Will AI replace Medical Assistants?

Not as a job, but it is already doing parts of the work. Across the 20 official task statements scored for Medical Assistants (United States, SOC 31-9092), 16% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 24 out of 100 (range 21–29, band: low). 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 “Medical Assistants” can AI already do?

The highest-scoring tasks in release 2026-q4.1 are: “Record patients' medical history, vital statistics, or information such as test results in medical records” (81/100, very high); “Schedule appointments for patients” (79/100, high); “Contact medical facilities or departments to schedule patients for tests or admission” (64/100, high). 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 “Medical Assistants” stay human?

About 70% 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: “Operate x-ray, electrocardiogram (EKG), or other equipment to administer routine diagnostic tests” (0/100, minimal); “Set up medical laboratory equipment” (0/100, minimal); “Change dressings on wounds” (0/100, 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 “Medical Assistants” do about AI?

Start from the ledger rather than the headline: 16% of this job's weighted core work is exposed, and roughly 70% 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 Medical Assistants 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 20 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.

US dataswitch to UK

Medical Assistants

interviewing patients to obtain medical information and measure their vital signs, authorizing drug refills and providing prescription information to pharmacies and changing dressings on wounds. If that's your week, this page is about your job.

The honest answer

AI is already taking a real slice of the routine work here: recording patients' medical history, vital statistics or information, test results in medical records. That is a slice of tasks, not of you.

Your move: what you can actually do about this ↓

Where the work sits, by task weight

shifting to AI: 16%
changing shape: 13%
staying human: 70%

These bars are tasks changing hands, not people being counted out. The ledger below shows which.

Whole-job exposure score 24 out of 100 (21–29 allowing for uncertainty): low exposure, across 20 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 medical assistants 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 2026-08-04. Read the full method.

That slice is not coming back; the core of the job, cleaning and sterilizing instruments and dispose of contaminated supplies, stays yours. New tools, same person answering for it.

Your week, as this page understands it

Perform administrative and certain clinical duties under the direction of a physician. Administrative duties may include scheduling appointments, maintaining medical records, billing, and coding information for insurance purposes. Clinical duties may include taking and recording vital signs and medical histories, preparing patients for examination, drawing blood, and administering medications as directed by physician. The job title says “medical assistants”. The real job is the part underneath: cleaning and sterilizing instruments and dispose of contaminated supplies. 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 medical assistants is not one task. It is 20 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is cleaning and sterilizing instruments and dispose of contaminated supplies, and the ledger below shows exactly why.

Where the work sits, by task weight

shifting to AI: 16%
changing shape: 13%
staying human: 70%

These bars are tasks changing hands, not people being counted out. The ledger below shows which.

How we know this

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 2026-08-04. 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.

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

3 tasks

Tasks 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.

Recording patients' medical history, vital statistics or information, test results in medical records
This is reading one thing and writing another: patients' medical history, vital statistics or information in, a record out. That is the shape today's tools are built for.
importance 5 · Core
Source: “Record patients' medical history, vital statistics, or information such as test results in medical records.” (O*NET task statement)
How this row was scored
Exposure score: 81 out of 100 (77–85 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Typing history, vitals and results into the record is documentation, and speech-to-note tools already do most of it.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Scheduling appointments for patients
This is reading one thing and writing another: appointments in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Schedule appointments for patients.” (O*NET task statement)
How this row was scored
Exposure score: 79 out of 100 (75–83 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Booking appointments is routine scheduling that software already does end to end.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Contacting medical facilities or departments to schedule patients for tests or admission
This is reading one thing and writing another: medical facilities in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Contact medical facilities or departments to schedule patients for tests or admission.” (O*NET task statement)
How this row was scored
Exposure score: 64 out of 100 (60–68 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Arranging tests and admissions with other departments is booking and messaging work.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.

Changing shape

3 tasks

Tasks 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.

