Desk part half by now |
| Assess refractive conditions of eyes, using retinoscopes.Retinoscopy on the patient.Done hourly or more by most who do it. Robots: in a structured facility, Nidek ARK-F / AR-F auto ref/keratometer (sold). Anthropic's rating. | 5% | 13 min4 min to 25 min | Hands-on 100% | Stays with people |
| Assist physicians in performing ophthalmic procedures, including surgery.Hands-on assisting during procedures and surgery.Done more than weekly by most who do it. Robots: no robot shown. Anthropic's rating. | 5% | 29 min13 min to 1.3 h | Hands-on 100% | Stays with people |
| Measure corneal curvature with keratometers or ophthalmometers to aid in the diagnosis of conditions, such as astigmatism.Keratometry at the instrument, charted.Done daily by most who do it. Robots: in a structured facility, NIDEK ARK-F / AR-F Auto Ref/Keratometer (sold). Anthropic's rating. | 4% | 8 min4 min to 17 min | Hands-on 80%, systems 20% | 20%Desk part half by now |
| Administer topical ophthalmic or oral medications.Putting in the drops or handing over the tablets, as the physician directs.Done hourly or more by most who do it. Robots: no robot shown. Anthropic's rating. | 4% | 4 min3 min to 8 min | 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 Ophthalmic Medical Technicians is within reach of AI now?
- An estimated 14% of the working time is within reach of AI models now and 14% 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 Ophthalmic Medical 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: Take medical histories (30% of the task's time now); Test eye muscle function (20% of the task's time now); and Measure lens power (30% of the task's time now).
- Which tasks of Ophthalmic Medical Technicians stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Operate ophthalmic equipment; Assess refraction with retinoscopes; and Assist with eye procedures. Together such tasks are about 39% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Ophthalmic Medical 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 handling protected records. By the end of 2028 on the long-run pace at four in five, about 85% of the working time stays with people, 13% 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 Ophthalmic Medical 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 0%. 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 Ophthalmic Medical Technicians?
- Anthropic's robot exposure rating (September 2026) finds 82% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 55% of the working time, 36% in a structured facility. Its index is 0.90 of 3. One example: Eyebot S1 vision-test kiosk for "operate ophthalmic equipment". 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 20 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 1, 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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