Opticians, Dispensing
In short: today's best AI models could do about 15% 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 85% of the time, stays with people.
Design, measure, fit, and adapt lenses and frames for client according to written optical prescription or specification. Assist client with inserting, removing, and caring for contact lenses. Assist client with selecting frames. Measure customer for size of eyeglasses and coordinate frames with facial and eye measurements and optical prescription. Prepare work order for optical laboratory containing instructions for grinding and mounting lenses in frames. Verify exactness of finished lens spectacles. Adjust frame and lens position to fit client. May shape or reshape frames. Includes contact lens opticians.
73,530 people do this job in the US. $47,260 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 work6 h
- Desk work AI can't do yet0 h
- Stays with people34 h
Opticians, Dispensing, now: of a 40-hour week, AI could take on 0 hours, 6 hours become checking its work, 0 hours are desk work it can't do yet, and 34 hours stay with people.
The largest pieces: Do shop administration (about 2 h, a person checks); Prepare lens work orders (about 1 h, a person checks); Keep prescription and payment records (about 1 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.
- 4%
- 11%
- 1%
- 38%
- 46%
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 15% 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, 3%. With Claude Mythos Preview (early), measured in April 2026, 15%. Today's estimate: 15%.
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 21 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 52% of this job's working time as physical work. For 15% of the working time, a robot has been shown doing most of the task somewhere: 15% in a purpose-built cell. 0.15 of 3, the 478th highest of the 923 jobs.
- Not physical 48%
- No robot shown 37%
- In a purpose-built cell 15%
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.
- Help clients choose frames, the in-person work, 9%
- Recommend lenses and frames, the in-person work, 9%
- Fabricate lenses to prescription, the hands-on work, 8%
- Assemble eyeglasses, the hands-on work, 8%
- Arrange merchandise displays, the hands-on work, 6%
- Sell eyewear, the in-person work, 6%
What becomes checking the machine
15% 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.
- Do shop administration, costly if wrong, 5%
- Prepare lens work orders, costly if wrong, 3%
- Keep prescription and payment records, costly if wrong, 3%
- Order frames and lenses, costly if wrong, 2%
- Match prescriptions to clients' needs, costly if wrong, 2%
- Verify prescriptions and records, costly if wrong, 0.6%
What to learn
- The hands-on craft. About 46% of the time is hands-on work, which no model here does; robots are rated separately on this page.
- The conversations. About 39% of the time is conversation and in-person work, which this site leaves with people: listening, explaining, persuading, calming.
- Dealing with people outside the organization. Customers, patients, suppliers or the public: trust with them is built by a 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: spotting what a draft gets wrong is a skill of its own.
- Running AI inside the business systems. About 11% 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 | ||||
|---|---|---|---|---|
| Assist clients in selecting frames according to style and color, and ensure that frames are coordinated with facial and eye measurements and optical prescriptions.On the floor with the client trying frames.Done hourly or more by most who do it. Robots: no robot shown. Anthropic's rating. | 9% | 25 min13 min to 46 min | In person 80%, hands-on 20% | Stays with people |
| Recommend specific lenses, lens coatings, and frames to suit client needs.Advising the client at the counter.Done hourly or more by most who do it. | 9% | 25 min13 min to 42 min | In person 100% | Stays with people |
| Fabricate lenses to meet prescription specifications.Making the lenses on the lab equipment to the prescription.Done daily by most who do it. Robots: in a purpose-built cell, MEI EZline / Stackers-Destackers feeding system for MEI lens edgers (sold). Anthropic's rating. | 8% | 1.3 h25 min to 2.5 h | Hands-on 100% | Stays with people |
| Assemble eyeglasses by cutting and edging lenses, and fitting the lenses into frames.Cutting, edging and fitting lenses into frames at the bench.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 8% | 1.1 h25 min to 1.7 h | Hands-on 100% | Stays with people |
| Evaluate prescriptions in conjunction with clients' vocational and avocational visual requirements.Talking through how the client uses their eyes, and reading the prescription against it.Done hourly or more by most who do it. | 6% | 21 min8 min to 38 min | In person 70%, documents 30% | 30%Desk part half by now |
| Arrange and maintain displays of optical merchandise.Setting out and tidying the displays.Done several times a day by most who do it. Robots: in a purpose-built cell, UR5 + Robotiq gripper machine-tending cell (Universal Robots / Robotiq) (deployed). Anthropic's rating. | 6% | 38 min17 min to 1.3 h | Hands-on 100% | Stays with people |
| Sell goods such as contact lenses, spectacles, sunglasses, and goods related to eyes, in general.Selling on the shop floor, with the goods handled.Done hourly or more by most who do it. | 6% | 17 min8 min to 38 min | In person 80%, hands-on 20% | Stays with people |
| Supervise the training of student opticians.Teaching students at the bench and the counter.Done daily by most who do it. | 5% | 1.3 h25 min to 2.5 h | In person 100% | Stays with people |
| Grind lens edges, or apply coatings to lenses.Edging and coating lenses on the lab equipment.Done daily by most who do it. Robots: in a purpose-built cell, HSE Modulo (Schneider Optical Machines) (sold). Anthropic's rating. | 5% | 50 min17 min to 1.3 h | Hands-on 100% | Stays with people |
| Perform administrative duties, such as tracking inventory and sales, submitting patient insurance information, and performing simple bookkeeping.Inventory, sales, insurance claims and bookkeeping kept in the shop's systems.Done daily by most who do it. | 5% | 25 min13 min to 50 min | Systems 80%, documents 20% | 100%Half by now |
| Measure clients' bridge and eye size, temple length, vertex distance, pupillary distance, and optical centers of eyes, using measuring devices.Measuring the client's face and eyes with the instruments.Done hourly or more by most who do it. Robots: no robot shown. Anthropic's rating. | 5% | 13 min8 min to 21 min | Hands-on 80%, in person 20% | Stays with people |
| Heat, shape, or bend plastic or metal frames to adjust eyeglasses to fit clients, using pliers and hands.Bending the frames by hand and fitting them on the client.Done hourly or more by most who do it. Robots: no robot shown. Anthropic's rating. | 4% | 13 min4 min to 21 min | Hands-on 80%, in person 20% | 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 Opticians, Dispensing is within reach of AI now?
- An estimated 15% of the working time is within reach of AI models now and 15% 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 Opticians, Dispensing 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: Do shop administration (100% of the task's time now); Prepare lens work orders (100% of the task's time now); and Keep prescription and payment records (100% of the task's time now).
- Which tasks of Opticians, Dispensing stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Help clients choose frames; Recommend lenses and frames; and Fabricate lenses to prescription. Together such tasks are about 80% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Opticians, Dispensing 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; the conversations; and dealing with people outside the organization. By the end of 2028 on the long-run pace at four in five, about 85% of the working time stays with people, 15% 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 Opticians, Dispensing?
- 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 Opticians, Dispensing?
- 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 15% of the working time. Its index is 0.15 of 3. One example: MEI EZline / Stackers-Destackers feeding system for MEI lens edgers for "fabricate lenses to prescription". 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 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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