US dataswitch to UK

First-Line Supervisors of Office and Administrative Support Workers

supervising the work of office, evaluating employees' job performance and conformance to regulations and recommending appropriate personnel action and training or instructing employees in job duties or company policies or arranging for training. If that's your week, this page is about your job.

The honest answer

This job is splitting in two: computing figures, balances, totals or commissions is work AI now does quickly and cheaply, and discussing job performance problems with employees to identify causes and issues and to work on resolving problems is work it can't touch.

Your move: what you can actually do about this ↓

Where the work sits, by task weight

shifting to AI: 40%
changing shape: 22%
staying human: 37%

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

Whole-job exposure score 52 out of 100 (46–59 allowing for uncertainty): partial exposure, across 28 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 office and administrative support 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.

Which half fills your week decides your exposure. That is more in your control than it sounds.

Your week, as this page understands it

Directly supervise and coordinate the activities of clerical and administrative support workers. The job title says “first-line supervisors of office” or “administrative support workers”: officially one job, two names. The real job is the part underneath: discussing job performance problems with employees to identify causes and issues and to work on resolving problems. 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 office and administrative support workers is not one task. It is 28 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is discussing job performance problems with employees to identify causes and issues and to work on resolving problems, and the ledger below shows exactly why.

Where the work sits, by task weight

shifting to AI: 40%
changing shape: 22%
staying human: 37%

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

How we know this

How the bar is built: Each task’s share of the bar is its published importance weight, so a task you do all day counts for more than one you do twice a year.

Release: 2026-q4.1, scores computed 2026-08-04. Read the full method.

Your job, task by task

These are the official task statements for this occupation, in plain English, sorted by what the evidence says is happening to each one. The official wording sits under every line so you can check the rewrite against it.

One row is marked low confidence, so treat it as a ballpark rather than a fine measurement.
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

12 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.

Researching, compiling and preparing reports, manuals, correspondence or other information required by management or governmental agencies
This is reading one thing and writing another: reports, manuals, correspondence or other information in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Research, compile, and prepare reports, manuals, correspondence, or other information required by management or governmental agencies.” (O*NET task statement)
How this row was scored
Exposure score: 81 out of 100 (74–88 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: Compiling reports, manuals and returns from existing information is writing work AI does well, with a manager approving what goes out.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Interpreting and communicating work procedures and company policies to staff
This is reading one thing and writing another: work procedures in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Interpret and communicate work procedures and company policies to staff.” (O*NET task statement)
How this row was scored
Exposure score: 64 out of 100 (57–71 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: Turning company policy into clear instructions for staff is writing and explaining 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 1/4 · how much data exists 3/4.
Developing or updating procedures, policies or standards
This is reading one thing and writing another: procedures, policies or standards in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Develop or update procedures, policies, or standards.” (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: Drafting and updating procedures and standards is document work AI 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 3/4.
Preparing and issuing 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 · Core
Source: “Prepare and issue work schedules, deadlines, and duty assignments for office or administrative staff.” (O*NET task statement)
How this row was scored
Exposure score: 79 out of 100 (75–83 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Building schedules and duty rosters from workloads and availability is a planning problem software solves quickly and well.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.

Changing shape

6 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.

Training or instructing employees in job duties or company policies or arranging for training
The software now makes the first pass at employees, but the part that matters is a person saying it and standing behind it. So the job becomes checking and deciding rather than producing.
importance 4 · Core
Source: “Train or instruct employees in job duties or company policies or arrange for training to be provided.” (O*NET task statement)
How this row was scored
Exposure score: 53 out of 100 (46–60 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; the value is that a specific person does it.
The rating behind it: AI produces good training material quickly, though someone still needs to teach it and answer the room's questions.
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 2/4 · how much data exists 3/4.
Supervising the work of office
The software now makes the first pass at the work of office, but the part that matters is a person saying it and standing behind it. So the job becomes checking and deciding rather than producing.
importance 4 · Core
Source: “Supervise the work of office, administrative, or customer service employees to ensure adherence to quality standards, deadlines, and proper procedures, correcting errors or problems.” (O*NET task statement)
How this row was scored
Exposure score: 40 out of 100 (33–47 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; the value is that a specific person does it.
The rating behind it: Checking work against standards can be automated, but correcting people and keeping quality up depends on knowing the team.
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 3/4.
Resolving customer complaints or answering customers' questions regarding policies and procedures
The software now makes the first pass at customer complaints, but the part that matters is a person saying it and standing behind it. So the job becomes checking and deciding rather than producing.
importance 4 · Core
Source: “Resolve customer complaints or answer customers' questions regarding policies and procedures.” (O*NET task statement)
How this row was scored
Exposure score: 53 out of 100 (46–60 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; the value is that a specific person does it.
The rating behind it: Software answers policy questions well, but an upset customer usually wants a person who can listen and put things right.
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 2/4 · 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.

