First-Line Supervisors of Retail Sales Workers
In short: today's best AI models could do about 49% 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 51% by the end of 2028 if progress keeps its long-run pace. The conversations, in-person and hands-on work, about 49% of the time, stays with people.
Directly supervise and coordinate activities of retail sales workers in an establishment or department. Duties may include management functions, such as purchasing, budgeting, accounting, and personnel work, in addition to supervisory duties.
1,121,800 people do this job in the US. $48,520 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 work18 h
- Desk work AI can't do yet0 h
- Stays with people20 h
First-Line Supervisors of Retail Sales Workers, now: of a 40-hour week, AI could take on 2 hours, 18 hours become checking its work, 0 hours are desk work it can't do yet, and 20 hours stay with people.
The largest pieces: Establish credit policies and procedures (about 4 h, a person checks); Plan budgets and authorize payments (about 3 h, a person checks); Formulate pricing policies (about 2 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.
- 43%
- 8%
- 2%
- 29%
- 18%
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 49% 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, 20%. Today's estimate: 49%.
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, 0.037% went to this job's tasks in May 2026, the 252nd largest of the 447 jobs that showed up at all; 3 of its 21 tasks showed up. Within each of Anthropic's methods, never across a change: 0.045% to 0.039% (released February and March 2025); 0.064% to 0.08% (August 2025 to February 2026); 0.04% to 0.037% (April to May 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.045% | 291 of 708 | 8 of 21 |
| Released March 2025 | 0.039% | 307 of 703 | 5 of 21 |
| The week of Aug 4, 2025 (released September 2025) | 0.064% | 205 of 655 | 4 of 21 |
| The week of Nov 13, 2025 (released January 2026) | 0.065% | 205 of 672 | 8 of 21 |
| The week of Feb 5, 2026 (released March 2026) | 0.08% | 194 of 677 | 8 of 21 |
| April 2026 (released June 2026) | 0.04% | 244 of 434 | 3 of 21 |
| May 2026 (released June 2026) | 0.037% | 252 of 447 | 3 of 21 |
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 26% of this job's working time as physical work. For 14% of the working time, a robot has been shown doing most of the task somewhere: 5% in a purpose-built cell, 9% in a structured facility. 0.23 of 3, the 416th highest of the 923 jobs.
- Not physical 74%
- No robot shown 13%
- In a purpose-built cell 5%
- In a structured facility 9%
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
49% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Monitor service on the sales floor, the in-person work, 7%
- Work the floor alongside staff, the hands-on work, 6%
- Direct and supervise sales employees, the in-person work, 6%
- Hire, train and evaluate staff, the in-person work, 4%
- Set department policies and goals, the in-person work, 4%
- Check merchandise pricing and display, the hands-on work, 3%
What becomes checking the machine
46% 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.
- Establish credit policies and procedures, costly if wrong, 9%
- Plan budgets and authorize payments, costly if wrong, 7%
- Formulate pricing policies, costly if wrong, 6%
- Estimate demand and decide what to stock, costly if wrong, 5%
- Set department policies and goals, costly if wrong, 5%
- Plan promotions and prepare displays, costly if wrong, 4%
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 43% 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.
- The conversations. About 31% of the time is conversation and in-person work, which this site leaves with people: listening, explaining, persuading, calming.
- The hands-on craft. About 18% of the time is hands-on work, which no model here does; robots are rated separately on this page.
- Dealing with people outside the organization. Customers, patients, suppliers or the public: trust with them is built by a person.
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 . 21 tasks from .
