US dataswitch to UK
Optometrists
examining eyes, using observation, instruments and pharmaceutical agents, prescribing, supplying, fitting and adjusting eyeglasses, contacting lenses and other vision aids and educating and counseling patients on contact lens care. If that's your week, this page is about your job.
The honest answer
AI changes the edges of this job, not the middle: examining eyes, using observation, instruments and pharmaceutical agents is work software can't reach.
What shifts is consulting with and referring patients to ophthalmologist or other health care practitioner if additional medical treatment. This page scores what today's tools actually do, not headlines.
Your week, as this page understands it
Diagnose, manage, and treat conditions and diseases of the human eye and visual system. Examine eyes and visual system, diagnose problems or impairments, prescribe corrective lenses, and provide treatment. May prescribe therapeutic drugs to treat specific eye conditions. The job title says “optometrists”. The real job is the part underneath: examining eyes, using observation, instruments and pharmaceutical agents, to determine visual acuity and perception, focus and coordination and to diagnose diseases and other abnormalities. That is the thing someone has to be right about.
The exposed part of this job is specific, and we won’t pretend it is coming back. But optometrists is not one task. It is 10 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is examining eyes, using observation, instruments and pharmaceutical agents, to determine visual acuity and perception, focus and coordination and to diagnose diseases and other abnormalities, and the ledger below shows exactly why.
Where the work sits, by task weight
- shifting to AI
- 0%
- changing shape
- 20%
- staying human
- 80%
These bars are tasks changing hands, not people being counted out. The ledger below shows which.
Whole-job exposure score 18 out of 100 (14–23 allowing for uncertainty): minimal exposure, across 10 scored tasks. The number is the support for the sentence above it, not a headline about anyone’s future.
How we know this
What is measured: Every published task statement for optometrists is rated on five dimensions: can a model produce the output, does the work need a body in a room, does it need a legally accountable person, does it depend on a person being trusted in the moment, and how much data exists. A published formula turns those five ratings into the score; the model never writes the number.
How the bar is built: Each task’s share of the bar is its published importance weight, so a task you do all day counts for more than one you do twice a year.
Release: 2026-q4.1, scores computed 2026-08-05. Read the full method.
Your job, task by task
These are the official task statements for this occupation, in plain English, sorted by what the evidence says is happening to each one. The official wording sits under every line so you can check the rewrite against it.
- One task scored differently between repeat runs, so its range on this page is wider. We would rather show the wobble than hide it.
- 1 of this occupation's scored task statements carry a score that was measured under a different occupation's context, because the statement is shared between jobs and has only been scored once so far. Each one names the occupation it was measured under in the free routes below; none is presented as a measurement for this job.
- Task clusters are not derived in this release, so the task-cluster field is empty and no Collab365 Space routing is attached to this occupation yet.
Shifting to AI
0 tasksTasks today’s tools can already do most of. This is the part we will not soften: where these rows are the bulk of your week, the week changes.
Nothing in this job’s scored task list landed in this group. That is the measurement, not an editorial choice, and it is worth knowing either way.
Changing shape
2 tasksTasks where the machine takes the producing and a person keeps the checking, the deciding, or the answering-for-it. For most jobs this is the biggest group, and it is where "transformation, not termination" is literally visible.
Analyzing test results and developing a treatment plan
The software now makes the first pass at test results, but someone has to be answerable for the result, and it cannot be the software. So the job becomes checking and deciding rather than producing.
importance 5 · CoreSource: “Analyze test results and develop a treatment plan.” (O*NET task statement)
How this row was scored
Exposure score: 40 out of 100 (33–47 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; someone qualified has to answer for it.
The rating behind it: AI reads test results well, but the law puts diagnosis and the treatment plan in a licensed optometrist’s hands.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 3/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Consulting with and referring patients to ophthalmologist or other health care practitioner if additional medical treatment
The software now makes the first pass at and referring patients, but someone has to be answerable for the result, and it cannot be the software. So the job becomes checking and deciding rather than producing.
importance 5 · CoreSource: “Consult with and refer patients to ophthalmologist or other health care practitioner if additional medical treatment is determined necessary.” (O*NET task statement)
How this row was scored
Exposure score: 48 out of 100 (41–55 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; someone qualified has to answer for it.
