Will AI replace Curators?

Not as a job, but it is already doing parts of the work. Across the 15 official task statements scored for Curators (United States, SOC 25-4012), 15% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 29 out of 100 (range 24–36, 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 “Curators” can AI already do?

The highest-scoring tasks in release 2026-q4.1 are: “Develop and maintain an institution's registration, cataloging, and basic record-keeping systems, using computer databases” (75/100, high); “Provide information from the institution's holdings to other curators and to the public” (64/100, high); “Write and review grant proposals, journal articles, institutional reports, and publicity materials” (58/100, 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 “Curators” 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: “Inspect premises to assess the need for repairs and to ensure that climate and pest control issues are addressed” (0/100, minimal); “Attend meetings, conventions, and civic events to promote use of institution's services, to seek financing, and to maintain community alliances” (3/100, minimal); “Study, examine, and test acquisitions to authenticate their origin, composition, history, and to assess their current value” (6/100, 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 “Curators” do about AI?

Start from the ledger rather than the headline: 15% 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 Curators 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 15 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

Curators

planning and organizing the acquisition, studying, examining and inspecting premises to assess the need for repairs and to ensure that climate and pest control issues. 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: providing information from the institution's holdings to other curators and to the public. 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: 15%
changing shape: 15%
staying human: 70%

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

Whole-job exposure score 29 out of 100 (24–36 allowing for uncertainty): low exposure, across 15 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 curators 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.

That slice is not coming back; the core of the job, planning and organizing the acquisition, stays yours. The tools change hands, the accountability doesn't.

Your week, as this page understands it

Administer collections, such as artwork, collectibles, historic items, or scientific specimens of museums or other institutions. May conduct instructional, research, or public service activities of institution. The job title says “curators”. The real job is the part underneath: planning and organizing the acquisition. 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 curators is not one task. It is 15 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is planning and organizing the acquisition, and the ledger below shows exactly why.

Where the work sits, by task weight

shifting to AI: 15%
changing shape: 15%
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 2026-08-05. 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

2 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.

Providing information from the institution's holdings to other curators and to the public
This is reading one thing and writing another: information in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Provide information from the institution's holdings to other curators and to the public.” (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: Answering questions about what the museum holds is lookup and explanation from records already digitized.
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.
Developing and maintaining an institution's registration
This is reading one thing and writing another: an institution's registration in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Develop and maintain an institution's registration, cataloging, and basic record-keeping systems, using computer databases.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (68–82 allowing for uncertainty): high 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: Cataloging systems follow published standards, so software can design and maintain the records well.
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 0/4 · 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.

Writing and reviewing grant proposals
The software now makes the first pass at grant proposals, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · Core
Source: “Write and review grant proposals, journal articles, institutional reports, and publicity materials.” (O*NET task statement)
How this row was scored
Exposure score: 58 out of 100 (51–65 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Reports and publicity draft easily, but grant bids and journal articles still need heavy expert rework.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Scheduling events and organizing details
The software now makes the first pass at events, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 3 · Supplemental
Source: “Schedule events and organize details, including refreshment, entertainment, decorations, and the collection of any fees.” (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: Scheduling an event and lining up catering and details is coordination work software 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 1/4 · how much data exists 3/4.
Arranging insurance coverage for objects on loan or for special exhibits and recommending changes in coverage for the entire collection
The software now makes the first pass at insurance coverage, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 3 · Supplemental
Source: “Arrange insurance coverage for objects on loan or for special exhibits and recommend changes in coverage for the entire collection.” (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: Arranging insurance for loans is standard paperwork against values and schedules already recorded.
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.

Staying human

10 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.

