US dataswitch to UK
First-Line Supervisors of Production and Operating Workers
enforcing safety and sanitation regulations, interpreting specifications, blueprints, job orders and company policies and procedures and observing work and monitoring gauges. 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: planning and establishing work schedules. That is a slice of tasks, not of you.
That slice is not coming back; the core of the job, enforcing safety and sanitation regulations, stays yours. New tools, same person answering for it.
Your week, as this page understands it
Directly supervise and coordinate the activities of production and operating workers, such as inspectors, precision workers, machine setters and operators, assemblers, fabricators, and plant and system operators. Excludes team or work leaders. The job title says “first-line supervisors of production” or “operating workers”: officially one job, two names. The real job is the part underneath: enforcing safety and sanitation regulations. 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 first-line supervisors of production and operating workers is not one task. It is 20 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is enforcing safety and sanitation regulations, and the ledger below shows exactly why.
Where the work sits, by task weight
- shifting to AI
- 33%
- changing shape
- 0%
- staying human
- 67%
These bars are tasks changing hands, not people being counted out. The ledger below shows which.
Whole-job exposure score 39 out of 100 (34–45 allowing for uncertainty): low exposure, across 20 scored tasks. The number is the support for the sentence above it, not a headline about anyone’s future.
How we know this
What is measured: Every published task statement for first-line supervisors of production and operating workers is rated on five dimensions: can a model produce the output, does the work need a body in a room, does it need a legally accountable person, does it depend on a person being trusted in the moment, and how much data exists. A published formula turns those five ratings into the score; the model never writes the number.
How the bar is built: Each task’s share of the bar is its published importance weight, so a task you do all day counts for more than one you do twice a year.
Release: 2026-q4.1, scores computed 2026-08-04. Read the full method.
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.
- 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
7 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.
Planning and establishing work schedules
This is reading one thing and writing another: work schedules in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Plan and establish work schedules, assignments, and production sequences to meet production goals.” (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: Building schedules and production sequences from goals and available capacity is a planning problem software solves 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.
Reading and analyzing charts, work orders
This is reading one thing and writing another: charts, work orders in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Read and analyze charts, work orders, production schedules, and other records and reports to determine production requirements and to evaluate current production estimates and outputs.” (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: Reading production schedules and reports and drawing conclusions from them is exactly the kind of paperwork 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 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Requisitioning materials, supplies, equipment parts or repairing services
This is reading one thing and writing another: materials, supplies, equipment parts or repairing services in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Requisition materials, supplies, equipment parts, or repair services.” (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: Raising requisitions for parts and services is straightforward ordering paperwork.
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.
Keeping records of employees' attendance and hours
This is reading one thing and writing another: records of employees' attendance in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Keep records of employees' attendance and hours worked.” (O*NET task statement)
How this row was scored
Exposure score: 93 out of 100 (89–97 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: Attendance and hours are already captured and totalled by timekeeping systems better than by hand.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Calculating labor and equipment requirements and production specifications
This is reading one thing and writing another: labor in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Calculate labor and equipment requirements and production specifications, using standard formulas.” (O*NET task statement)
How this row was scored
Exposure score: 93 out of 100 (89–97 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: These are standard formulas applied to workplace figures, which is arithmetic software does reliably.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Changing shape
0 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.
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.
Staying human
13 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.
Enforcing safety and sanitation regulations
This work happens in the physical world: safety, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Enforce safety and sanitation regulations.” (O*NET task statement)
How this row was scored
Exposure score: 7 out of 100 (3–11 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: the same decision, made over and over; work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Rules can be written up automatically, but enforcing them means being on the floor and speaking to people directly.
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 2/4 · how much data exists 3/4.
Inspecting materials, products or equipment to detect defects or malfunctions
This work happens in the physical world: materials, products or equipment, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Inspect materials, products, or equipment to detect defects or malfunctions.” (O*NET task statement)
How this row was scored
Exposure score: 8 out of 100 (4–12 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Detecting a defect or malfunction means someone physically handling or examining the item.
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.
Conferring with management or subordinates to resolve worker problems
The value here is that a specific person handles management and stands behind it. That is earned, not computed.
importance 4 · CoreSource: “Confer with management or subordinates to resolve worker problems, complaints, or grievances.” (O*NET task statement)
How this row was scored
Exposure score: 14 out of 100 (10–18 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: the value is that a specific person does it.
The rating behind it: Sorting out a grievance depends on a trusted person listening and being believed by both sides.
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 3/4 · how much data exists 1/4.