Performing general office duties, such as answering telephones, taking dictation or completing insurance forms
The software now makes the first pass at general office duties, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 5 · Core
Source: “Perform general office duties, such as answering telephones, taking dictation, or completing insurance forms.” (O*NET task statement)
How this row was scored
Exposure score: 56 out of 100 (52–60 allowing for uncertainty): partial exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Phones, dictation and insurance forms are standard office work that software handles well.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Authorizing drug refills and providing prescription information to pharmacies
The software now makes the first pass at drug refills, 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 4 · Core
Source: “Authorize drug refills and provide prescription information to pharmacies.” (O*NET task statement)
How this row was scored
Exposure score: 47 out of 100 (40–54 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: Refill requests and pharmacy messages are handled in the record system, but a prescriber must authorise them.
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 0/4 · how much data exists 3/4.
Keeping financial records or performing other bookkeeping duties
The software now makes the first pass at financial records, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · Supplemental
Source: “Keep financial records or perform other bookkeeping duties, such as handling credit or collections or mailing monthly statements to patients.” (O*NET task statement)
How this row was scored
Exposure score: 59 out of 100 (52–66 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; mistakes that are cheap to catch.
The rating behind it: Billing, statements and collections are routine bookkeeping that accounting software largely automates.
The five ratings: output a model can produce 4/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.

Staying human

14 tasks

Tasks 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.

Interviewing patients to obtain medical information and measure their vital signs
This work happens in the physical world: patients, in a real place. Software cannot follow it there.
importance 5 · Core
Source: “Interview patients to obtain medical information and measure their vital signs, weight, and height.” (O*NET task statement)
How this row was scored
Exposure score: 6 out of 100 (0–13 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; work that happens in the physical world; the value is that a specific person does it.
The rating behind it: A history could be taken on a form, but weight, height and vital signs need hands on the patient.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 1/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
Cleaning and sterilizing instruments and dispose of contaminated supplies
This work happens in the physical world: instruments, in a real place. Software cannot follow it there.
importance 5 · Core
Source: “Clean and sterilize instruments and dispose of contaminated supplies.” (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.
The rating behind it: Cleaning and sterilising instruments and disposing of waste is physical work in the clinic.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Preparing treatment rooms for patient examinations
This work happens in the physical world: treatment rooms, in a real place. Software cannot follow it there.
importance 5 · Core
Source: “Prepare treatment rooms for patient examinations, keeping the rooms neat and clean.” (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.
The rating behind it: Getting a treatment room ready and clean is hands-on work in the room.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Showing patients to examination rooms and preparing them for the physician
This work happens in the physical world: patients, in a real place. Software cannot follow it there.
importance 5 · Core
Source: “Show patients to examination rooms and prepare them for the physician.” (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: work that happens in the physical world.
The rating behind it: Walking a patient to a room and getting them ready happens in person.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 2/4.

