Online Merchants
In short: today's best AI models could do about 54% 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 80% by the end of 2028 if progress keeps its long-run pace. The conversations, in-person and hands-on work, about 20% of the time, stays with people.
Conduct retail activities of businesses operating exclusively online. May perform duties such as preparing business strategies, buying merchandise, managing inventory, implementing marketing activities, fulfilling and shipping online orders, and balancing financial records.
$83,050 a year (for the broader BLS group this job sits in).
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 on8 h
- A person checks AI's work14 h
- Desk work AI can't do yet10 h
- Stays with people8 h
Online Merchants, now: of a 40-hour week, AI could take on 8 hours, 14 hours become checking its work, 10 hours are desk work it can't do yet, and 8 hours stay with people.
The largest pieces: Research products and markets (about 3 h, a person checks); Maintain the customer database (about 2 h); Write the business plan (about 1 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.
- 58%
- 22%
- 11%
- 2%
- 7%
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 54% 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, 2%. With Claude Mythos Preview (early), measured in April 2026, 27%. Today's estimate: 54%.
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, 0.63% went to this job's tasks in May 2026, the 40th largest of the 447 jobs that showed up at all; 10 of its 34 tasks showed up. Within each of Anthropic's methods, never across a change: 0.21% to 0.2% (released February and March 2025); 0.17% to 0.29% (August 2025 to February 2026); 0.6% to 0.63% (April to May 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.21% | 87 of 708 | 18 of 34 |
| Released March 2025 | 0.2% | 88 of 703 | 17 of 34 |
| The week of Aug 4, 2025 (released September 2025) | 0.17% | 106 of 655 | 12 of 34 |
| The week of Nov 13, 2025 (released January 2026) | 0.23% | 73 of 672 | 19 of 34 |
| The week of Feb 5, 2026 (released March 2026) | 0.29% | 71 of 677 | 23 of 34 |
| April 2026 (released June 2026) | 0.6% | 42 of 434 | 9 of 34 |
| May 2026 (released June 2026) | 0.63% | 40 of 447 | 10 of 34 |
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 25% of this job's working time as physical work. For 20% of the working time, a robot has been shown doing most of the task somewhere: 18% in a purpose-built cell, 1% in a structured facility. 0.21 of 3, the 435th highest of the 923 jobs.
- Not physical 75%
- No robot shown 6%
- In a purpose-built cell 18%
- In a structured facility 1%
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
20% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Align online and physical retail, the conversation, 7%
- Answer customer questions and complaints, the conversation, 2%
- Find sources of stock, the in-person work, 2%
- Pack and ship orders, the hands-on work, 2%
- Photograph products, the hands-on work, 1%
- Work with search shopping specialists, the conversation, 1%
What becomes checking the machine
60% 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 20% is desk work that is small if wrong, which can be handed over with lighter checks.
- Write the business plan, costly if wrong, 11%
- Align online and physical retail, costly if wrong, 11%
- Research products and markets, costly if wrong, 10%
- Secure the store, severe if wrong, 7%
- Design the storefront, costly if wrong, 4%
- Publish terms and policies, costly if wrong, 3%
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 58% 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.
- Dealing with people outside the organization. Customers, patients, suppliers or the public: trust with them is built by a person.
- Judgment where errors are severe. Some tasks are severe if wrong. Knowing when not to trust an output matters more there than speed.
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 . 34 tasks from .
