US dataswitch to UK
Museum Technicians and Conservators
installing, arranging, assembling and preparing artifacts, preparing reports on the operation of conservation laboratories and entering information about museum collections into computer databases. If that's your week, this page is about your job.
The honest answer
AI changes the edges of this job, not the middle: photographing objects for documentation is work software can't reach.
What shifts is entering information about museum collections into computer databases. This page scores what today's tools actually do, not headlines.
Your week, as this page understands it
Restore, maintain, or prepare objects in museum collections for storage, research, or exhibit. May work with specimens such as fossils, skeletal parts, or botanicals; or artifacts, textiles, or art. May identify and record objects or install and arrange them in exhibits. Includes book or document conservators. The job title says “museum technicians” or “conservators”: officially one job, two names. The real job is the part underneath: photographing objects for documentation. 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 museum technicians and conservators is not one task. It is 24 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is photographing objects for documentation, and the ledger below shows exactly why.
Where the work sits, by task weight
- shifting to AI
- 0%
- changing shape
- 23%
- staying human
- 77%
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 24 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 museum technicians and conservators 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.
- 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
6 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.
Entering information about museum collections into computer databases
The software now makes the first pass at information, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Enter information about museum collections into computer databases.” (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: Typing collection details into a database is standard record work that software already handles well.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Recommending preservation procedures, such as control of temperature and humidity, to curatorial and building staff
The software now makes the first pass at preservation procedures, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Recommend preservation procedures, such as control of temperature and humidity, to curatorial and building staff.” (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; mistakes that are cheap to catch.
The rating behind it: Temperature and humidity guidance is well published, so a solid recommendation can be drafted from the building's readings.
The five ratings: output a model can produce 3/4 · 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.
Notifying superior when restoration of artifacts requires outside experts
The software now makes the first pass at superior, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Notify superior when restoration of artifacts requires outside experts.” (O*NET task statement)
How this row was scored
Exposure score: 43 out of 100 (36–50 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; mistakes that are cheap to catch.
The rating behind it: Flagging that a job needs an outside specialist is a short judgment call that follows familiar patterns.
The five ratings: output a model can produce 3/4 · 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 2/4.
Classifying and assigning registration numbers to artifacts and supervising inventory control
The software now makes the first pass at registration numbers, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · SupplementalSource: “Classify and assign registration numbers to artifacts and supervise inventory control.” (O*NET task statement)
How this row was scored
Exposure score: 56 out of 100 (49–63 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: Assigning registration numbers and tracking inventory is systematic record work computers do reliably.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Preparing reports on the operation of conservation laboratories
The software now makes the first pass at reports, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · SupplementalSource: “Prepare reports on the operation of conservation laboratories, documenting the condition of artifacts, treatment options, and the methods of preservation and repair used.” (O*NET task statement)
How this row was scored
Exposure score: 56 out of 100 (49–63 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: Writing up lab activity and treatment options is standard report writing from records already kept.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Staying human
18 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.
Determining whether objects need repair and choosing the safest and most effective method of repair
This work happens in the physical world: whether objects need repair, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Determine whether objects need repair and choose the safest and most effective method of repair.” (O*NET task statement)
How this row was scored
Exposure score: 25 out of 100 (18–32 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Software can suggest repair methods from images and records, but judging a fragile object usually means examining it closely.
The five ratings: output a model can produce 2/4 · 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 2/4.
Photographing objects for documentation
This work happens in the physical world: objects, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Photograph objects for documentation.” (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: Photographing an object means setting it up and operating a camera in the room with it.
The five ratings: output a model can produce 1/4 · 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 2/4.
Installing, arranging, assembling and preparing artifacts for exhibition, ensuring the artifacts' safety
This work happens in the physical world: artifacts, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Install, arrange, assemble, and prepare artifacts for exhibition, ensuring the artifacts' safety, reporting their status and condition, and identifying and correcting any problems with the set up.” (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: Mounting and arranging real artifacts in a gallery is careful hands-on work.
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 2/4.
Cleaning objects, such as paper, textiles, wood, metal, glass, rock, pottery and furniture, using cleansers, solvents, soap solutions and polishes
This work happens in the physical world: objects, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Clean objects, such as paper, textiles, wood, metal, glass, rock, pottery, and furniture, using cleansers, solvents, soap solutions, and polishes.” (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: Cleaning delicate objects with solvents and polishes is done by hand on the object.
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 1/4.
Preparing artifacts for storage and shipping
This work happens in the physical world: artifacts, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Prepare artifacts for storage and shipping.” (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: Wrapping and packing artifacts for storage or shipping is careful physical handling.