Show the other 10 tasks

Inventorying and ordering medical, lab or office supplies or equipment
staying human
This work happens in the physical world: medical, lab or office supplies or equipment, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Inventory and order medical, lab, or office supplies or equipment.” (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: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Reordering is automatic once stock is tracked, but counting what is on the shelf needs someone there.
The five ratings: output a model can produce 3/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Explaining treatment procedures, medications, diets or physicians' instructions to patients
staying human
The value here is that a specific person handles treatment procedures, medications, diets or physicians' instructions and stands behind it. That is earned, not computed.
importance 5 · Core
Source: “Explain treatment procedures, medications, diets, or physicians' instructions to patients.” (O*NET task statement)
How this row was scored
Exposure score: 34 out of 100 (27–41 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: Clear instructions are easy to produce, but patients ask questions and want a person to check they understood.
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 3/4.
Greeting and logging in patients arriving at office or clinic
staying human
This work happens in the physical world: patients, in a real place. Software cannot follow it there.
importance 5 · Core
Source: “Greet and log in patients arriving at office or clinic.” (O*NET task statement)
How this row was scored
Exposure score: 12 out of 100 (5–19 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Check-in screens already handle the paperwork, but greeting patients as they arrive happens at the desk.
The five ratings: output a model can produce 2/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Performing routine laboratory tests and sampling analyses
staying human
This work happens in the physical world: routine laboratory tests, in a real place. Software cannot follow it there.
importance 5 · Core
Source: “Perform routine laboratory tests and sample analyses.” (O*NET task statement)
How this row was scored
Exposure score: 9 out of 100 (2–16 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; work that happens in the physical world.
The rating behind it: Routine lab tests mean physically handling samples and analysers, even where results print automatically.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Preparing and administering medications as directed by a physician
staying human
This work happens in the physical world: medications, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Prepare and administer medications as directed by a physician.” (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: Preparing and giving medicines is hands-on and legally restricted to trained, supervised staff.
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 3/4.
Collecting blood, tissue or other laboratory specimens, log the specimens and preparing them for testing
staying human
This work happens in the physical world: blood, tissue or other laboratory specimens, in a real place. Software cannot follow it there.
importance 5 · Core
Source: “Collect blood, tissue, or other laboratory specimens, log the specimens, and prepare them for testing.” (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.
The rating behind it: Drawing blood and taking samples means physically handling a patient and the specimens.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 1/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Helping physicians examine and treating patients
staying human
This work happens in the physical world: physicians examine, in a real place. Software cannot follow it there.
importance 5 · Core
Source: “Help physicians examine and treat patients, handing them instruments or materials or performing such tasks as giving injections or removing sutures.” (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: work that happens in the physical world; someone qualified has to answer for it.
The rating behind it: Assisting during examinations, giving injections and removing sutures is direct hands-on care.
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.
Changing dressings on wounds
staying human
This work happens in the physical world: dressings, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Change dressings on wounds.” (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.
The rating behind it: Changing a wound dressing is direct physical care.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 1/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Setting up medical laboratory equipment
staying human
This work happens in the physical world: medical laboratory equipment, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Set up medical laboratory equipment.” (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.
The rating behind it: Setting up laboratory equipment is physical work at the bench.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Operating x-ray, electrocardiogram, EKG) or other equipment to administer routine diagnostic tests
staying human
This work happens in the physical world: x-ray, electrocardiogram, ekg) or other equipment, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Operate x-ray, electrocardiogram (EKG), or other equipment to administer routine diagnostic tests.” (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: Running an x-ray or EKG means positioning the patient and the equipment.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 2/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.

What this job pays, and how many people do it

Median pay: $45,690a 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: 817,870in 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: patients' medical history, vital statistics or information in, a record out. The rows above are exactly that shape: recording patients' medical history, vital statistics or information and scheduling appointments for patients. What it cannot do is be there in the room, and that is still where instruments get done. 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: cleaning and sterilizing instruments and dispose of contaminated supplies is the middle of this job, and the evidence on this page says it stays with a person.

So, given all that: 16% of this job's task weight sits in rows the software is already learning, 13% in rows that change shape rather than disappear, and 70% in rows it is nowhere near. That is the position, measured across 20 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. Recording patients' medical history, vital statistics or information, test results in medical records 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 patients' medical history, vital statistics or information, 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 instruments 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 performing general office duties, such as answering telephones, taking dictation or completing insurance forms. 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 medical assistants (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was licensed practical and licensed vocational nurses: only about 11% of its durable work is work you already do. And on the numbers you do not need one. This job scores 24/100 here, with only 16% of the task list in the top band, and “interview patients to obtain medical information and measure their vital signs, weight…” 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.

