Production, Planning, and Expediting Clerks
In short: today's best AI models could do about 72% of this job's working time (projected from METR's April 2026 measurement and Epoch's November 2026 index) if the work were set up for them, and about 73% by the end of 2028 if progress keeps its long-run pace. The conversations, in-person and hands-on work, about 27% of the time, stays with people.
Coordinate and expedite the flow of work and materials within or between departments of an establishment according to production schedule. Duties include reviewing and distributing production, work, and shipment schedules; conferring with department supervisors to determine progress of work and completion dates; and compiling reports on progress of work, inventory levels, costs, and production problems.
390,160 people do this job in the US. $59,650 a year.
Reviewed on September 30, 2026: what each task is made of, and what handing it over would ask.
A typical 40-hour week
- AI could take on2 h
- A person checks AI's work27 h
- Desk work AI can't do yet0 h
- Stays with people11 h
Production, Planning, and Expediting Clerks, now: of a 40-hour week, AI could take on 2 hours, 27 hours become checking its work, 0 hours are desk work it can't do yet, and 11 hours stay with people.
The largest pieces: Plan production timetables (about 7 h, a person checks); Compile status report data (about 3 h, a person checks); Write build instructions and projections (about 3 h, a person checks).
Estimates for a typical week of this job, if progress keeps its long-run pace, counting work the best models finish four times in five. Every task is below.
of the working time. Now is projected from METR's April 2026 measurement and Epoch's November 2026 index.
- 51%
- 22%
- 20%
- 2%
- 5%
of the work: Anthropic's measure of what people already bring to Claude at work (2025). It counts help with part of a task, so it can be higher than the share within reach.
On the chosen pace and reliability. Estimate.
Share of the working time within reach, now to 2030
Change assumptionsHide assumptionsLong-run pace, four in five
What each choice means: , , , , . Every pace starts from .
At this date and pace, models finish tasks up to 2.4 work days long four times in five.
What handing it over would take, now
The 72% within reach splits by what a model would need. The dates, pace and reliability follow the controls above. Estimates.
of the working time. The material can be handed to a model and the result handed back.
of the working time. The model has to be connected to the system the work lives in.
is conversation short enough by length. This site leaves conversation with people, so it is not in the total.
How far this has come
With GPT-4, measured in March 2023, 0% of this job's working time was within reach at . With Claude 3.7 Sonnet, measured in February 2025, 1%. With Claude Mythos Preview (early), measured in April 2026, 43%. Today's estimate: 72%.
A backcast: today's task data with the best model METR had measured by each date. It shows how fast the models have moved, not what anyone forecast at the time.
Measured use over time
Of the Claude.ai conversations Anthropic sampled and tied to a work task, 0.17% went to this job's tasks in May 2026, the 115th largest of the 447 jobs that showed up at all; 3 of its 17 tasks showed up. Within each of Anthropic's methods, never across a change: 0.055% to 0.026% (released February and March 2025); 0.021% to 0.014% (August 2025 to February 2026); 0.16% to 0.17% (April to May 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.055% | 262 of 708 | 5 of 17 |
| Released March 2025 | 0.026% | 384 of 703 | 3 of 17 |
| The week of Aug 4, 2025 (released September 2025) | 0.021% | 364 of 655 | 3 of 17 |
| The week of Nov 13, 2025 (released January 2026) | 0.0094% | 487 of 672 | 2 of 17 |
| The week of Feb 5, 2026 (released March 2026) | 0.014% | 441 of 677 | 4 of 17 |
| April 2026 (released June 2026) | 0.16% | 118 of 434 | 2 of 17 |
| May 2026 (released June 2026) | 0.17% | 115 of 447 | 3 of 17 |
Measured, not estimated: Anthropic's samples of Claude.ai conversations, each tied by a model to an O*NET task, from the Anthropic Economic Index. It says where Claude's use goes, not how much of this job's working time it covers, so it is not on the same scale as the reach above. The releases differ in their sample, their classifier and the smallest share they report (the June 2026 file rounds each task to a hundredth of a percent, so a smaller task reads as none), which is why a change of method starts a new line. At least 96% of each older release's task-tied use matched this site's tasks, and all of the newest. Claude.ai only, so use through other tools and other companies' models is not in it. Every job ranked.
Robots and the physical work
Anthropic rates almost none of this job's working time as physical work, so robots do not reach it.