The rating behind it: Deciding a case needs specialist care follows documented criteria, though a qualified clinician makes the call.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 2/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Staying human
8 tasksTasks that stay with a person, because they happen in the physical world, because the rules need someone accountable, or because the value is that a specific person does them.
Examining eyes, using observation, instruments and pharmaceutical agents
This work happens in the physical world: eyes, in a real place. Software cannot follow it there.
importance 5 · CoreSource: “Examine eyes, using observation, instruments, and pharmaceutical agents, to determine visual acuity and perception, focus, and coordination and to diagnose diseases and other abnormalities, such as glaucoma or color blindness.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: the same decision, made over and over; work that happens in the physical world; someone qualified has to answer for it.
The rating behind it: Eye examination uses instruments held against the patient, so a qualified person has to be there.
The five ratings: output a model can produce 1/4 · needs a body in a room 4/4 · needs an accountable person 3/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Prescribing medications to treat eye diseases if state laws permit
The rules require a named, qualified person to answer for medications, and that person cannot be a piece of software.
importance 5 · CoreSource: “Prescribe medications to treat eye diseases if state laws permit.” (O*NET task statement)
How this row was scored
Exposure score: 18 out of 100 (14–22 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: the same decision, made over and over; someone qualified has to answer for it.
The rating behind it: Only a licensed practitioner may write the prescription, whatever software suggests.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 4/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Prescribing, supplying, fitting and adjusting eyeglasses, contacting lenses and other vision aids
This work happens in the physical world: eyeglasses, contacting lenses and other vision aids, in a real place. Software cannot follow it there.
importance 5 · CoreSource: “Prescribe, supply, fit and adjust eyeglasses, contact lenses, and other vision aids.” (O*NET task statement)
How this row was scored
Exposure score: 4 out of 100 (0–8 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world; someone qualified has to answer for it.
The rating behind it: Fitting and adjusting lenses and frames is hands-on work with the patient present.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 3/4 · needs to be trusted in the moment 1/4 · how much data exists 2/4.
Educating and counseling patients on contact lens care
The value here is that a specific person handles patients and stands behind it. That is earned, not computed.
importance 5 · CoreSource: “Educate and counsel patients on contact lens care, visual hygiene, lighting arrangements, and safety factors.” (O*NET task statement)
How this row was scored
Exposure score: 38 out of 100 (31–45 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; the value is that a specific person does it.
The rating behind it: Lens care and eye safety advice is standard information that written or video guidance already covers well.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 1/4 · needs to be trusted in the moment 2/4 · how much data exists 4/4.
Providing patients undergoing eye surgeries
This work happens in the physical world: patients undergoing eye surgeries, in a real place. Software cannot follow it there.
importance 5 · CoreSource: “Provide patients undergoing eye surgeries, such as cataract and laser vision correction, with pre- and post-operative care.” (O*NET task statement)
How this row was scored
Exposure score: 4 out of 100 (0–8 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world; someone qualified has to answer for it; the value is that a specific person does it.
The rating behind it: Surgical aftercare means examining the eye in person and reassuring an anxious patient.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 3/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.
Removing foreign bodies from the eye
This work happens in the physical world: foreign bodies, in a real place. Software cannot follow it there.
importance 5 · CoreSource: “Remove foreign bodies from the eye.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–7 allowing for uncertainty): minimal exposure, high confidence, and it moved between repeat runs, so the range is widened.
Why it sits in this group: work that happens in the physical world; someone qualified has to answer for it.
The rating behind it: Removing something from somebody’s eye is a delicate hands-on procedure.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 3/4 · needs to be trusted in the moment 1/4 · how much data exists 2/4.
Prescribing therapeutic procedures to correct or conserve vision
The rules require a named, qualified person to answer for therapeutic procedures, and that person cannot be a piece of software.
importance 4 · CoreSource: “Prescribe therapeutic procedures to correct or conserve vision.” (O*NET task statement)
How this row was scored
Exposure score: 23 out of 100 (16–30 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; someone qualified has to answer for it.
The rating behind it: Prescribing vision therapy is a licensed decision, even though the options are well documented.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 3/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Providing vision therapy and low-vision rehabilitation
This work happens in the physical world: vision therapy, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Provide vision therapy and low-vision rehabilitation.” (O*NET task statement)
How this row was scored
Exposure score: 3 out of 100 (0–7 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world; someone qualified has to answer for it; the value is that a specific person does it.