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 2/4.
Show the other 14 tasks
Estimating cost of restoration work
changing shapeThe software now makes the first pass at cost of restoration work, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 3 · SupplementalSource: “Estimate cost of restoration work.” (O*NET task statement)
How this row was scored
Exposure score: 51 out of 100 (44–58 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; mistakes that are cheap to catch.
The rating behind it: Costing restoration is calculation from rates and hours, though the hours come from seeing the object.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Performing tests and examinations to establish storage and conservation requirements
staying humanThis work happens in the physical world: tests, in a real place. Software cannot follow it there.
importance 4 · SupplementalSource: “Perform tests and examinations to establish storage and conservation requirements, policies, and procedures.” (O*NET task statement)
How this row was scored
Exposure score: 29 out of 100 (22–36 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: Setting storage policy is writing, but the tests behind it are carried out on real objects.
The five ratings: output a model can produce 2/4 · 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.
Studying object documentation or conducting standard chemical and physical tests to ascertain the object's age
staying humanThis work happens in the physical world: object documentation, in a real place. Software cannot follow it there.
importance 4 · SupplementalSource: “Study object documentation or conduct standard chemical and physical tests to ascertain the object's age, composition, original appearance, need for treatment or restoration, and appropriate preservation method.” (O*NET task statement)
How this row was scored
Exposure score: 25 out of 100 (18–32 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Reading the object's paperwork is desk work, but the chemical and physical tests need the object on the bench.
The five ratings: output a model can produce 2/4 · 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 2/4.
Planning and conducting research to develop and improve methods of restoring and preserving specimens
staying humanThis work happens in the physical world: research, in a real place. Software cannot follow it there.
importance 3 · SupplementalSource: “Plan and conduct research to develop and improve methods of restoring and preserving specimens.” (O*NET task statement)
How this row was scored
Exposure score: 25 out of 100 (18–32 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Reviewing conservation literature is desk work, but developing new methods means testing them on real materials.
The five ratings: output a model can produce 2/4 · 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 2/4.
Specializing in particular materials or types of object
staying humanThis work happens in the physical world: particular materials, in a real place. Software cannot follow it there.
importance 4 · SupplementalSource: “Specialize in particular materials or types of object, such as documents and books, paintings, decorative arts, textiles, metals, or architectural materials.” (O*NET task statement)
How this row was scored
Exposure score: 8 out of 100 (1–15 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Building deep skill with one material, like textiles or metals, comes from years of handling the real thing.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Coordinating exhibit installations, assisting with design, constructing displays, dioramas, display cases and models and ensuring the availability of necessary materials
staying humanThis work happens in the physical world: exhibit installations, in a real place. Software cannot follow it there.
importance 4 · SupplementalSource: “Coordinate exhibit installations, assisting with design, constructing displays, dioramas, display cases, and models, and ensuring the availability of necessary materials.” (O*NET task statement)
How this row was scored
Exposure score: 7 out of 100 (0–14 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Coordinating an installation involves building display cases and models, which is workshop work.
The five ratings: output a model can produce 1/4 · 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 2/4.
Leading tours and teaching educational courses to students and the general public
staying humanThis work happens in the physical world: tours, in a real place. Software cannot follow it there.
importance 3 · CoreSource: “Lead tours and teach educational courses to students and the general public.” (O*NET task statement)
How this row was scored
Exposure score: 7 out of 100 (0–14 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Tour material can be drafted, but leading a group through a gallery depends on a person in the room.
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 3/4 · how much data exists 2/4.
Directing and supervising curatorial, technical and student staff in the handling, mounting, care and storage of art objects
staying humanThis work happens in the physical world: curatorial, technical and student staff, in a real place. Software cannot follow it there.
importance 4 · SupplementalSource: “Direct and supervise curatorial, technical, and student staff in the handling, mounting, care, and storage of art objects.” (O*NET task statement)
How this row was scored
Exposure score: 4 out of 100 (0–11 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Directing staff in how to handle and mount art means being present and trusted while they do it.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 3/4 · how much data exists 2/4.
Supervising and working with volunteers
staying humanThis work happens in the physical world: volunteers, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Supervise and work with volunteers.” (O*NET task statement)
How this row was scored
Exposure score: 3 out of 100 (0–10 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Working alongside volunteers depends on being present with them and building a working relationship.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 3/4 · how much data exists 1/4.
