Will AI replace Editors?

Not as a job, but it is already doing parts of the work. Across the 21 official task statements scored for Editors (United States, SOC 27-3041), 59% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 58 out of 100 (range 52–65, band: partial). 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 “Editors” can AI already do?

The highest-scoring tasks in release 2026-q4.1 are: “Prepare, rewrite and edit copy to improve readability, or supervise others who do this work” (83/100, very high); “Verify facts, dates, and statistics, using standard reference sources” (83/100, very high); “Read material to determine index items and arrange them alphabetically or topically, indicating page or chapter location” (83/100, very 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 “Editors” stay human?

About 25% 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: “Interview and hire writers and reporters or negotiate contracts, royalties, and payments for authors or freelancers” (13/100, minimal); “Supervise and coordinate work of reporters and other editors” (17/100, minimal); “Meet frequently with artists, typesetters, layout personnel, marketing directors, and production managers to discuss projects and resolve problems” (17/100, 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 “Editors” do about AI?

Start from the ledger rather than the headline: 59% of this job's weighted core work is exposed, and roughly 25% 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 Editors 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 21 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

Editors

reading copy or proof to detect and correct errors in spelling, supervising and coordinating work of reporters and other editors and monitoring news-gathering operations to ensure utilization of all news sources. If that's your week, this page is about your job.

The honest answer

Most tasks in this job are the kind AI has learned to do: verifying facts, dates and statistics, using standard reference sources. The tasks, though, are not you.

Your move: three real directions from here ↓

Where the work sits, by task weight

shifting to AI: 59%
changing shape: 16%
staying human: 25%

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

Whole-job exposure score 58 out of 100 (52–65 allowing for uncertainty): partial exposure, across 21 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 editors 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.

It would be a lie to soften that; conferring with management and editorial staff members regarding placement and emphasis of developing news stories is what this work rebuilds around. Your move starts there.

Your week, as this page understands it

Plan, coordinate, revise, or edit written material. May review proposals and drafts for possible publication. The job title says “editors”. The real job is the part underneath: conferring with management and editorial staff members regarding placement and emphasis of developing news stories. 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 editors is not one task. It is 21 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is conferring with management and editorial staff members regarding placement and emphasis of developing news stories, and the ledger below shows exactly why.

Where the work sits, by task weight

shifting to AI: 59%
changing shape: 16%
staying human: 25%

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.

3 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

11 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.

Reading copy or proof to detect and correct errors in spelling
This is reading one thing and writing another: copy in, a record out. That is the shape today's tools are built for.
importance 5 · Core
Source: “Read copy or proof to detect and correct errors in spelling, punctuation, and syntax.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 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: Detecting and correcting text errors is highly automated work with vast reference material behind it.
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.
Verifying facts, dates and statistics, using standard reference sources
This is reading one thing and writing another: facts, dates and statistics in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Verify facts, dates, and statistics, using standard reference sources.” (O*NET task statement)
How this row was scored
Exposure score: 83 out of 100 (76–90 allowing for uncertainty): very 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: Checking facts and dates against reference sources is fast with software, though it still needs verifying.
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 4/4.
Reading, evaluating and editing manuscripts or other materials
This is reading one thing and writing another: manuscripts in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Read, evaluate and edit manuscripts or other materials submitted for publication, and confer with authors regarding changes in content, style or organization, or publication.” (O*NET task statement)
How this row was scored
Exposure score: 68 out of 100 (61–75 allowing for uncertainty): high 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: Editing a manuscript is well supported by software, but agreeing changes runs through the relationship with the author.
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 2/4.
Preparing rewrite and editing copy to improve readability
This is reading one thing and writing another: rewrite in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Prepare, rewrite and edit copy to improve readability, or supervise others who do this work.” (O*NET task statement)
How this row was scored
Exposure score: 83 out of 100 (79–87 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: Rewriting copy to read better is one of the clearest strengths of current writing tools.
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 4/4.

Changing shape

4 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.