| Task | ||||
|---|---|---|---|---|
| Establish credit policies and operating procedures.Writing policy.Done daily by most who do it. | 9% | 2.5 h50 min to 6.7 h | Documents 100% | 96%Half by now |
| Establish and implement policies, goals, objectives, and procedures for the department.Writing the policy, and putting it to the crew in person.Done daily by most who do it. | 9% | 2.5 h50 min to 6.7 h | Documents 60%, in person 40% | 57%Desk part half by now |
| Direct and supervise employees engaged in sales, inventory-taking, reconciling cash receipts, or in performing services for customers.Leading a crew on the store floor.Done daily by most who do it. | 7% | 38 min13 min to 1.7 h | In person 80%, documents 20% | 20%Desk part half by now |
| Monitor sales activities to ensure that customers receive satisfactory service and quality goods.Being on the floor to watch and step in.Done daily by most who do it. AI observed on this task. | 7% | 38 min13 min to 1.7 h | In person 60%, hands-on 40% | Stays with people |
| Plan budgets and authorize payments and merchandise returns.Budget work on paper, and approvals in the system.Done more than monthly by most who do it. | 7% | 3.3 h50 min to 6.7 h | Documents 60%, systems 40% | 91%Half by now |
| Hire, train, and evaluate personnel in sales or marketing establishments, promoting or firing workers when appropriate.Interviews, coaching and reviews in person, with the write-ups.Done more than yearly by most who do it. | 6% | 3.3 h1.3 h to 1 work day | In person 60%, documents 40% | 38%Desk part half by now |
| Perform work activities of subordinates, such as cleaning and organizing shelves and displays and selling merchandise.Stocking, tidying and selling in person.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 6% | 50 min13 min to 2.5 h | Hands-on 60%, in person 40% | Stays with people |
| Plan and coordinate advertising campaigns and sales promotions and prepare merchandise displays and advertising copy.Planning and writing copy, and building displays by hand.Done more than weekly by most who do it. AI observed on this task.Robots: in a purpose-built cell, Comau/Siscodata robotic co-packing line at Number1 Logistics Group (deployed). Anthropic's rating. | 6% | 4.2 h1.7 h to 1 work day | Documents 70%, hands-on 30% | 68%Desk part half by now |
| Formulate pricing policies for merchandise, according to profitability requirements.Analysis of margins and prices on paper.Done daily by most who do it. | 6% | 1.7 h38 min to 3.3 h | Documents 100% | 100%Half by now |
| Estimate consumer demand and determine the types and amounts of goods to be sold.Analysis of sales and demand.Done daily by most who do it. | 5% | 2.5 h50 min to 5 h | Documents 100% | 99%Half by now |
| Review inventory and sales records to prepare reports for management and budget departments.Pulling the records and writing the report.Done daily by most who do it. | 4% | 2.1 h50 min to 4.2 h | Documents 70%, systems 30% | 100%Half by now |
| Inventory stock and reorder when inventory drops to a specified level.Counting on the floor and in the stockroom, then the order entry.Done daily by most who do it. Robots: in a structured facility, Tally (Simbe Robotics) (deployed). Anthropic's rating. | 4% | 1.3 h25 min to 2.5 h | Hands-on 80%, systems 20% | 20%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.
- First-Line Supervisors of Non-Retail Sales Workers46% now, 49% by 2028
- First-Line Supervisors of Office and Administrative Support Workers54% now, 58% by 2028
- First-Line Supervisors of Food Preparation and Serving Workers48% now, 48% by 2028
- First-Line Supervisors of Entertainment and Recreation Workers, Except Gambling Services27% now, 28% by 2028
- First-Line Supervisors of Housekeeping and Janitorial Workers43% now, 44% by 2028
- Sales Representatives of Services, Except Advertising, Insurance, Financial Services, and Travel59% now, 60% 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 First-Line Supervisors of Retail Sales Workers is within reach of AI now?
- An estimated 49% of the working time is within reach of AI models now and 51% 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 First-Line Supervisors of Retail Sales Workers 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: Establish credit policies and procedures (96% of the task's time now); Plan budgets and authorize payments (91% of the task's time now, 100% by the end of 2028); and Formulate pricing policies (100% of the task's time now).
- Which tasks of First-Line Supervisors of Retail Sales Workers stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Monitor service on the sales floor; Work the floor alongside staff; and Check merchandise pricing and display. Together such tasks are about 28% of the working time, and the people and body parts of the other tasks stay with people too.
- What should First-Line Supervisors of Retail Sales Workers 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 the conversations. By the end of 2028 on the long-run pace at four in five, about 49% of the working time stays with people, 46% 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 First-Line Supervisors of Retail Sales Workers?
- In the Claude.ai conversations Anthropic sampled for May 2026 and tied to a work task, 0.037% went to this job's tasks, the 252nd largest share of the 447 jobs that showed up; 3 of its 21 tasks appeared. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 26%. 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 First-Line Supervisors of Retail Sales Workers?
- Anthropic's robot exposure rating (September 2026) finds 26% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 14% of the working time, 9% in a structured facility. Its index is 0.23 of 3. One example: Tally (Simbe Robotics) for "count stock and reorder". 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 21 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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