Planning and organizing the acquisition
This work happens in the physical world: the acquisition, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Plan and organize the acquisition, storage, and exhibition of collections and related materials, including the selection of exhibition themes and designs, and develop or install exhibit materials.” (O*NET task statement)
How this row was scored
Exposure score: 21 out of 100 (14–28 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: Exhibition themes can be drafted, but choosing acquisitions and installing the show involves real objects and spaces.
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 1/4 · how much data exists 2/4.
Planning and conducting special research projects in area of interest or expertise
The ratings behind this row put special research projects well outside what today's tools can do on their own.
importance 4 · Core
Source: “Plan and conduct special research projects in area of interest or expertise.” (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: mistakes that are cheap to catch.
The rating behind it: Research support is strong, but genuinely new scholarship still needs the curator's own expertise and sources.
The five ratings: output a model can produce 2/4 · 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.
Designing, organizing or conducting tours, workshops and instructional or educational sessions to acquaint individuals with an institution's facilities and materials
This work happens in the physical world: tours, workshops and instructional or educational sessions, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Design, organize, or conduct tours, workshops, and instructional or educational sessions to acquaint individuals with an institution's facilities and materials.” (O*NET task statement)
How this row was scored
Exposure score: 20 out of 100 (13–27 allowing for uncertainty): low 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: Session plans can be written, but running a tour or workshop depends on a person with the group.
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 2/4 · how much data exists 3/4.
Negotiating and authorizing purchase, sale, exchange or loan of collections
The value here is that a specific person handles purchase, sale, exchange or loan of collections and stands behind it. That is earned, not computed.
importance 4 · Core
Source: “Negotiate and authorize purchase, sale, exchange, or loan of collections.” (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 value is that a specific person does it.
The rating behind it: Negotiating a purchase or loan depends on trust between named people and on the curator's authority to commit.
The five ratings: output a model can produce 1/4 · needs a body in a room 1/4 · needs an accountable person 1/4 · needs to be trusted in the moment 3/4 · how much data exists 1/4.
Attending meetings, conventions and civic events to promote use of institution's services
This work happens in the physical world: meetings, conventions and civic events, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Attend meetings, conventions, and civic events to promote use of institution's services, to seek financing, and to maintain community alliances.” (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: Turning up at events to build alliances and seek funding is about being known and present.
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.

Show the other 5 tasks

Establishing specifications for reproductions and overseeing their manufacture or selecting items from commercially available replica sources
staying human
The ratings behind this row put specifications well outside what today's tools can do on their own.
importance 2 · Supplemental
Source: “Establish specifications for reproductions and oversee their manufacture or select items from commercially available replica sources.” (O*NET task statement)
How this row was scored
Exposure score: 32 out of 100 (25–39 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: mistakes that are cheap to catch.
The rating behind it: Reproduction specifications can be drafted, but overseeing manufacture and judging quality needs a person seeing samples.
The five ratings: output a model can produce 2/4 · 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.
Conferring with the board of directors to formulate and interpreting policies
staying human
The value here is that a specific person handles the board of directors and stands behind it. That is earned, not computed.
importance 4 · Core
Source: “Confer with the board of directors to formulate and interpret policies, to determine budget requirements, and to plan overall operations.” (O*NET task statement)
How this row was scored
Exposure score: 21 out of 100 (14–28 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the value is that a specific person does it.
The rating behind it: Board discussions on policy and budget turn on trust and standing with named people around the table.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 3/4 · how much data exists 2/4.
Training and supervising curatorial, fiscal, technical, research and clerical staff, as well as volunteers or interns
staying human
This work happens in the physical world: curatorial, fiscal, technical, research and clerical staff, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Train and supervise curatorial, fiscal, technical, research, and clerical staff, as well as volunteers or interns.” (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: work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Training and supervising staff and interns runs on personal working relationships.
The five ratings: output a model can produce 1/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 3/4 · how much data exists 2/4.
Studying, examining and testing acquisitions to authenticate their origin, composition, history and to assess their current value
staying human
This work happens in the physical world: acquisitions, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Study, examine, and test acquisitions to authenticate their origin, composition, history, and to assess their current value.” (O*NET task statement)
How this row was scored
Exposure score: 6 out of 100 (2–10 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Authenticating a piece depends on handling it and spotting things only experience notices.
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 1/4.
Inspecting premises to assess the need for repairs and to ensure that climate and pest control issues
staying human
This work happens in the physical world: premises, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Inspect premises to assess the need for repairs and to ensure that climate and pest control issues are addressed.” (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 the building to spot repair, climate and pest problems means being in the rooms.
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.