Discussing job performance problems with employees to identify causes and issues and to work on resolving problems
The value here is that a specific person handles job performance problems and stands behind it. That is earned, not computed.
importance 4 · Core
Source: “Discuss job performance problems with employees to identify causes and issues and to work on resolving problems.” (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: Talking to someone about their performance is a conversation that depends entirely on the relationship between the two 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 3/4 · how much data exists 1/4.
Providing employees with guidance in handling difficult or complex problems or in resolving escalated complaints or disputes
The value here is that a specific person handles employees and stands behind it. That is earned, not computed.
importance 4 · Core
Source: “Provide employees with guidance in handling difficult or complex problems or in resolving escalated complaints or disputes.” (O*NET task statement)
How this row was scored
Exposure score: 28 out of 100 (24–32 allowing for uncertainty): low exposure, high confidence.
Why it sits in this group: the value is that a specific person does it.
The rating behind it: Coaching staff through a difficult case or a heated dispute rests on trust built with those individuals.
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 3/4 · how much data exists 2/4.
Evaluating employees' job performance and conformance to regulations and recommending appropriate personnel action
The value here is that a specific person handles employees' job performance and stands behind it. That is earned, not computed.
importance 4 · Core
Source: “Evaluate employees' job performance and conformance to regulations and recommend appropriate personnel action.” (O*NET task statement)
How this row was scored
Exposure score: 28 out of 100 (21–35 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: Performance data can be summarised automatically, but judging a person and recommending action rests on the manager who knows them.
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 3/4 · how much data exists 2/4.