Conferring with other supervisors to coordinate operations and activities within or between departments
The value here is that a specific person handles other supervisors and stands behind it. That is earned, not computed.
importance 4 · CoreSource: “Confer with other supervisors to coordinate operations and activities within or between departments.” (O*NET task statement)
How this row was scored
Exposure score: 17 out of 100 (13–21 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: the value is that a specific person does it.
The rating behind it: Coordinating between departments happens through live conversation where colleagues negotiate and agree in the moment.
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.
Evaluating employee performance
The value here is that a specific person handles employee performance and stands behind it. That is earned, not computed.
importance 4 · CoreSource: “Evaluate employee performance.” (O*NET task statement)
How this row was scored
Exposure score: 35 out of 100 (28–42 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: Drafting an appraisal is easy, but the judgement rests on things a manager notices in person and rarely writes down.
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 2/4 · how much data exists 2/4.
Show the other 10 tasks
Maintaining operations data, such as time, production and cost records and preparing management reports of production results
shifting to AIThis is reading one thing and writing another: operations data in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Maintain operations data, such as time, production, and cost records, and prepare management reports of production results.” (O*NET task statement)
How this row was scored
Exposure score: 93 out of 100 (89–97 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: Keeping production and cost records and turning them into management reports is routine data work for software.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Determining standards, budgets, production goals and rates, based on company policies, equipment and labor availability and workloads
shifting to AIThis is reading one thing and writing another: standards, budgets, production goals and rates in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Determine standards, budgets, production goals, and rates, based on company policies, equipment and labor availability, and workloads.” (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: Setting targets, budgets and rates is a calculation from policy, capacity and workload figures 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 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Interpreting specifications, blueprints, job orders and company policies and procedures for workers
staying humanThe ratings behind this row put specifications, blueprints well outside what today's tools can do on their own.
importance 4 · CoreSource: “Interpret specifications, blueprints, job orders, and company policies and procedures for workers.” (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: Software can explain written specifications and policies clearly, though drawings and shop-floor questions still often need a person.
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.
Recommending or executing personnel actions
staying humanThe value here is that a specific person handles personnel actions and stands behind it. That is earned, not computed.
importance 4 · CoreSource: “Recommend or execute personnel actions, such as hirings, evaluations, or promotions.” (O*NET task statement)
How this row was scored
Exposure score: 35 out of 100 (28–42 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: Paperwork for hires and promotions is easy, but the underlying calls about people rest on personal judgement.
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 2/4 · how much data exists 2/4.
Planning and developing new products and production processes
staying humanThe ratings behind this row put new products well outside what today's tools can do on their own.
importance 3 · CoreSource: “Plan and develop new products and production processes.” (O*NET task statement)
How this row was scored
Exposure score: 24 out of 100 (17–31 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the five ratings behind the score, with no single dominant reason.
The rating behind it: New products and processes need original design work; software gives starting points that need heavy expert rework.
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 0/4 · how much data exists 2/4.
Conducting employee training in equipment operations or work and safety procedures
staying humanThis work happens in the physical world: employee, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Conduct employee training in equipment operations or work and safety procedures, or assign employee training to experienced workers.” (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: Training material can be produced automatically, but showing someone how to run equipment safely happens beside the machine.
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.
Recommending or implementing measures to motivate employees and to improve production methods
staying humanThis work happens in the physical world: measures, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Recommend or implement measures to motivate employees and to improve production methods, equipment performance, product quality, or efficiency.” (O*NET task statement)
How this row was scored
Exposure score: 18 out of 100 (11–25 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: Suggesting improvements is easy to automate, but actually getting people to change how they work happens on the floor.
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 2/4.
Observing work and monitoring gauges
staying humanThis work happens in the physical world: work, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Observe work and monitor gauges, dials, and other indicators to ensure that operators conform to production or processing standards.” (O*NET task statement)
How this row was scored
Exposure score: 14 out of 100 (7–21 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Instrument readings can be monitored digitally, but watching how operators actually work means being on the floor.
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 0/4 · how much data exists 3/4.
Directing and coordinating the activities of employees engaged in the production or processing of goods
staying humanThis work happens in the physical world: the activities of employees, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Direct and coordinate the activities of employees engaged in the production or processing of goods, such as inspectors, machine setters, or fabricators.” (O*NET task statement)
How this row was scored
Exposure score: 11 out of 100 (7–15 allowing for uncertainty): minimal exposure, high 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 a production crew mixes being present on the floor with the personal authority to redirect people.
