Postal Service Mail Sorters, Processors, and Processing Machine Operators
In short: today's best AI models could do about 1% 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 the same by the end of 2028 if progress keeps its long-run pace. The conversations, in-person and hands-on work, about 99% of the time, stays with people.
Prepare incoming and outgoing mail for distribution for the United States Postal Service (USPS). Examine, sort, and route mail. Load, operate, and occasionally adjust and repair mail processing, sorting, and canceling machinery. Keep records of shipments, pouches, and sacks, and perform other duties related to mail handling within the postal service. Includes postal service mail sorters and processors employed by USPS contractors.
105,200 people do this job in the US. $58,470 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 on0 h
- A person checks AI's work0 h
- Desk work AI can't do yet0 h
- Stays with people40 h
Postal Service Mail Sorters, Processors, and Processing Machine Operators, now: of a 40-hour week, AI could take on 0 hours, 0 hours become checking its work, 0 hours are desk work it can't do yet, and 40 hours stay with people.
The largest pieces: Look up addresses for redirected mail (under an hour).
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.
- 0%
- 1%
- 0%
- 11%
- 88%
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 1% 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, 0%. With Claude Mythos Preview (early), measured in April 2026, 1%. Today's estimate: 1%.
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
None of this job's 14 tasks showed up in the Claude.ai conversations Anthropic sampled in any of its 7 releases, from February 2025 to May 2026.
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 98% of this job's working time as physical work. For 92% of the working time, a robot has been shown doing most of the task somewhere: 69% in a purpose-built cell, 23% in a structured facility. 1.14 of 3, the 69th highest of the 923 jobs.
- Not physical 2%
- No robot shown 6%
- In a purpose-built cell 69%
- In a structured facility 23%
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
99% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Operate processing equipment, the hands-on work, 29%
- Sort odd mail by hand, the hands-on work, 11%
- Train new workers, the in-person work, 11%
- Key routing at the sorter, the hands-on work, 11%
- Bundle and route sorted mail, the hands-on work, 8%
- Clear equipment jams, the hands-on work, 7%
What becomes checking the machine
No desk work within reach by then in tasks where a mistake costs something.
What to learn
- The hands-on craft. About 88% of the time is hands-on work, which no model here does; robots are rated separately on this page.
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 . 14 tasks from .
| Task | ||||
|---|---|---|---|---|
| Operate various types of equipment, such as computer scanning equipment, addressographs, mimeographs, optical character readers, and bar-code sorters.Scanners, readers and sorters run.Done hourly or more by most who do it. Robots: in a purpose-built cell, AFSM 100 Automatic Induction (AI) enhancement (USPS / Northrop Grumman) (deployed). Anthropic's rating. | 29% | 50 min13 min to 1.7 h | Hands-on 100% | Stays with people |
| Sort odd-sized mail by hand, sort mail that other workers have been unable to sort, and segregate items requiring special handling.Hand sorting of what the machines cannot.Done daily by most who do it. Robots: in a purpose-built cell, Parcel Robotic Sortation System (PRSS), Topeka MDC (USPS Engineering Systems) (deployed). Anthropic's rating. | 11% | 29 min13 min to 50 min | Hands-on 100% | Stays with people |
| Train new workers.Training on the floor.Done more than yearly by most who do it. | 11% | 3.3 h50 min to 6.7 h | In person 100% | Stays with people |
| Direct items according to established routing schemes, using computer-controlled keyboards or voice-recognition equipment.Keying codes as the mail passes.Done hourly or more by most who do it.Robots: in a purpose-built cell, Parallel Induction Linear Sorter (PILS) / Matrix East-West Sorter (MEWS) (USPS with Intralox) (deployed). Anthropic's rating. | 11% | 38 min8 min to 1.3 h | Hands-on 100% | Stays with people |
| Bundle, label, and route sorted mail to designated areas, depending on destinations and according to established procedures and deadlines.Mail bundled and sent to its area.Done daily by most who do it.Robots: in a purpose-built cell, TOP 2000 flat sorter with Soly tray-handling robots (Solystic) (sold). Anthropic's rating. | 8% | 25 min8 min to 50 min | Hands-on 100% | Stays with people |