Reviewing and approving proofs submitted by composing room prior to publication production
The software now makes the first pass at proofs, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · Core
Source: “Review and approve proofs submitted by composing room prior to publication production.” (O*NET task statement)
How this row was scored
Exposure score: 49 out of 100 (42–56 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: Checking proofs before print is close reading software does well, though someone signs off before it runs.
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 0/4 · how much data exists 3/4.
Assigning topics, events and stories to individual writers or reporters for coverage
The software now makes the first pass at topics, events and stories, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · Core
Source: “Assign topics, events and stories to individual writers or reporters for coverage.” (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: mistakes that are cheap to catch.
The rating behind it: Assigning stories depends on knowing which reporter suits which subject and what they are already working on.
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 1/4 · how much data exists 2/4.
Making manuscript acceptance or revision recommendations to the publisher
The software now makes the first pass at manuscript acceptance, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · Supplemental
Source: “Make manuscript acceptance or revision recommendations to the publisher.” (O*NET task statement)
How this row was scored
Exposure score: 49 out of 100 (42–56 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: A recommendation on a manuscript can be drafted, but the publisher relies on the editor’s own judgment.
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 1/4 · how much data exists 3/4.

Staying human

6 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.

Overseeing publication production, including artwork, layout, computer typesetting and printing ensuring adherence to deadlines and budget requirements
The ratings behind this row put publication production, including artwork, layout well outside what today's tools can do on their own.
importance 4 · Core
Source: “Oversee publication production, including artwork, layout, computer typesetting, and printing, ensuring adherence to deadlines and budget requirements.” (O*NET task statement)
How this row was scored
Exposure score: 37 out of 100 (30–44 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.
The rating behind it: Production oversight is coordination across artwork, print and deadlines that needs someone chasing people.
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 3/4.
Conferring with management and editorial staff members regarding placement and emphasis of developing news stories
The value here is that a specific person handles management and stands behind it. That is earned, not computed.
importance 4 · Core
Source: “Confer with management and editorial staff members regarding placement and emphasis of developing news stories.” (O*NET task statement)
How this row was scored
Exposure score: 17 out of 100 (10–24 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: Where a story sits and how hard it is pushed is decided in newsroom conversations.
The five ratings: output a model can produce 1/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.
Supervising and coordinating work of reporters and other editors
The value here is that a specific person handles work of reporters and stands behind it. That is earned, not computed.
importance 4 · Core
Source: “Supervise and coordinate work of reporters and other editors.” (O*NET task statement)
How this row was scored
Exposure score: 17 out of 100 (10–24 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: Running a newsroom team depends on knowing and directing individual reporters.
The five ratings: output a model can produce 1/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.

Show the other 11 tasks

Reading material to determine index items and arrange them alphabetically or topically
shifting to AI
This is reading one thing and writing another: material in, a record out. That is the shape today's tools are built for.
importance 3 · Supplemental
Source: “Read material to determine index items and arrange them alphabetically or topically, indicating page or chapter location.” (O*NET task statement)
How this row was scored
Exposure score: 83 out of 100 (79–87 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: Pulling index terms out of a text and ordering them is structured work software does quickly.
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 4/4.
Writing text, such as stories, articles, editorials or newsletters
shifting to AI
This is reading one thing and writing another: text in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Write text, such as stories, articles, editorials, or newsletters.” (O*NET task statement)
How this row was scored
Exposure score: 83 out of 100 (79–87 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: Drafting articles, editorials and newsletters is core written output software produces to a usable standard.
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 4/4.
Planning the contents of publications according to the publication's style
shifting to AI
This is reading one thing and writing another: the contents of publications in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Plan the contents of publications according to the publication's style, editorial policy, and publishing requirements.” (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: Planning contents against a known style and editorial policy is structured work software supports 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.
Developing story or content ideas
shifting to AI
This is reading one thing and writing another: story in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Develop story or content ideas, considering reader or audience appeal.” (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: Generating story and content ideas for a known audience is something software does copiously and quickly.
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.
Monitoring news-gathering operations to ensure utilization of all news sources
shifting to AI
This is reading one thing and writing another: operations in, a record out. That is the shape today's tools are built for.
importance 4 · Supplemental
Source: “Monitor news-gathering operations to ensure utilization of all news sources, such as press releases, telephone contacts, radio, television, wire services, and other reporters.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 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: Monitoring wires, releases and other news sources is continuous scanning software does 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.
Selecting local, state, national and international news items received from wire services
shifting to AI
This is reading one thing and writing another: local, state, national and international news items in, a record out. That is the shape today's tools are built for.
importance 4 · Supplemental
Source: “Select local, state, national, and international news items received from wire services, based on assessment of items' significance and interest value.” (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: Sorting wire items by significance and interest is judgment software now approximates well against a known audience.
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.
Arranging for copyright permissions
shifting to AI
This is reading one thing and writing another: copyright permissions in, a record out. That is the shape today's tools are built for.
importance 3 · Supplemental
Source: “Arrange for copyright permissions.” (O*NET task statement)
How this row was scored
Exposure score: 66 out of 100 (59–73 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: Copyright permissions follow set correspondence and record-keeping 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 0/4 · how much data exists 3/4.
Allocating print space for story text
changing shape
The software now makes the first pass at print space, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · Supplemental
Source: “Allocate print space for story text, photos, and illustrations according to space parameters and copy significance, using knowledge of layout principles.” (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: Layout software helps allocate space, but the final page balance is still an editor’s call.
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.
Directing the policies and departments of newspapers
staying human
The value here is that a specific person handles the policies and stands behind it. That is earned, not computed.
importance 4 · Supplemental
Source: “Direct the policies and departments of newspapers, magazines and other publishing establishments.” (O*NET task statement)
How this row was scored
Exposure score: 23 out of 100 (16–30 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the value is that a specific person does it.
The rating behind it: Directing a publication’s policies and departments is leadership exercised among people.
The five ratings: output a model can produce 1/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.
Meeting frequently with artists, typesetters, layout personnel, marketing directors and production managers to discuss projects and resolve problems
staying human
The value here is that a specific person handles artists, typesetters, layout personnel and stands behind it. That is earned, not computed.
importance 4 · Core
Source: “Meet frequently with artists, typesetters, layout personnel, marketing directors, and production managers to discuss projects and resolve problems.” (O*NET task statement)
How this row was scored
Exposure score: 17 out of 100 (10–24 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: Resolving production problems happens in meetings with the people doing each part of the job.
The five ratings: output a model can produce 1/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.
Interviewing and hiring writers and reporters or negotiating contracts
staying human
The value here is that a specific person handles writers and stands behind it. That is earned, not computed.
importance 3 · Supplemental
Source: “Interview and hire writers and reporters or negotiate contracts, royalties, and payments for authors or freelancers.” (O*NET task statement)
How this row was scored
Exposure score: 13 out of 100 (6–20 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: Hiring writers and negotiating terms depends on judgment about people and live negotiation.
The five ratings: output a model can produce 1/4 · 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.