The rating behind it: Vision therapy is delivered in person session by session, and progress depends on the relationship.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 2/4 · needs to be trusted in the moment 3/4 · how much data exists 2/4.
What this job pays, and how many people do it
- Median pay
- $136,570a year, the middle of the range, so half earn more and half earn less.bls-oews, 2025 · May 2025 estimates (national_M2025_dl.xlsx)
How we know this
Source: bls-oews
Reference period: May 2025 estimates (national_M2025_dl.xlsx)
Rounding: Shown as published.
- People doing this job
- 42,790in the US, 2025.bls-oews · May 2025 estimates (national_M2025_dl.xlsx)
What is deliberately not here: a forecast of how many of these jobs exist in ten years. Where an official projection exists for a market we publish it with its vintage; where it does not, we leave the space empty rather than borrow the other country’s number.
Why this is shifting
The reason is boringly specific. Most of what is shifting here is reading one thing and writing another: and referring patients in, a record out. The rows above are exactly that shape: consulting with and referring patients to ophthalmologist or other health care practitioner if additional medical treatment and analyzing test results and developing a treatment plan. What it cannot do is be answerable: eyes need a named person the rules will accept, and software cannot be that person. Which is why this page talks about your tasks changing, not your job ending.
Your move
Over a pint: what I’d tell you if you were my friend
Start with what does not change: examining eyes, using observation, instruments and pharmaceutical agents is the middle of this job, and the evidence on this page says it stays with a person.
So, given all that: 0% of this job's task weight sits in rows the software is already learning, 20% in rows that change shape rather than disappear, and 80% in rows it is nowhere near. That is the position, measured across 10 scored tasks. It is not a forecast about you.
So the thing worth your attention is not the job going away. It is the layer around it. Consulting with and referring patients to ophthalmologist or other health care practitioner if additional medical treatment is the part turning into software, and being the person who understands that layer is worth money.
This week: one thing
Ask the one question. Find whoever is bringing new software into your workplace (the manager, the office, whoever runs the system) and ask them what it is meant to do to and referring patients, and what it is not meant to touch. Ten minutes, this week, before anyone decides it for you.
- What you end up holding
- a straight answer about what is actually being rolled out, and when
- How long it takes
- ten minutes
If there’s nobody obvious to ask, or you’d rather not ask your manager: Put the same question to your union rep, your shift lead or the person who has been there longest, in person, over a break. Same ten minutes, same answer, and you will usually get a straighter one. Write down what they say. The note is the artifact, and it tells you whether eyes are in scope or not. Nothing to log into, no license needed.
Over the next 90 days
Get inside the tool rollout rather than waiting for it. Over the next ninety days, ask to be in the group that tests, checks or signs off whatever new system arrives near analyzing test results and developing a treatment plan. It is usually an unglamorous seat that nobody fights for, and it is the one that decides how the software is used on your job rather than to it.
Over the next 12 months
On this evidence I would not retrain out of this job, and I will say that plainly rather than hedge it. The task list here is dominated by work that stays with a person. What I would do with a year is get formally recognised for the layer around it (the systems, the compliance, the planning), so you are the one who understands the software instead of the one it is done to. Before you pay for anything, use CareerOneStop - Find local training. It is free, it is the Labor Department's own service, and it is listed below with the rest of the free routes.
The roads out of here, and why I am not sending you down them
I looked at the obvious moves out of this job, and here is what I found.
I checked the 12 nearest US occupations to optometrists (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was obstetricians and gynecologists: only about 9% of its durable work is work you already do and the 2.1× pay gap is the market pricing a barrier. And on the numbers you do not need one. This job scores 18/100 here, with only 0% of the task list in the top band, and “examine eyes, using observation, instruments, and pharmaceutical agents, to determine visual acuity…” is not work that hands over cleanly. None of them beats deepening what you already have.
How that was checked: this job was compared against all 830 US occupations in this release on their official task statements, and the 12 nearest were examined one by one. A move that turns on an industry, an employer or a qualification rather than on the work itself will not show up in a check like that. And this release carries no licence register, so anything you are weighing needs that looked up separately.
3 moves I checked and rejected
These are the obvious-looking jumps. They are here with their reasons rather than quietly dropped, because the ones that fail are worth knowing about. It is one less thing to turn over at night.