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 2/4 · how much data exists 2/4.
Setting up and adjusting machines and equipment
staying humanThis work happens in the physical world: and adjusting machines, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Set up and adjust machines and 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: Setting up and adjusting a machine means physically handling the machine.
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
- $74,450a 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
- 673,430in 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: work schedules in, a record out. The rows above are exactly that shape: planning and establishing work schedules and reading and analyzing charts, work orders. What it cannot do is be there in the room, and that is still where safety 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
Your week is splitting in two, and which half fills it is the whole question. Planning and establishing work schedules is going; enforcing safety and sanitation regulations is not.
So, given all that: 33% of this job's task weight sits in rows the software is already learning, 0% in rows that change shape rather than disappear, and 67% in rows it is nowhere near. That is the position, measured across 20 scored tasks. It is not a forecast about you.
The occupation is an average and you are not, so the first job below is finding out where your own week actually sits.
This week: one thing
Print the task ledger above and put your own hours next to each row. Roughly, in pen, in one sitting. Then look at which group your hours actually pile up in. Twenty minutes, this week.
- What you end up holding
- your own week, on one page, sorted into what is shifting and what is not
- How long it takes
- about twenty minutes
If printing it isn’t practical: Read the rows off this page and write the same list on the back of an envelope. Same twenty minutes, same page, and it works just as well said out loud to someone who knows the job. The point is your hours next to the rows, not the paper it is on.
Over the next 90 days
Volunteer toward the durable end, visibly. Over the next ninety days put your hand up for the work in the bottom group (enforcing safety and sanitation regulations) and let people see you doing it. Not a new project: the same job, with your mix deliberately tilted. The point is that when the rota or the reorganisation comes, the version of you people picture is the one doing the part that stays.
Over the next 12 months
Claim a specialism at the durable end and let the other end go. Over a year, deliberately become the person who handles enforcing safety and sanitation regulations, and deliberately stop being the first choice for the rows in the top group. That trade costs something, because the exposed work is often the comfortable work. Decide it on purpose rather than by drift. 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 first-line supervisors of production and operating workers (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was first-line supervisors of mechanics, installers, and repairers: only about 11% of its durable work is work you already do. And on the numbers you do not need one. This job scores 39/100 here, with only 33% of the task list in the top band, and “enforce safety and sanitation regulations” 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.
First-Line Supervisors of Mechanics, Installers, and Repairers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already interpret specifications, blueprints, job orders, and company policies and procedures for workers, and their equivalent is to interpret specifications, blueprints, or job orders to construct templates and lay out reference…. Across both published task lists that is about 11% of the durable work in that job.
Why I am not recommending it: You would be starting most of it from nothing: about 11% of the durable work in that job is work you do today, and the rest you would be learning while the bills carried on.
First-Line Supervisors of Personal Service Workers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already confer with management or subordinates to resolve worker problems, complaints, or grievances, and their equivalent is to investigate employee complaints and resolve problems following management rules and regulations. Across both published task lists that is about 9% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 9% of the durable side of that job. That is a different job, not a next step. It is a pay cut, in those words: $48,590 against your $74,450, 34.7% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice. And it is a narrow door: about 114,110 of those jobs against 673,430 of yours (OEWS May 2025), 17% as many seats.
Production, Planning, and Expediting Clerks
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already confer with other supervisors to coordinate operations and activities within or between departments, and their equivalent is to confer with department supervisors or other personnel to assess progress and discuss needed…. Across both published task lists that is about 6% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 6% of the durable side of that job. That is a different job, not a next step. I will not move you off one melting floe onto another: 61% of its own task list already scores in the top exposure band (64/100 in this release), so the same software is eating it. It is a pay cut, in those words: $59,650 against your $74,450, 19.9% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice.
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: 33% of its task weight, across 20 scored tasks. Every row behind it is printed above with the source. Check ours; ignore theirs.
The whole-job doom story
Nothing on this page says this job ends. It says the mix inside it moves. Half the rows above are unchanged or changing shape, and the plan is about which half your week sits in. That is a very different problem, and a solvable one.
Panic-buying a course
Do the twenty-minute sorting exercise first. Most people who buy a course before they have done it buy the wrong one, and the free services listed below will tell you the same thing without charging for it.
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.