| Task | ||||
|---|---|---|---|---|
| Integrate online retailing strategy with physical or catalogue retailing operations.Planning on paper and coordination with the stores.Done more than monthly by most who do it. | 19% | 1.7 work days3.3 h to 1.3 work weeks | Documents 60%, conversation 40% | 14%Desk part half by May 2027 |
| Develop or revise business plans for online business, emphasizing factors such as product line, pricing, inventory, or marketing strategy.Writing at the desk.Done more than yearly by most who do it. AI observed on this task. | 11% | 1.7 work days3.3 h to 4.2 work days | Documents 100% | 31%Half by Mar 2027 |
| Investigate products or markets to determine areas for opportunity or viability for merchandising specific products, using online or offline sources.Research at the desk.Done more than monthly by most who do it. AI observed on this task. | 10% | 3.3 h50 min to 1.7 work days | Documents 100% | 71%Half by now |
| Implement security practices to preserve assets, minimize liabilities, or ensure customer privacy, using parallel servers, hardware redundancy, fail-safe technology, information encryption, or firewalls.Security set up in the systems, with the plan.Done more than yearly by most who do it. AI observed on this task. | 7% | 6.7 h1.7 h to 4.2 work days | Systems 70%, documents 30% | 40%Half by Jan 2027 |
| Create or distribute offline promotional material, such as brochures, pamphlets, business cards, stationary, or signage.Designing the pieces and handing them out.Done more than yearly by most who do it. | 4% | 2.5 h50 min to 1.3 work days | Documents 70%, hands-on 30% | 61%Desk part half by now |
| Investigate sources, such as auctions, estate sales, liquidators, wholesalers, or trade shows for new items, used items, or collectibles.Searching online and going to sales and shows.Done more than yearly by most who do it. | 4% | 3.3 h50 min to 1.7 work days | Documents 50%, in person 30%, hands-on 20% | 35%Desk part half by now |
| Design customer interface of online storefront, using web programming or e-commerce software.Design and setup in the platform.Done more than yearly by most who do it. AI observed on this task. | 4% | 6.7 h2.5 h to 3.3 work days | Documents 60%, systems 40% | 59%Half by now |
| Create or maintain database of customer accounts.Entries in the customer database.Done daily by most who do it. AI observed on this task. | 4% | 50 min13 min to 3.3 h | Systems 100% | 97%Half by now |
| Purchase new or used items from online or physical sources for resale via retail or auction Web site.Buying online and in person, with the sums worked.Done more than weekly by most who do it. Robots: no robot shown. Anthropic's rating. | 3% | 1.7 h25 min to 5 h | Systems 50%, hands-on 30%, documents 20% | 66%Desk part half by now |
| Disclose merchant information and terms and policies of transactions in online or offline materials.Writing the terms and putting them up.Done more than yearly by most who do it. | 3% | 1.3 h25 min to 3.3 h | Documents 100% | 99%Half by now |
| Compose images of products, using video or still cameras, lighting equipment, props, or photo or video editing software.Shooting the product and editing the images.Done more than yearly by most who do it. AI observed on this task.Robots: in a purpose-built cell, Orbitvu Alphashot 360 / Alphashot XL / Alphastudio XXL automated photo studios (sold). Anthropic's rating. | 3% | 50 min17 min to 2.5 h | Documents 50%, hands-on 50% | 50%Desk part half by now |
| Prepare or organize online storefront marketing material, including product descriptions or subject lines, optimizing content to search engine criteria.Writing and optimizing at the desk.Done more than monthly by most who do it. AI observed on this task. | 2% | 50 min17 min to 2.5 h | Documents 100% | 100%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.
- Marketing Managers30% now, 64% by 2028
- Sales Managers42% now, 43% by 2028
- Wholesale and Retail Buyers, Except Farm Products60% now, 62% by 2028
- Market Research Analysts and Marketing Specialists50% now, 93% by 2028
- Advertising Sales Agents56% now, 61% by 2028
- Advertising and Promotions Managers60% now, 85% by 2028
Where this job works
The industry groups that employ the most of it (BLS, May 2025). Counts are for the broader BLS group this job sits in.
Where the most of these jobs are
The metro areas with the most people in it (BLS, May 2025). Counts are for the broader BLS group this job sits in.
Questions about this job
- How much of the work of Online Merchants is within reach of AI now?
- An estimated 54% of the working time is within reach of AI models now and 80% by the end of 2028, on METR's long-run pace at four in five (75% to 80% across the three paces the site shows). 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 Online Merchants 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: Research products and markets (71% of the task's time now, 100% by the end of 2028); Maintain the customer database (97% of the task's time now); and Write the business plan (31% of the task's time now, 100% by the end of 2028).
- Which tasks of Online Merchants stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Answer customer questions and complaints. Together such tasks are about 2% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Online Merchants 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 20% of the working time stays with people, 60% becomes checking a model's work and 20% 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 Online Merchants?
- In the Claude.ai conversations Anthropic sampled for May 2026 and tied to a work task, 0.63% went to this job's tasks, the 40th largest share of the 447 jobs that showed up; 10 of its 34 tasks appeared. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 18%. 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 Online Merchants?
- Anthropic's robot exposure rating (September 2026) finds 25% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 20% of the working time, 1% in a structured facility. Its index is 0.21 of 3. One example: Gather AI drone inventory monitoring for "keep shipping supplies stocked". 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 34 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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