Obstetricians and Gynecologists
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already analyze test results and develop a treatment plan, and their equivalent is to explain procedures and discuss test results or prescribed treatments with patients. Across both published task lists that is about 9% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 9% of the durable side of that job. That is a different job, not a next step. The pay gap is the market pricing a barrier: $292,910 against your $136,570 is 2.15× (OEWS May 2025 (both)), and you would be crossing it holding about 9% of their durable work. A gap that size with an overlap that small is a wish, not a route.
Family Medicine Physicians
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already analyze test results and develop a treatment plan, and their equivalent is to explain procedures and discuss test results or prescribed treatments with patients. Across both published task lists that is about 8% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 8% of the durable side of that job. That is a different job, not a next step.
General Internal Medicine Physicians
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already analyze test results and develop a treatment plan, and their equivalent is to explain procedures and discuss test results or prescribed treatments with patients. Across both published task lists that is about 7% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 7% of the durable side of that job. That is a different job, not a next step.
What I’d stop worrying about
A friend tells you what not to spend fear on. This is that list.
The headline number you read somewhere
The big “X% of jobs” figures are about the whole economy, not about you. The number that describes your job is on this page: 0% of its task weight, across 10 scored tasks. Every row behind it is printed above with the source. Check ours; ignore theirs.
The headlines about your trade disappearing
They are usually about the technology, not the timetable. Changes to work like examining eyes, using observation, instruments and pharmaceutical agents arrive through rules, insurance and money, slowly and visibly. This page tracks the task evidence and will move when it moves.
Retraining out of a job that is holding up
On this evidence I would not spend money leaving. Spend it on the layer around the job instead: the tools, the paperwork, the planning. That is where the change actually is.
The “obvious” next job everyone suggests
I checked the obvious moves and most of them did not survive. The reasons are printed with the routes above, including the pay and the gate. A move that fails on the numbers is worth knowing about so you can stop turning it over at night.
You are reading the United States figures
The United Kingdom splits this work across more than one official group, of which Optometrists is the closest. The pay and employment figures are not directly comparable, and we do not average them together.
Switch to the United Kingdom page →partial match
The other groups this work is counted across:
In UK official statistics this job is counted as Optometrists and Dispensing opticians. Pay is shown separately for each of those groups (medians cannot be averaged together), while the task list and the scores on this page are for this group only.
Your route through this
Where to go next, and what it costs
Free, and complete
The moves above cost nothing. These are the real services that go with them: public, government-funded, and free at the point of use. Nothing on this page is behind an email address or a payment.
Anywhere in the US:
CareerOneStop - Find local training
Search what's running near you, from the Labor Department's own database, before anyone sells you a course.
Free to search; individual programs vary, and some are funded
Anywhere in the US:
An American Job Center will sit down with you for free. Find yours by ZIP code.
Free
Anywhere in the US:
CareerOneStop - Licensed occupations finder
Check what your state actually requires before you pay for anything.
Free
Anywhere in the US:
Free
Why there is no community here
Collab365, who build this site, run paid Spaces for a small number of subjects, and none of them is built for this job. We are not going to point you at the nearest one and call it a fit.
So the free services listed on this page are the whole answer, and it is the same answer we would give a friend.
Noted, and thank you. We’ll email you if a Space for optometrists launches. Nothing else.
That did not look like an email address, so nothing was saved. Have another go below.
We could not save that. The fault is ours, not yours, and your address was not stored. Please try again later.
No deadline on any of this. The page will still be here, and the data is refreshed on a published schedule rather than when someone wants a headline.
Questions people ask about this job
- Will AI replace Optometrists?
- Not as a job, but it is already doing parts of the work. Across the 10 official task statements scored for Optometrists (United States, SOC 29-1041), 0% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 18 out of 100 (range 14–23, band: minimal). That is a statement about tasks, not about headcount: this measures what AI could do, not whether any employer adopts it, whether the law allows it, or whether doing the routine parts faster creates more demand for the human parts. Figures are from release 2026-q4.1.
- Which tasks in “Optometrists” can AI already do?
- The highest-scoring tasks in release 2026-q4.1 are: “Consult with and refer patients to ophthalmologist or other health care practitioner if additional medical treatment is determined necessary” (48/100, partial); “Analyze test results and develop a treatment plan” (40/100, partial); “Educate and counsel patients on contact lens care, visual hygiene, lighting arrangements, and safety factors” (38/100, low). Each score comes from five published 0–4 ratings turned into a number by a published formula, and each carries the model's one-sentence reason on the page.