If you run a team doing this job
If you run a team doing this job, the conversation you owe them is the one on this page, and sooner than feels comfortable. Show them the ledger rather than a reassurance: the rows moving toward the software are planning and establishing work schedules, and the rows that are not are where you want your people visible. Ask each of them to do the this-week move and bring the list to your next one-to-one. It turns a rumour into a piece of work, and it tells you which parts of your team's week are actually at stake. And say the thing out loud that a team lead usually leaves unsaid: a shrinking team is your exposure too, so do the move yourself as well.
You are reading the United States figures
The United Kingdom splits this work across more than one official group, of which Skilled metal, electrical and electronic trades supervisors 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 Skilled metal, electrical and electronic trades supervisors, Water and sewerage plant operatives and Production, factory and assembly supervisors. Pay is shown separately for each of those groups (medians cannot be averaged together), while the task list and the scores on this page are for this group only.
Your route through this
Where to go next, and what it costs
Free, and complete
The moves above cost nothing. These are the real services that go with them: public, government-funded, and free at the point of use. Nothing on this page is behind an email address or a payment.
Anywhere in the US:
CareerOneStop - Find local training
Search what's running near you, from the Labor Department's own database, before anyone sells you a course.
Free to search; individual programs vary, and some are funded
Anywhere in the US:
An American Job Center will sit down with you for free. Find yours by ZIP code.
Free
Anywhere in the US:
CareerOneStop - Licensed occupations finder
Check what your state actually requires before you pay for anything.
Free
Anywhere in the US:
Free
No Space for this job, but one for what is happening to it
Nothing Collab365 runs is built for first-line supervisors of production / operating workers, 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 33% of the work on this page is already inside what they can do.
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 first-line supervisors of production / operating workers. 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 first-line supervisors of production / operating workers 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 First-Line Supervisors of Production and Operating Workers?
- Not as a job, but it is already doing parts of the work. Across the 20 official task statements scored for First-Line Supervisors of Production and Operating Workers (United States, SOC 51-1011), 33% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 39 out of 100 (range 34–45, 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 “First-Line Supervisors of Production and Operating Workers” can AI already do?
- The highest-scoring tasks in release 2026-q4.1 are: “Maintain operations data, such as time, production, and cost records, and prepare management reports of production results” (93/100, very high); “Calculate labor and equipment requirements and production specifications, using standard formulas” (93/100, very high); “Keep records of employees' attendance and hours worked” (93/100, 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 “First-Line Supervisors of Production and Operating Workers” stay human?
- About 67% 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: “Set up and adjust machines and equipment” (0/100, minimal); “Enforce safety and sanitation regulations” (7/100, minimal); “Inspect materials, products, or equipment to detect defects or malfunctions” (8/100, 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 “First-Line Supervisors of Production and Operating Workers” do about AI?
- Start from the ledger rather than the headline: 33% of this job's weighted core work is exposed, and roughly 67% 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 First-Line Supervisors of Production and Operating Workers calculated?
- Each official task statement for the occupation is rated on five published 0–4 dimensions (output replicability, physical embodiment, licensed accountability, real-time human trust, and data availability) by claude-opus-5 using scoring prompt task_scoring_v1.0. The model never writes the score; a published formula turns the five ratings into a 0–100 number, so every score can be recomputed by hand. The occupation figure is the importance-weighted mean across 20 scored tasks. The prompt, the rubric, the formula and the full dataset are published at https://futureproof.collab365.com/method and https://futureproof.collab365.com/data/2026-q4.1 under CC BY 4.0.
Where these numbers come from
Worth knowing about these figures
- The match between this job and its counterpart in the other country is partial, so the two pages count slightly different groups of people.
- Task clusters are not derived in this release, so the task-cluster field is empty and no Collab365 Space routing is attached to this occupation yet.
- Task statements
- onet-dbProcessing: catalogue-bridge → onet-im-rt-weighting → task-scoring → score-aggregation
- Task weights
- onet-db (im-rt)
- Scores
- Rubric task_scoring_v1.0, model claude-opus-5, computed 2026-08-04.
- Pay and employment
- bls-oews (May 2025 estimates (national_M2025_dl.xlsx))bls-oews (May 2025 estimates (national_M2025_dl.xlsx))
Figures on this page come from release 2026-q4.1, published 2026-08-05. Every release keeps its own permanent address, so a figure you cite in March is still there, unchanged, in November.
The plain-English wording on this page is assembled directly from the task statements and the published ratings, not written by hand for this occupation. That is why it is specific, and it is also why we say so.
The routes and free resources further up are today’s, not the release’s (last reviewed 2026-08-05). A route is an offer, not a historical fact, so it moves on its own clock.
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.