What this job pays, and how many people do it

Median pay: $77,920a 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: 91,690in 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: facts, dates and statistics in, a record out. The rows above are exactly that shape: verifying facts, dates and statistics, using standard reference sources and reading copy or proof to detect and correct errors in spelling. What it cannot do is be trusted in person, which is what management runs on: someone specific doing it and standing behind it. 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

The exposed part of your job is the biggest part, and I am not going to dress that up: verifying facts, dates and statistics, using standard reference sources is work today's tools do quickly and cheaply, and that is not coming back.

So, given all that: 59% of this job's task weight sits in rows the software is already learning, 16% in rows that change shape rather than disappear, and 25% in rows it is nowhere near. That is the position, measured across 21 scored tasks. It is not a forecast about you.

What you have that the software does not is conferring with management and editorial staff members regarding placement and emphasis of developing news stories, plus the years of knowing when something looks wrong before you can say why. That is the raw material for everything below.

This week: one thing

Sit on the machine's side of the desk. Pick one real piece of facts, dates and statistics you would normally do yourself, let whatever software you already have take the first pass at it, and then go through what it produced and write down every single thing it got wrong. One evening this week. Do not fix anything yet. Just catch it.

What you end up holding: a written list of the machine’s mistakes, in your handwriting
How long it takes: an evening, or an hour if you pick one job rather than one client

If you can’t run software on your employer’s or your clients’ data: Do the same hunt on paper. Take one printed piece of facts, dates and statistics, work through it the way you always do, and mark every point where you made a call rather than followed a rule. Same evening, same list, nothing to log into and nobody to ask permission from. That list is the same artifact: it is the judgment written down.

Over the next 90 days

Change one sentence about what you do. Not on a CV. Out loud, to whoever pays you. From “my job is verifying facts, dates and statistics, using standard reference sources” to “I check what the software does and tell you what it means.” Your error list from this week is what makes that sentence true instead of a claim, so use it: show it once, to one person, inside the next ninety days. Same skills, priced as judgment rather than as typing.