Anthropic's rating, not this site's estimate: Claude Opus 5, searching the web, rated each physical O*NET task by the kind of setting in which a robot it could cite (deployed, sold or demonstrated) does most of the task, weighted by its own estimate of each task's share of the time (What work can robots do?, September 30, 2026, data CC BY 4.0; every job ranked). A robot shown somewhere is not a robot in your building: cost, setup and safety decide that. The share within reach on this page still counts no body work. The robot behind each rated task is under the task below.
What changes for the people in this job
From the task-by-task review, by the end of 2028 on the long-run pace at four in five. It says which parts of the work stay with people and which change, not whether anyone keeps a job: that depends on decisions no data set can see.
What stays with people
26% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Coordinate with vendors and customers, the conversation, 6%
- Revise production schedules, the conversation, 5%
- Expedite supplies and parts, the conversation, 5%
- Check progress with supervisors, the conversation, 5%
- Check work and materials against standards, the hands-on work, 2%
- Requisition and track materials, the hands-on work, 2%
What becomes checking the machine
68% of the working time: desk work a model could do by then, in tasks where a mistake costs something or a licensed person signs. A person checks it. Another 5% is desk work that is small if wrong, which can be handed over with lighter checks.
- Plan production timetables, costly if wrong, 19%
- Compile status report data, costly if wrong, 8%
- Write build instructions and projections, costly if wrong, 8%
- Prepare production documentation, costly if wrong, 6%
- Revise production schedules, costly if wrong, 5%
- Work out material and staffing needs, costly if wrong, 5%
What to learn
- Reviewing work you did not do yourself. The tasks under What becomes checking the machine, where a mistake costs something, stay a person's to check: spotting what a draft gets wrong is a skill of its own.
- Briefing a model and checking its drafts. About 51% of the time is documents and data, the part models reach first: writing a clear brief, giving the right material, and checking what comes back.
- Running AI inside the business systems. About 22% of the time is work inside business systems, which a model can do only once it is connected: knowing the systems well enough to set that up and watch it.
- The conversations. About 21% of the time is conversation and in-person work, which this site leaves with people: listening, explaining, persuading, calming.
Your own version of this job: read it against your job description. The headline is free; the full personal report, every task with its timeline and what to learn, is $19 (a sample).
The tasks
Sorted by . 17 tasks from .
| Task | ||||
|---|---|---|---|---|
| Plan production commitments or timetables for business units, specific programs, or jobs, using sales forecasts.Working the forecast into a production plan.Done daily by most who do it. | 19% | 2.5 h50 min to 6.7 h | Documents 100% | 96%Half by now |
| Revise production schedules when required due to design changes, labor or material shortages, backlogs, or other interruptions, collaborating with management, marketing, sales, production, or engineering.Reworking the schedule and agreeing the changes with the departments.Done daily by most who do it. | 11% | 1.3 h25 min to 3.3 h | Documents 50%, conversation 50% | 50%Desk part half by now |
| Arrange for delivery, assembly, or distribution of supplies or parts to expedite flow of materials and meet production schedules.Orders and calls to get the parts where they are needed.Done daily by most who do it. | 10% | 50 min17 min to 2.1 h | Systems 50%, conversation 50% | 50%Desk part half by now |
| Compile information, such as production rates and progress, materials inventories, materials used, or customer information, so that status reports can be completed.Pulling the figures from the systems and putting them together.Done daily by most who do it. | 8% | 1.3 h25 min to 3.3 h | Documents 60%, systems 40% | 99%Half by now |
| Establish and prepare product construction directions and locations and information on required tools, materials, equipment, numbers of workers needed, and cost projections.Setting out how the product is built, what it takes, and what it costs.Done daily by most who do it. | 8% | 3.3 h1.3 h to 6.7 h | Documents 100% | 98%Half by now |
| Requisition and maintain inventories of materials or supplies necessary to meet production demands.Entries and requisitions, with checks on the stock.Done daily by most who do it. | 7% | 50 min17 min to 2.5 h | Systems 70%, hands-on 30% | 70%Desk part half by now |
| Compile and prepare documentation related to production sequences, transportation, personnel schedules, or purchase, maintenance, or repair orders.Writing up sequences and orders from the system.Done daily by most who do it. | 6% | 1.3 h25 min to 2.8 h | Documents 60%, systems 40% | 100%Half by now |
| Confer with establishment personnel, vendors, or customers to coordinate production or shipping activities and to resolve complaints or eliminate delays.Calls and emails to keep orders moving and settle complaints.Done daily by most who do it. | 6% | 38 min13 min to 1.7 h | Conversation 100% | Stays with people |