- Which tasks in “Optometrists” stay human?
- About 80% of this job's task weight sits in work that scores low for AI exposure. The lowest-scoring tasks in release 2026-q4.1 are: “Remove foreign bodies from the eye” (0/100, minimal); “Examine eyes, using observation, instruments, and pharmaceutical agents, to determine visual acuity and perception, focus, and coordination and to diagnose d…” (0/100, minimal); “Provide vision therapy and low-vision rehabilitation” (3/100, minimal). Low scores usually mean the task needs a body in a room, a legally accountable human, or trust built in real time. Those are the three things the scoring rubric treats as gates rather than obstacles.
- What should someone working in “Optometrists” do about AI?
- Start from the ledger rather than the headline: 0% of this job's weighted core work is exposed, and roughly 80% is not. The practical move is to spend more of your week on the tasks that score low, the ones above, and to get fluent at directing AI through the tasks that score high, because those are the parts that change whether or not you are ready for them. This page does not predict your job, and nothing here is career advice tailored to you: the score describes the occupation, not the person.
- How is the AI exposure score for Optometrists calculated?
- Each official task statement for the occupation is rated on five published 0–4 dimensions (output replicability, physical embodiment, licensed accountability, real-time human trust, and data availability) by claude-opus-5 using scoring prompt task_scoring_v1.0. The model never writes the score; a published formula turns the five ratings into a 0–100 number, so every score can be recomputed by hand. The occupation figure is the importance-weighted mean across 10 scored tasks. The prompt, the rubric, the formula and the full dataset are published at https://futureproof.collab365.com/method and https://futureproof.collab365.com/data/2026-q4.1 under CC BY 4.0.
Where these numbers come from
About the data on this page
- One task scored differently between repeat runs, so its range on this page is wider. We would rather show the wobble than hide it.
- The match between this job and its counterpart in the other country is partial, so the two pages count slightly different groups of people.
- 1 of this occupation's scored task statements carry a score that was measured under a different occupation's context, because the statement is shared between jobs and has only been scored once so far. Each one names the occupation it was measured under in the free routes below; none is presented as a measurement for this job.
- Task clusters are not derived in this release, so the task-cluster field is empty and no Collab365 Space routing is attached to this occupation yet.
- Task statements
- onet-dbProcessing: catalogue-bridge → onet-im-rt-weighting → task-scoring → score-aggregation
- Task weights
- onet-db (im-rt)
- Scores
- Rubric task_scoring_v1.0, model claude-opus-5, computed 2026-08-05.
- Pay and employment
- bls-oews (May 2025 estimates (national_M2025_dl.xlsx))bls-oews (May 2025 estimates (national_M2025_dl.xlsx))
Figures on this page come from release 2026-q4.1, published 2026-08-05. Every release keeps its own permanent address, so a figure you cite in March is still there, unchanged, in November.
The plain-English wording on this page is assembled directly from the task statements and the published ratings, not written by hand for this occupation. That is why it is specific, and it is also why we say so.
The routes and free resources further up are today’s, not the release’s (last reviewed 2026-08-05). A route is an offer, not a historical fact, so it moves on its own clock.
Using these figures?
Cite this
Everything on this site is published under CC BY 4.0. Quote it, chart it, sell something built on it. Just say where it came from, and cite the dated release rather than the site, so the figure you quote stays checkable.
Plain text
Collab365 (2026). Collab365 Futureproof: task-level AI exposure for US and UK occupations, release 2026-q4.1 (methodVersion 2.0.0, promptVersion task_scoring_v1.0). https://futureproof.collab365.com/data/2026-q4.1. Licensed CC BY 4.0. Built with O*NET data (USDOL/ETA, CC BY 4.0); ONS data (Open Government Licence v3.0); GAISI task framework (arXiv:2507.22748, MIT); BLS data (public domain).
BibTeX
@misc{collab365futureproof2026q41,
title = {Collab365 Futureproof: task-level AI exposure for US and UK occupations, release 2026-q4.1},
author = {{Collab365}},
year = {2026},
url = {https://futureproof.collab365.com/data/2026-q4.1},
note = {Release 2026-q4.1, methodVersion 2.0.0, promptVersion task_scoring_v1.0, CC BY 4.0}
}Data as of release 2026-q4.1, published . Releases never change after publication; when the figures move, a new dated release is published beside this one and this one stays exactly where it is.