What this job pays, and how many people do it

Median pay: $63,420a 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: 12,150in 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: an institution's registration in, a record out. The rows above are exactly that shape: providing information from the institution's holdings to other curators and to the public and developing and maintaining an institution's registration. What it cannot do is be there in the room, and that is still where the acquisition gets 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: planning and organizing the acquisition is the middle of this job, and the evidence on this page says it stays with a person.

So, given all that: 15% of this job's task weight sits in rows the software is already learning, 15% in rows that change shape rather than disappear, and 70% in rows it is nowhere near. That is the position, measured across 15 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. Providing information from the institution's holdings to other curators and to the public 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 an institution's registration, 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 the acquisition 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 writing and reviewing grant proposals. 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 curators (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was museum technicians and conservators: only about 4% of its durable work is work you already do and it pays 18.9% less. And on the numbers you do not need one. This job scores 29/100 here, with only 15% of the task list in the top band, and “plan and organize the acquisition, storage, and exhibition of collections and related…” 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.

Museum Technicians and Conservators
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already train and supervise curatorial, fiscal, technical, research, and clerical staff, as well as…, and their equivalent is to supervise and work with volunteers. Across both published task lists that is about 4% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 4% of the durable side of that job. That is a different job, not a next step. It is a pay cut, in those words: $51,440 against your $63,420, 18.9% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice.
Look at that job’s page anyway →
Set and Exhibit Designers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already plan and organize the acquisition, storage, and exhibition of collections and related materials, and their equivalent is to examine objects to be included in exhibits to plan where and how to…. Across both published task lists that is about 4% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 4% of the durable side of that job. That is a different job, not a next step.
Look at that job’s page anyway →
Anthropologists and Archeologists
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already write and review grant proposals, journal articles, institutional reports, and publicity materials, and their equivalent is to write grant proposals to obtain funding for research. Across both published task lists that is about 1% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 1% of the durable side of that job. That is a different job, not a next step.
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: 15% of its task weight, across 15 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 planning and organizing the acquisition 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 nearest United Kingdom equivalent is Archivists, conservators and curators. It is a close match rather than an identical one: the two countries draw the boundary of the job in slightly different places.

Switch to the United Kingdom page →close match

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:
American Job Center locator
An American Job Center will sit down with you for free. Find yours by ZIP code.
Free
- CareerOneStop local help hub
Anywhere in the US:
CareerOneStop - Licensed occupations finder
Check what your state actually requires before you pay for anything.
Free
Anywhere in the US:
CareerOneStop
Free

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

Nothing Collab365 runs is built for curators, 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 15% 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 curators. 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 curators launches. Nothing else.

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No Space for curators 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 curators existed, with researched problems, courses and people in the same boat, would you want in?

Your email

We use your email address for one thing: to tell you if a Space for curators launches. We never sell it, never use it for unrelated marketing, and every email has a one-click unsubscribe. Our privacy policy has the full version.

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 Curators?: Not as a job, but it is already doing parts of the work. Across the 15 official task statements scored for Curators (United States, SOC 25-4012), 15% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 29 out of 100 (range 24–36, 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 “Curators” can AI already do?: The highest-scoring tasks in release 2026-q4.1 are: “Develop and maintain an institution's registration, cataloging, and basic record-keeping systems, using computer databases” (75/100, high); “Provide information from the institution's holdings to other curators and to the public” (64/100, high); “Write and review grant proposals, journal articles, institutional reports, and publicity materials” (58/100, 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 “Curators” 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: “Inspect premises to assess the need for repairs and to ensure that climate and pest control issues are addressed” (0/100, minimal); “Attend meetings, conventions, and civic events to promote use of institution's services, to seek financing, and to maintain community alliances” (3/100, minimal); “Study, examine, and test acquisitions to authenticate their origin, composition, history, and to assess their current value” (6/100, 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 “Curators” do about AI?: Start from the ledger rather than the headline: 15% 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 Curators 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 15 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

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.

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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}
}

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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.