| Review documents, such as production schedules, work orders, or staffing tables, to determine personnel or materials requirements or material priorities.Reading the schedules and orders to set requirements and priorities.Done daily by most who do it. | 5% | 38 min17 min to 1.7 h | Documents 100% | 100%Half by now |
| Confer with department supervisors or other personnel to assess progress and discuss needed changes.Conversations with the supervisors, some on the floor.Done daily by most who do it. | 5% | 25 min13 min to 1.1 h | Conversation 60%, in person 40% | Stays with people |
| Examine documents, materials, or products and monitor work processes to assess completeness, accuracy, and conformance to standards and specifications.Looking at the product and the process on the floor, and the paperwork.Done daily by most who do it. AI observed on this task. | 4% | 50 min17 min to 2.5 h | Hands-on 60%, documents 40% | 40%Desk part half by now |
| Distribute production schedules or work orders to departments.Sending the schedules out through the system, some printed.Done daily by most who do it. | 3% | 17 min8 min to 38 min | Systems 80%, hands-on 20% | 80%Desk part half by now |
Within reach, per task: the share of the task's time whose instances are short enough for a model to finish at the chosen date, pace and reliability. Half by: the date half of that time comes within reach. Made of: how the task's time splits among five kinds of doing. Only the documents and systems parts can count as within reach, so a task that is 30% documents can be at most 30% within reach.
Jobs that share skills with this one
From O*NET's related occupations. Within reach now and by the end of 2028, long-run pace, four in five.
- Project Management Specialists58% now, 65% by 2028
- Shipping, Receiving, and Inventory Clerks53% now, 53% by 2028
- First-Line Supervisors of Helpers, Laborers, and Material Movers, Hand33% now, 34% by 2028
- First-Line Supervisors of Production and Operating Workers48% now, 54% by 2028
- Weighers, Measurers, Checkers, and Samplers, Recordkeeping30% now, 30% by 2028
- First-Line Supervisors of Office and Administrative Support Workers54% now, 58% by 2028
Where this job works
The industry groups that employ the most of it (BLS, May 2025).
Where the most of these jobs are
The metro areas with the most people in it (BLS, May 2025).
Questions about this job
- How much of the work of Production, Planning, and Expediting Clerks is within reach of AI now?
- An estimated 72% of the working time is within reach of AI models now and 73% by the end of 2028, on METR's long-run pace at four in five. Within reach means a model could finish work that long at that reliability. It is not a forecast of jobs lost or of savings.
- Which tasks of Production, Planning, and Expediting Clerks come within reach first?
- Weighted by the time each takes, the tasks with the most within reach now (projected from METR's April 2026 measurement and Epoch's November 2026 index) are: Plan production timetables (96% of the task's time now); Compile status report data (99% of the task's time now); and Write build instructions and projections (98% of the task's time now).
- Which tasks of Production, Planning, and Expediting Clerks stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Coordinate with vendors and customers; Check progress with supervisors; and Check shipments with suppliers. Together such tasks are about 11% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Production, Planning, and Expediting Clerks learn as AI takes on more of the work?
- By the job's own task-by-task review, the first things to learn are reviewing work you did not do yourself; briefing a model and checking its drafts; and running AI inside the business systems. By the end of 2028 on the long-run pace at four in five, about 26% of the working time stays with people, 68% becomes checking a model's work and 5% could be handed over with lighter checks. It says which parts of the work change, never whether anyone keeps a job.
- Do people already use AI for the work of Production, Planning, and Expediting Clerks?
- In the Claude.ai conversations Anthropic sampled for May 2026 and tied to a work task, 0.17% went to this job's tasks, the 115th largest share of the 447 jobs that showed up; 3 of its 17 tasks appeared. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 9%. These are measures of use, not of how much of the work AI could finish, and they cover Claude only.
- Can robots do the physical work of Production, Planning, and Expediting Clerks?
- Anthropic's robot exposure rating (September 2026) finds almost none of the working time is physical work, so robots do not reach it.
- How is this estimated?
- From the 17 tasks O*NET lists for the occupation, each with an estimated length checked against GDPval and a share of the working time, reviewed one task at a time on September 30, 2026 for what each is made of (documents, business systems, conversation, in person, hands-on), and METR's measurements of how long a task the best AI models can finish, carried forward to the date from the latest, Claude Mythos Preview (early) in April 2026. Data checked November 10, 2026.
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