Performing on-site field work which may involve interviewing people
staying humanThis work happens in the physical world: on-site field work, in a real place. Software cannot follow it there.
importance 3 · CoreSource: “Perform on-site field work which may involve interviewing people, inspecting and identifying artifacts, note-taking, viewing sites and collections, and repainting exhibition spaces.” (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: Field work means traveling to sites, handling artifacts, and even repainting spaces 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 1/4.
Repairing, restoring and reassemble artifacts, designing and fabricating missing or broken parts
staying humanThis work happens in the physical world: reassemble artifacts, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Repair, restore, and reassemble artifacts, designing and fabricating missing or broken parts, to restore them to their original appearance and prevent deterioration.” (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: Repairing an artifact and making replacement parts is skilled work with the object in hand.
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 1/4.
Preserving or directing preservation of objects
staying humanThis work happens in the physical world: preservation of objects, in a real place. Software cannot follow it there.
importance 3 · SupplementalSource: “Preserve or direct preservation of objects, using plaster, resin, sealants, hardeners, and shellac.” (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: Applying plaster, resin and sealants to preserve an object is hands-on treatment.
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 1/4.
Building, repairing and installing wooden steps, scaffolds and walkways to gain access to or permit improved view of exhibited equipment
staying humanThis work happens in the physical world: wooden steps, scaffolds and walkways, in a real place. Software cannot follow it there.
importance 3 · SupplementalSource: “Build, repair, and install wooden steps, scaffolds, and walkways to gain access to or permit improved view of exhibited 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: work that happens in the physical world.
The rating behind it: Building and installing steps, scaffolds and walkways is carpentry.
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 1/4.
Delivering artwork on courier trips
staying humanThis work happens in the physical world: artwork, in a real place. Software cannot follow it there.
importance 3 · SupplementalSource: “Deliver artwork on courier trips.” (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: Traveling with artwork as a courier is defined by a person physically accompanying it.
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 1/4.
What this job pays, and how many people do it
- Median pay
- $51,440a 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
- 12,310in 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: information in, a record out. The rows above are exactly that shape: entering information about museum collections into computer databases. What it cannot do is be there in the room, and that is still where objects 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: photographing objects for documentation 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, 23% in rows that change shape rather than disappear, and 77% in rows it is nowhere near. That is the position, measured across 24 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. Entering information about museum collections into computer databases 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 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 whether objects need repair is 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 entering information about museum collections into computer databases. 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 museum technicians and conservators (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was fine artists, including painters, sculptors, and illustrators: only about 3% of its durable work is work you already do. 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 “determine whether objects need repair and choose the safest and most effective…” 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.
Fine Artists, Including Painters, Sculptors, and Illustrators
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already photograph objects for documentation, and their equivalent is to photograph objects, places, or scenes for reference material. Across both published task lists that is about 3% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 3% of the durable side of that job. That is a different job, not a next step.
Curators
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already supervise and work with volunteers, and their equivalent is to train and supervise curatorial, fiscal, technical, research, and clerical staff, as well as…. Across both published task lists that is about 2% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 2% of the durable side of that job. That is a different job, not a next step.
Anthropologists and Archeologists
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already repair, restore, and reassemble artifacts, designing and fabricating missing or broken parts, to…, and their equivalent is to clean, restore, and preserve artifacts. Across both published task lists that is about 2% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 2% 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 24 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 photographing objects for documentation 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 Archivists, conservators and curators 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 Archivists, conservators and curators and Library clerks and assistants. 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
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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 museum technicians / conservators launches. Nothing else.
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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 Museum Technicians and Conservators?
- Not as a job, but it is already doing parts of the work. Across the 24 official task statements scored for Museum Technicians and Conservators (United States, SOC 25-4013), 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 “Museum Technicians and Conservators” can AI already do?
- The highest-scoring tasks in release 2026-q4.1 are: “Classify and assign registration numbers to artifacts and supervise inventory control” (56/100, partial); “Prepare reports on the operation of conservation laboratories, documenting the condition of artifacts, treatment options, and the methods of preservation and…” (56/100, partial); “Enter information about museum collections into computer databases” (56/100, partial). 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 “Museum Technicians and Conservators” stay human?
- About 77% 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: “Deliver artwork on courier trips” (0/100, minimal); “Photograph objects for documentation” (0/100, minimal); “Build, repair, and install wooden steps, scaffolds, and walkways to gain access to or permit improved view of exhibited equipment” (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 “Museum Technicians and Conservators” do about AI?
- Start from the ledger rather than the headline: 0% of this job's weighted core work is exposed, and roughly 77% 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 Museum Technicians and Conservators 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 24 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 2026-08-05.
- 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.