Over the next 12 months

Walk toward the end of this job that answers for things, and get it recognised. Pick the one part of conferring with management and editorial staff members regarding placement and emphasis of developing news stories you are already best at, and spend the year making it formal: a qualification, a named responsibility, a specialism people ask for by name. Price it honestly: that is evenings, it is months rather than weeks, and the seats are competitive because everyone in your position is looking at the same door. 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 editors (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was proofreaders and copy markers: only about 15% of its durable work is work you already do, it is under the same pressure this job is, it pays 34.4% less and there are far fewer of those jobs than of yours. Your own job splits about 59/41: that share of the list sits in the top exposure band and the rest does not. On this evidence the honest move is inside the job rather than out of it. Become the person who owns “oversee publication production”, and let the exposed end go.

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.

Proofreaders and Copy Markers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already read copy or proof to detect and correct errors in spelling, punctuation, and…, and their equivalent is to read proof sheets aloud, calling out punctuation marks and spelling unusual words and…. Across both published task lists that is about 15% of the durable work in that job.
Why I am not recommending it: You would be starting most of it from nothing: about 15% of the durable work in that job is work you do today, and the rest you would be learning while the bills carried on. I will not move you off one melting floe onto another: 81% of its own task list already scores in the top exposure band (80/100 in this release), so the same software is eating it. It is a pay cut, in those words: $51,120 against your $77,920, 34.4% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice. And it is a narrow door: about 4,580 of those jobs against 91,690 of yours (OEWS May 2025), 5% as many seats.
Look at that job’s page anyway →
News Analysts, Reporters, and Journalists
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already supervise and coordinate work of reporters and other editors, and their equivalent is to discuss issues with editors to establish priorities or positions. 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: $62,200 against your $77,920, 20.2% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice.
Look at that job’s page anyway →
Writers and Authors
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already make manuscript acceptance or revision recommendations to the publisher, and their equivalent is to confer with clients, editors, publishers, or producers to discuss changes or revisions to…. 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.
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: 59% of its task weight, across 21 scored tasks. Every row behind it is printed above with the source. Check ours; ignore theirs.
“It’s too late for me to become something else”
You are not starting from zero, and the page shows why: conferring with management and editorial staff members regarding placement and emphasis of developing news stories is work the software cannot do and you already do it. The move above is a repricing of what you know, not a new career. Nobody who has just left college has that.
“I should learn to code”
Almost certainly not. The value in your job is moving toward checking, deciding and answering for the output, not toward writing the software. A weekend of Python will not change your position; the error list from this week will.
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 Newspaper, periodical and broadcast editors 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 Newspaper, periodical and broadcast editors, Newspaper and periodical broadcast journalists and reporters, Authors, writers and translators and Managers and directors in the creative industries. 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

Two honest options, and no deadline on either

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:
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A nearby route

There's no Space built for editors yet.

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

The closest match is The AI Authority, a community for non-technical managers and domain experts turning one-off AI prompts into workflows a team can trust. It overlaps with the part of your job that is growing: owning AI-drafted text (verifying the claims in it, keeping it in your own voice, and setting a review gate before anything is sent). It is written for managers and consultants, not for the publishing trade: no editorial craft, no house style, no commissioning. If that overlap isn't you, the free route below covers the same ground.

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.

After the trial it is a paid community, and you get identical data either way. If the overlap above is not your job, the moves above cost nothing and stand on their own.

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

That did not look like an email address, so nothing was saved. Have another go below.

We could not save that. The fault is ours, not yours, and your address was not stored. Please try again later.

No deadline on any of this. The page will still be here, and the data is refreshed on a published schedule rather than when someone wants a headline.

Questions people ask about this job

Will AI replace Editors?: Not as a job, but it is already doing parts of the work. Across the 21 official task statements scored for Editors (United States, SOC 27-3041), 59% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 58 out of 100 (range 52–65, band: partial). 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 “Editors” can AI already do?: The highest-scoring tasks in release 2026-q4.1 are: “Prepare, rewrite and edit copy to improve readability, or supervise others who do this work” (83/100, very high); “Verify facts, dates, and statistics, using standard reference sources” (83/100, very high); “Read material to determine index items and arrange them alphabetically or topically, indicating page or chapter location” (83/100, very 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 “Editors” stay human?: About 25% 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: “Interview and hire writers and reporters or negotiate contracts, royalties, and payments for authors or freelancers” (13/100, minimal); “Supervise and coordinate work of reporters and other editors” (17/100, minimal); “Meet frequently with artists, typesetters, layout personnel, marketing directors, and production managers to discuss projects and resolve problems” (17/100, 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 “Editors” do about AI?: Start from the ledger rather than the headline: 59% of this job's weighted core work is exposed, and roughly 25% 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 Editors 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 21 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.
3 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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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}
}

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.