Receptionists and Information Clerks
In short: today's best AI models could do about 60% 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 40% of the time, stays with people.
Answer inquiries and provide information to the general public, customers, visitors, and other interested parties regarding activities conducted at establishment and location of departments, offices, and employees within the organization.
910,180 people do this job in the US. $38,010 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 on17 h
- A person checks AI's work7 h
- Desk work AI can't do yet0 h
- Stays with people16 h
Receptionists and Information Clerks, now: of a 40-hour week, AI could take on 17 hours, 7 hours become checking its work, 0 hours are desk work it can't do yet, and 16 hours stay with people.
The largest pieces: Do clerical support tasks (about 6 h, a person checks); Look into questions from the public (about 3 h); Schedule rooms and equipment (about 3 h).
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.
- 20%
- 39%
- 11%
- 10%
- 20%
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 60% 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, 11%. With Claude Mythos Preview (early), measured in April 2026, 58%. Today's estimate: 60%.
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, 0.38% went to this job's tasks in May 2026, the 68th largest of the 447 jobs that showed up at all; 5 of its 18 tasks showed up. Within each of Anthropic's methods, never across a change: 0.088% to 0.16% (released February and March 2025); 0.1% to 0.08% (August 2025 to February 2026); 0.4% to 0.38% (April to May 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.088% | 188 of 708 | 9 of 18 |
| Released March 2025 | 0.16% | 108 of 703 | 9 of 18 |
| The week of Aug 4, 2025 (released September 2025) | 0.1% | 153 of 655 | 5 of 18 |
| The week of Nov 13, 2025 (released January 2026) | 0.078% | 186 of 672 | 8 of 18 |
| The week of Feb 5, 2026 (released March 2026) | 0.08% | 193 of 677 | 7 of 18 |
| April 2026 (released June 2026) | 0.4% | 61 of 434 | 5 of 18 |
| May 2026 (released June 2026) | 0.38% | 68 of 447 | 5 of 18 |
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 17% of this job's working time as physical work. For 17% of the working time, a robot has been shown doing most of the task somewhere: 11% in a purpose-built cell, 6% in a structured facility. 0.22 of 3, the 420th highest of the 923 jobs.
- Not physical 83%
- In a purpose-built cell 11%
- In a structured facility 6%
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
40% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Keep the reception area tidy, the hands-on work, 6%
- Sort and distribute mail, the hands-on work, 6%
- Hear and resolve complaints, the in-person work, 5%
- Greet and direct visitors, the in-person work, 4%
- Take payment and record receipts, the hands-on work, 4%
- Run the switchboard, the conversation, 4%
What becomes checking the machine
17% 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 42% is desk work that is small if wrong, which can be handed over with lighter checks.
- Do clerical support tasks, costly if wrong, 15%
- Calculate and quote rates, costly if wrong, 3%
What to learn
- Running AI inside the business systems. About 39% 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.
- 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.
- The conversations. About 21% of the time is conversation and in-person work, which this site leaves with people: listening, explaining, persuading, calming.
- Briefing a model and checking its drafts. About 20% 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.
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 . 18 tasks from . One has a worked example.