Show the other 18 tasks

Maintaining records pertaining
shifting to AI
This is reading one thing and writing another: records in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Maintain records pertaining to inventory, personnel, orders, supplies, or machine maintenance.” (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 records of inventory, staff, orders and supplies is structured record-keeping that business systems already do.
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.
Computing figures, balances, totals or commissions
shifting to AI
This is reading one thing and writing another: figures, balances, totals or commissions in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Compute figures such as balances, totals, or commissions.” (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: Working out balances, totals and commissions is straightforward calculation from figures already in the system.
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.
Developing work schedules according to budgets and workloads
shifting to AI
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 · Supplemental
Source: “Develop work schedules according to budgets and workloads.” (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: Matching staff hours to budgets and workload is a scheduling calculation software does quickly and accurately.
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.
Reviewing records or reports pertaining
shifting to AI
This is reading one thing and writing another: records in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Review records or reports pertaining to activities such as production, payroll, or shipping to verify details, monitor work activities, or evaluate performance.” (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: Checking payroll, production and shipping records for errors and patterns is data work software handles 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.
Keeping informed of provisions of labor-management agreements and their effects on departmental operations
shifting to AI
This is reading one thing and writing another: informed of provisions of labor-management agreements in, a record out. That is the shape today's tools are built for.
importance 3 · Supplemental
Source: “Keep informed of provisions of labor-management agreements and their effects on departmental operations.” (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: Keeping up with labour agreements and what they mean for the department is reading and interpreting documents.
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 inventory levels and requisition or purchasing supplies
shifting to AI
This is reading one thing and writing another: inventory levels in, a record out. That is the shape today's tools are built for.
importance 3 · Supplemental
Source: “Monitor inventory levels and requisition or purchase supplies as needed.” (O*NET task statement)
How this row was scored
Exposure score: 69 out of 100 (62–76 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: Reordering when stock runs low is automatic in most systems, though someone occasionally checks the shelves.
The five ratings: output a model can produce 4/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Analyzing financial activities of establishments or departments and providing input into budget planning and preparation processes
shifting to AI
This is reading one thing and writing another: financial activities of establishments in, a record out. That is the shape today's tools are built for.
importance 4 · Supplemental
Source: “Analyze financial activities of establishments or departments and provide input into budget planning and preparation processes.” (O*NET task statement)
How this row was scored
Exposure score: 64 out of 100 (57–71 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: Analysing departmental spending and feeding into budget planning is number work software handles from existing finance data.
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.
Designing, implementing or evaluating staff training and development programs, customer service initiatives or performance measurement criteria
shifting to AI
This is reading one thing and writing another: staff in, a record out. That is the shape today's tools are built for.
importance 4 · Supplemental
Source: “Design, implement, or evaluate staff training and development programs, customer service initiatives, or performance measurement criteria.” (O*NET task statement)
How this row was scored
Exposure score: 64 out of 100 (57–71 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: Designing training programmes, service initiatives and performance measures is structured design work AI drafts 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 1/4 · how much data exists 3/4.
Planning layouts of stockrooms, warehouses or other storage areas, considering turnover, size, weight or related factors pertaining to items
changing shape
The software now makes the first pass at layouts of stockrooms, warehouses or other storage areas, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 2 · Supplemental
Source: “Plan layouts of stockrooms, warehouses, or other storage areas, considering turnover, size, weight, or related factors pertaining to items stored.” (O*NET task statement)
How this row was scored
Exposure score: 51 out of 100 (44–58 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; mistakes that are cheap to catch.
The rating behind it: Planning storage layouts from turnover, size and weight is a calculation, though you need to know the actual space.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Implementing corporate or departmental policies
changing shape
The software now makes the first pass at corporate, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · Core
Source: “Implement corporate or departmental policies, procedures, and service standards in conjunction with management.” (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: Writing and rolling out policies and service standards is document work AI drafts well, though people have to make it stick.
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.
Arranging for necessary maintenance or repairing work
changing shape
The software now makes the first pass at necessary maintenance, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 3 · Supplemental
Source: “Arrange for necessary maintenance or repair work.” (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: Booking in maintenance and repair work is scheduling and correspondence software handles, though access has to be arranged.
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.
Coordinating activities with other supervisory personnel or with other work units or departments
staying human
The value here is that a specific person handles activities and stands behind it. That is earned, not computed.
importance 4 · Core
Source: “Coordinate activities with other supervisory personnel or with other work units or departments.” (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: Coordinating with other departments means give and take between people who need to trust each other's commitments.
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.
Making recommendations to management concerning such issues as staffing decisions or procedural changes
staying human
The value here is that a specific person handles recommendations and stands behind it. That is earned, not computed.
importance 4 · Core
Source: “Make recommendations to management concerning such issues as staffing decisions or procedural changes.” (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: Recommending staffing or process changes carries weight because of who says it and how well they know the operation.
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.
Consulting with managers or other personnel to resolve problems in areas
staying human
The value here is that a specific person handles managers and stands behind it. That is earned, not computed.
importance 4 · Core
Source: “Consult with managers or other personnel to resolve problems in areas such as equipment performance, output quality, or work schedules.” (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: Sorting out equipment, quality or scheduling problems with other managers is a negotiation between people.
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 for or coordinating office services
staying human
The ratings behind this row put or coordinating office services well outside what today's tools can do on their own.
importance 3 · Supplemental
Source: “Plan for or coordinate office services, such as equipment or supply acquisition or organization, disposal of assets, relocation, parking, maintenance, or security services.” (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: Arranging office moves, parking, security and equipment involves suppliers and premises as well as planning.
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.
Coordinating or performing activities associated with shipping
staying human
This work happens in the physical world: activities, in a real place. Software cannot follow it there.
importance 3 · Supplemental
Source: “Coordinate or perform activities associated with shipping, receiving, distribution, or transportation.” (O*NET task statement)
How this row was scored
Exposure score: 29 out of 100 (22–36 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Shipping, receiving and distribution involve goods being physically handled as well as paperwork being coordinated.
The five ratings: output a model can produce 2/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Participating in the work of subordinates to facilitate productivity or to overcome difficult aspects of work
staying human
The value here is that a specific person handles the work of subordinates and stands behind it. That is earned, not computed.
importance 4 · Core
Source: “Participate in the work of subordinates to facilitate productivity or to overcome difficult aspects of work.” (O*NET task statement)
How this row was scored
Exposure score: 26 out of 100 (14–38 allowing for uncertainty): low exposure, low confidence.
Why it sits in this group: the value is that a specific person does it.
The rating behind it: Pitching in on the team's own work means doing whatever that work involves, alongside the people doing it.
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 2/4 · how much data exists 2/4.
Recruiting, interviewing and selecting employees
staying human
The value here is that a specific person handles employees and stands behind it. That is earned, not computed.
importance 4 · Core
Source: “Recruit, interview, and select employees.” (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 rests on judging people in interviews and persuading the right one to join.
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: $69,500a 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: 1,436,680in 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: figures, balances, totals or commissions in, a record out. The rows above are exactly that shape: computing figures, balances, totals or commissions and researching, compiling and preparing reports, manuals. What it cannot do is be trusted in person, which is what job performance problems run 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