| Clear jams in sorting equipment.Jams cleared by hand.Done hourly or more by most who do it. Robots: no robot shown. Anthropic's rating. | 7% | 13 min4 min to 38 min | Hands-on 100% | Stays with people |
| Check items to ensure that addresses are legible and correct, that sufficient postage has been paid or the appropriate documentation is attached, and that items are in a suitable condition for processing.Items looked over for address, postage and condition.Done daily by most who do it.Robots: in a structured facility, USPS letter automation OCR / Remote Computer Reader (United States Postal Service) (deployed). Anthropic's rating. | 6% | 17 min8 min to 42 min | Hands-on 100% | Stays with people |
| Load and unload mail trucks, sometimes lifting containers of mail onto equipment that transports items to sorting stations.Containers lifted on and off.Done daily by most who do it.Robots: in a structured facility, Pickle Unload System (Dill) (deployed). Anthropic's rating. | 5% | 38 min13 min to 1.3 h | Hands-on 100% | Stays with people |
| Open and label mail containers.Containers opened and labeled.Done hourly or more by most who do it.Robots: in a purpose-built cell, Videojet print-and-apply labelers (pallet/case labeling systems) (sold). Anthropic's rating. | 4% | 10 min4 min to 21 min | Hands-on 100% | Stays with people |
| Distribute incoming mail into the correct boxes or pigeonholes.Mail put into boxes and pigeonholes.Done daily by most who do it.Robots: in a purpose-built cell, Delivery Bar Code Sorter (DBCS) (USPS) (deployed). Anthropic's rating. | 3% | 25 min13 min to 1.7 h | Hands-on 100% | Stays with people |
| Move containers of mail, using equipment, such as forklifts and automated "trains".Forklifts and trains on the floor, which take a certified operator.Done daily by most who do it.Robots: in a structured facility, USPS Automated Guided Vehicles (AGV program) (U.S. Postal Service) (deployed). Anthropic's rating. | 3% | 17 min7 min to 38 min | Hands-on 100% | Stays with people |
| Cancel letter or parcel post stamps by hand.Stamps canceled.Done more than weekly by most who do it.Robots: in a purpose-built cell, Advanced Facer Canceller System 200 (AFCS 200) / AFCS-OCR (United States Postal Service) (deployed). Anthropic's rating. | 1% | 13 min4 min to 38 min | Hands-on 100% | Stays with people |
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.
- Mail Clerks and Mail Machine Operators, Except Postal Service13% now, 13% by 2028
- Shipping, Receiving, and Inventory Clerks53% now, 53% by 2028
- Postal Service Clerks19% now, 19% by 2028
- Stockers and Order Fillers19% now, 19% by 2028
- Office Machine Operators, Except Computer11% now, 11% by 2028
- Weighers, Measurers, Checkers, and Samplers, Recordkeeping30% now, 30% 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 Postal Service Mail Sorters, Processors, and Processing Machine Operators is within reach of AI now?
- An estimated 1% of the working time is within reach of AI models now and 1% 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 Postal Service Mail Sorters, Processors, and Processing Machine Operators 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: Look up addresses for redirected mail (100% of the task's time now).
- Which tasks of Postal Service Mail Sorters, Processors, and Processing Machine Operators stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Operate processing equipment; Sort odd mail by hand; and Train new workers. Together such tasks are about 99% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Postal Service Mail Sorters, Processors, and Processing Machine Operators learn as AI takes on more of the work?
- By the job's own task-by-task review, the first things to learn are the hands-on craft. By the end of 2028 on the long-run pace at four in five, about 99% of the working time stays with people, 0% becomes checking a model's work and 1% 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 Postal Service Mail Sorters, Processors, and Processing Machine Operators?
- In the Claude.ai conversations Anthropic sampled for May 2026, no reportable share went to this job's tasks. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 0%. 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 Postal Service Mail Sorters, Processors, and Processing Machine Operators?
- Anthropic's robot exposure rating (September 2026) finds 98% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 92% of the working time, 23% in a structured facility. Its index is 1.14 of 3. One example: USPS letter automation OCR / Remote Computer Reader for "check addresses and postage". A robot shown somewhere is not one in every workplace; this site's own estimates still count no physical work as within reach.
- How is this estimated?
- From the 14 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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