| Task | ||||
|---|---|---|---|---|
| Perform administrative support tasks, such as proofreading, transcribing handwritten information, or operating calculators or computers to work with pay records, invoices, balance sheets, or other documents.Proofreading and typing up notes, and entering pay and invoice figures.Done hourly or more by most who do it. See it done: one graded attempt (passes with named fixes) | 15% | 25 min8 min to 1.3 h | Documents 50%, systems 50% | 100%Half by now |
| File and maintain records.Records kept in the system, with paper filed by hand.Done daily by most who do it. Robots: in a purpose-built cell, OPEX Falcon+ RED / Falcon+ / Velo production scanners with CertainScan (sold). Anthropic's rating. | 9% | 13 min4 min to 38 min | Systems 60%, hands-on 40% | 60%Desk part half by now |
| Analyze data to determine answers to questions from customers or members of the public.Finding the answer in the records and working it out.Done daily by most who do it. AI observed on this task. | 8% | 21 min8 min to 50 min | Documents 60%, systems 40% | 100%Half by now |
| Schedule space or equipment for special programs and prepare lists of participants.Bookings, and participant lists typed up.Done more than monthly by most who do it. | 6% | 33 min13 min to 1.7 h | Systems 70%, documents 30% | 100%Half by now |
| Perform duties, such as taking care of plants or straightening magazines to maintain lobby or reception area.Tidying by hand.Done daily by most who do it. Robots: in a structured facility, Figure F.03 humanoid with Helix 02 (demonstrated). Anthropic's rating. | 6% | 13 min4 min to 25 min | Hands-on 100% | Stays with people |
| Receive payment and record receipts for services.Handling the payment at the desk, and recording the receipt.Done hourly or more by most who do it. Robots: in a structured facility, Clearwave patient check-in kiosk (deployed). Anthropic's rating. | 6% | 7 min3 min to 17 min | Hands-on 50%, systems 30%, in person 20% | 30%Desk part half by now |
| Collect, sort, distribute, or prepare mail, messages, or courier deliveries.Handling mail and deliveries.Done daily by most who do it. Robots: in a purpose-built cell, AmbiSort A-Series / B-Series (deployed). Anthropic's rating. | 6% | 17 min8 min to 50 min | Hands-on 100% | Stays with people |
| Operate telephone switchboard to answer, screen, or forward calls, providing information, taking messages, or scheduling appointments.Live calls, with messages and bookings entered.Done hourly or more by most who do it. AI observed on this task. | 6% | 4 min2 min to 13 min | Conversation 70%, systems 30% | 30%Desk part half by now |
| Process and prepare memos, correspondence, travel vouchers, or other documents.Document work, with forms entered.Done daily by most who do it. AI observed on this task. | 6% | 17 min8 min to 38 min | Documents 60%, systems 40% | 100%Half by now |
| Calculate and quote rates for tours, stocks, insurance policies, or other products or services.Working out the rate, and telling the customer.Done hourly or more by most who do it. | 5% | 13 min4 min to 38 min | Documents 50%, conversation 50% | 50%Desk part half by now |
| Hear and resolve complaints from customers or the public.Conversation at the desk and on the phone.Done daily by most who do it. AI observed on this task. | 5% | 13 min4 min to 38 min | In person 60%, conversation 40% | Stays with people |
| Keep a current record of staff members' whereabouts and availability.Entries on the in-and-out board.Done daily by most who do it. | 5% | 13 min4 min to 25 min | Systems 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.
- Medical Secretaries and Administrative Assistants84% now, 84% by 2028
- Office Clerks, General56% now, 56% by 2028
- Customer Service Representatives64% now, 64% by 2028
- Secretaries and Administrative Assistants, Except Legal, Medical, and Executive59% now, 68% by 2028
- Switchboard Operators, Including Answering Service77% now, 77% by 2028
- Interviewers, Except Eligibility and Loan50% now, 50% 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 Receptionists and Information Clerks is within reach of AI now?
- An estimated 60% of the working time is within reach of AI models now and 60% 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 Receptionists and Information 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: Do clerical support tasks (100% of the task's time now); Look into questions from the public (100% of the task's time now); and Schedule rooms and equipment (100% of the task's time now).
- Which tasks of Receptionists and Information Clerks stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Keep the reception area tidy; Sort and distribute mail; and Hear and resolve complaints. Together such tasks are about 23% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Receptionists and Information 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 running AI inside the business systems; dealing with people outside the organization; and reviewing work you did not do yourself. By the end of 2028 on the long-run pace at four in five, about 40% of the working time stays with people, 17% becomes checking a model's work and 42% 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 Receptionists and Information Clerks?
- In the Claude.ai conversations Anthropic sampled for May 2026 and tied to a work task, 0.38% went to this job's tasks, the 68th largest share of the 447 jobs that showed up; 5 of its 18 tasks appeared. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 43%. 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 Receptionists and Information Clerks?
- Anthropic's robot exposure rating (September 2026) finds 17% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 17% of the working time, 6% in a structured facility. Its index is 0.22 of 3. One example: Figure F.03 humanoid with Helix 02 for "keep the reception area tidy". 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 18 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. The Work Bench has 1 worked example of its tasks: a brief, a rubric written beforehand, one attempt by an AI model and its grade.
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