Your week is splitting in two, and which half fills it is the whole question. Computing figures, balances, totals or commissions is going; discussing job performance problems with employees to identify causes and issues and to work on resolving problems is not.

So, given all that: 40% of this job's task weight sits in rows the software is already learning, 22% in rows that change shape rather than disappear, and 37% in rows it is nowhere near. That is the position, measured across 28 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 (discussing job performance problems with employees to identify causes and issues and to work on resolving problems) 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 discussing job performance problems with employees to identify causes and issues and to work on resolving problems, 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 office and administrative support 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 housekeeping and janitorial workers: only about 6% of its durable work is work you already do, it pays 29.4% less and there are far fewer of those jobs than of yours. Your own job splits about 40/60: 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 “discuss job performance problems with employees to identify causes and issues and…”, 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.

First-Line Supervisors of Housekeeping and Janitorial Workers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already interpret and communicate work procedures and company policies to staff, and their equivalent is to confer with staff to resolve performance and personnel problems, and to discuss company…. 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. It is a pay cut, in those words: $49,100 against your $69,500, 29.4% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice. And it is a narrow door: about 178,760 of those jobs against 1,436,680 of yours (OEWS May 2025), 12% as many seats.
Look at that job’s page anyway →
First-Line Supervisors of Production and Operating Workers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already interpret and communicate work procedures and company policies to staff, and their equivalent is to interpret specifications, blueprints, job orders, and company policies and procedures for workers. Across both published task lists that is about 5% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 5% of the durable side of that job. That is a different job, not a next step.
Look at that job’s page anyway →
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 resolve customer complaints or answer customers' questions regarding policies and procedures, and their equivalent is to resolve customer complaints regarding worker performance or services rendered. 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: $48,590 against your $69,500, 30.1% 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 1,436,680 of yours (OEWS May 2025), 8% as many seats.
Look at that job’s page anyway →

What I’d stop worrying about

A friend tells you what not to spend fear on. This is that list.

The headline number you read somewhere
The big “X% of jobs” figures are about the whole economy, not about you. The number that describes your job is on this page: 40% of its task weight, across 28 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 computing figures, balances, totals or commissions, 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 Customer service managers 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 Customer service managers, Customer service supervisors and Office 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

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:
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

A guided route for this

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

Microsoft 365 Productivity Workers is built for coordinators, administrators, team leads and project owners who live in Outlook, Teams, meetings, files and task lists (the people this page is about). It works on the part of your job that is growing rather than shrinking: running the team's schedules, queues and shared files as one system rather than a pile of separate trackers.

Try Microsoft 365 Productivity Workers 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 office supervisors 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 First-Line Supervisors of Office and Administrative Support Workers?: Not as a job, but it is already doing parts of the work. Across the 28 official task statements scored for First-Line Supervisors of Office and Administrative Support Workers (United States, SOC 43-1011), 40% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 52 out of 100 (range 46–59, 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 “First-Line Supervisors of Office and Administrative Support Workers” can AI already do?: The highest-scoring tasks in release 2026-q4.1 are: “Maintain records pertaining to inventory, personnel, orders, supplies, or machine maintenance” (93/100, very high); “Compute figures such as balances, totals, or commissions” (93/100, very high); “Develop work schedules according to budgets and workloads” (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 Office and Administrative Support Workers” stay human?: About 37% 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: “Recruit, interview, and select employees” (13/100, minimal); “Discuss job performance problems with employees to identify causes and issues and to work on resolving problems” (14/100, minimal); “Participate in the work of subordinates to facilitate productivity or to overcome difficult aspects of work” (26/100, low). 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 Office and Administrative Support Workers” do about AI?: Start from the ledger rather than the headline: 40% of this job's weighted core work is exposed, and roughly 37% 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 Office and Administrative Support 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 28 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

One row is marked low confidence, so treat it as a ballpark rather than a fine measurement.
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.

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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.