Licensed Practical and Licensed Vocational Nurses
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already interview patients to obtain medical information and measure their vital signs, weight, and…, and their equivalent is to measure and record patients' vital signs. Across both published task lists that is about 11% of the durable work in that job.
Why I am not recommending it: You would be starting most of it from nothing: about 11% of the durable work in that job is work you do today, and the rest you would be learning while the bills carried on.
Look at that job’s page anyway →
Cardiologists
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already record patients' medical history, vital statistics, or information, and their equivalent is to diagnose medical conditions of patients, using records, reports, test results, or examination information. 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. The pay gap is the market pricing a barrier: $496,010 against your $45,690 is 10.86× (OEWS May 2025 (both)), and you would be crossing it holding about 8% of their durable work. A gap that size with an overlap that small is a wish, not a route. And it is a narrow door: about 17,290 of those jobs against 817,870 of yours (OEWS May 2025), 2% as many seats.
Look at that job’s page anyway →
Physician Assistants
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already operate x-ray, electrocardiogram (EKG), or other equipment to administer routine diagnostic tests, and their equivalent is to administer or order diagnostic tests. 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. The pay gap is the market pricing a barrier: $135,880 against your $45,690 is 2.97× (OEWS May 2025 (both)), and you would be crossing it holding about 8% of their durable work. A gap that size with an overlap that small is a wish, not a route. And it is a narrow door: about 162,150 of those jobs against 817,870 of yours (OEWS May 2025), 20% as many seats.
Look at that job’s page anyway →

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: 16% of its task weight, across 20 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 cleaning and sterilizing instruments and dispose of contaminated supplies 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 Pharmacy and optical dispensing assistants 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

In UK official statistics this job is counted as Pharmacy and optical dispensing assistants. Pay and employment stay on this page’s own group; the task list and the scores do not cross over.

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No Space for this job, but one for what is happening to it

Nothing Collab365 runs is built for medical assistants, and we are not going to point you at the nearest one and call it a fit.

There is one that is not about a job title at all. The AI Authority is about being the person who directs these tools at work rather than the person they get compared to. That is worth saying here, because 16% of the work on this page is already inside what they can do.

Try The AI Authority free →

7 days free, no card needed. Explore up to 2 Spaces before you choose a plan: you pick a plan later, not now.

The AI Authority is a general community about working with AI, not a course for medical assistants. You do not need it to act on anything here: the moves above cost nothing and stand on their own. The data on this page is the same either way.

Noted, and thank you. We’ll email you if a Space for medical assistants launches. Nothing else.

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No Space for medical assistants yet. Should there be one?

Collab365 Spaces is built by the same people as this site. We find the problems that AI and automation are creating inside one kind of work, then solve them as short courses, briefings and Blueprints. Each Space is the community too, so the research and the people doing your job are in the same place.

What a Space actually is, in full

Collab365 launches new communities where the need is real. If one for medical assistants existed, with researched problems, courses and people in the same boat, would you want in?

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This unlocks nothing. Every figure, every row and every step on this page is already yours, whether you fill this in or not.

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 Medical Assistants?: Not as a job, but it is already doing parts of the work. Across the 20 official task statements scored for Medical Assistants (United States, SOC 31-9092), 16% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 24 out of 100 (range 21–29, band: low). 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 “Medical Assistants” can AI already do?: The highest-scoring tasks in release 2026-q4.1 are: “Record patients' medical history, vital statistics, or information such as test results in medical records” (81/100, very high); “Schedule appointments for patients” (79/100, high); “Contact medical facilities or departments to schedule patients for tests or admission” (64/100, high). 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 “Medical Assistants” stay human?: About 70% 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: “Operate x-ray, electrocardiogram (EKG), or other equipment to administer routine diagnostic tests” (0/100, minimal); “Set up medical laboratory equipment” (0/100, minimal); “Change dressings on wounds” (0/100, 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 “Medical Assistants” do about AI?: Start from the ledger rather than the headline: 16% of this job's weighted core work is exposed, and roughly 70% 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 Medical Assistants 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 20 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

Worth knowing about these figures

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 2026-08-04.
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.

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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}
}

Permalink

https://futureproof.collab365.com/data/2026-q4.1

Data as of release 2026-q4.1, published 2026-08-05. 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.