Customer Service Representatives
In short: today's best AI models could do about 64% 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 36% of the time, stays with people.
Interact with customers to provide basic or scripted information in response to routine inquiries about products and services. May handle and resolve general complaints. Excludes individuals whose duties are primarily installation, sales, repair, and technical support.
2,595,750 people do this job in the US. $44,770 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 on8 h
- A person checks AI's work18 h
- Desk work AI can't do yet0 h
- Stays with people14 h
Customer Service Representatives, now: of a 40-hour week, AI could take on 8 hours, 18 hours become checking its work, 0 hours are desk work it can't do yet, and 14 hours stay with people.
The largest pieces: Investigate the validity of complaints (about 4 h, a person checks); Complete contract and account forms (about 4 h, a person checks); Check that fixes were made (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.
- 18%
- 46%
- 35%
- 0%
- 1%
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 64% 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, 14%. With Claude Mythos Preview (early), measured in April 2026, 64%. Today's estimate: 64%.
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, 0.074% went to this job's tasks in May 2026, the 196th largest of the 447 jobs that showed up at all; 2 of its 13 tasks showed up. Within each of Anthropic's methods, never across a change: 0.089% to 0.067% (released February and March 2025); 0.026% to 0.093% (August 2025 to February 2026); 0.079% to 0.074% (April to May 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.089% | 187 of 708 | 6 of 13 |
| Released March 2025 | 0.067% | 223 of 703 | 5 of 13 |
| The week of Aug 4, 2025 (released September 2025) | 0.026% | 339 of 655 | 4 of 13 |
| The week of Nov 13, 2025 (released January 2026) | 0.08% | 180 of 672 | 5 of 13 |
| The week of Feb 5, 2026 (released March 2026) | 0.093% | 172 of 677 | 6 of 13 |
| April 2026 (released June 2026) | 0.079% | 182 of 434 | 2 of 13 |
| May 2026 (released June 2026) | 0.074% | 196 of 447 | 2 of 13 |
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
36% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Talk with customers about orders and complaints, the conversation, 12%
- Contact customers with answers and results, the conversation, 7%
- Resolve service and billing complaints, the conversation, 5%
- Solicit sales of added services, the conversation, 5%
- Set charges and arrange billing, the conversation, 2%
- Check that fixes were made, the conversation, 2%
What becomes checking the machine
44% 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.
- Investigate the validity of complaints, costly if wrong, 11%
- Complete contract and account forms, costly if wrong, 10%
- Review policy terms for coverage, costly if wrong, 6%
- Resolve service and billing complaints, costly if wrong, 5%
- Talk with customers about orders and complaints, costly if wrong, 5%
- Set charges and arrange billing, 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.
- Running AI inside the business systems. About 46% 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 35% of the time is conversation and in-person work, which this site leaves with people: listening, explaining, persuading, calming.
- Dealing with people outside the organization. Customers, patients, suppliers or the public: trust with them is built by a person.
- Briefing a model and checking its drafts. About 18% 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 . 13 tasks from . 3 have a worked example.
| Task | ||||
|---|---|---|---|---|
| Confer with customers by telephone or in person to provide information about products or services, take or enter orders, cancel accounts, or obtain details of complaints.Live calls, with entry into the order system as they go.Done hourly or more by most who do it. AI observed on this task. | 17% | 13 min4 min to 33 min | Conversation 70%, systems 30% | 30%Desk part half by now |
| Obtain and examine all relevant information to assess validity of complaints and to determine possible causes, such as extreme weather conditions that could increase utility bills.Pulling the records and weighing what they show.Done hourly or more by most who do it.See it done: one graded attempt (passes with named fixes) | 11% | 25 min13 min to 42 min | Documents 60%, systems 40% | 100%Half by now |
| Contact customers to respond to inquiries or to notify them of claim investigation results or any planned adjustments.Calls to customers, and some written replies.Done hourly or more by most who do it. AI observed on this task. | 10% | 13 min4 min to 21 min | Conversation 70%, documents 30% | 30%Desk part half by now |
| Resolve customers' service or billing complaints by performing activities such as exchanging merchandise, refunding money, or adjusting bills.Talking the complaint through and making the refund or adjustment in the system.Done several times a day by most who do it. AI observed on this task. | 10% | 25 min8 min to 42 min | Systems 50%, conversation 50% | 50%Desk part half by now |
| Complete contract forms, prepare change of address records, or issue service discontinuance orders, using computers.Form entry in the account system.Done hourly or more by most who do it. | 10% | 13 min4 min to 21 min | Systems 100% | 100%Half by now |
| Check to ensure that appropriate changes were made to resolve customers' problems.Looking the account up to confirm the change, with a call back when needed.Done hourly or more by most who do it. | 10% | 13 min4 min to 25 min | Systems 80%, conversation 20% | 80%Desk part half by now |
| Keep records of customer interactions or transactions, recording details of inquiries, complaints, or comments, as well as actions taken.Notes typed into the customer record after each contact.Done hourly or more by most who do it. AI observed on this task. | 7% | 7 min3 min to 17 min | Systems 100% | 100%Half by now |
| Review insurance policy terms to determine whether a particular loss is covered by insurance.Reading a policy against the facts of a claim.Done hourly or more by most who do it.See it done: one graded attempt (passes) | 6% | 17 min8 min to 33 min | Documents 100% | 100%Half by now |
| Determine charges for services requested, collect deposits or payments, or arrange for billing.Working out the charge and entering the billing, on the line with the customer.Done daily by most who do it. | 5% | 10 min4 min to 17 min | Systems 60%, conversation 40% | 60%Desk part half by now |
| Solicit sales of new or additional services or products.Selling on the phone.Done daily by most who do it. AI observed on this task. | 5% | 13 min4 min to 21 min | Conversation 100% | Stays with people |
| Refer unresolved customer grievances to designated departments for further investigation.Routing the case in the system, with a word to the department taking it.Done more than monthly by most who do it. AI observed on this task. | 4% | 8 min3 min to 13 min | Systems 70%, conversation 30% | 70%Desk part half by now |
| Recommend improvements in products, packaging, shipping, service, or billing methods and procedures to prevent future problems.A written recommendation, talked over with colleagues.Done more than weekly by most who do it.See it done: one graded attempt (passes with named fixes) | 3% | 33 min17 min to 1.3 h | Documents 80%, conversation 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.
- Sales Representatives of Services, Except Advertising, Insurance, Financial Services, and Travel59% now, 60% by 2028
- Telemarketers56% now, 56% by 2028
- Insurance Claims and Policy Processing Clerks86% now, 86% by 2028
- Credit Authorizers, Checkers, and Clerks86% now, 86% by 2028
- New Accounts Clerks61% now, 61% by 2028
- Receptionists and Information Clerks60% 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 Customer Service Representatives is within reach of AI now?
- An estimated 64% of the working time is within reach of AI models now and 64% 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 Customer Service Representatives 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: Investigate the validity of complaints (100% of the task's time now); Complete contract and account forms (100% of the task's time now); and Check that fixes were made (80% of the task's time now).
- Which tasks of Customer Service Representatives stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Solicit sales of added services. Together such tasks are about 5% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Customer Service Representatives 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; running AI inside the business systems; and the conversations. By the end of 2028 on the long-run pace at four in five, about 36% of the working time stays with people, 44% 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 Customer Service Representatives?
- In the Claude.ai conversations Anthropic sampled for May 2026 and tied to a work task, 0.074% went to this job's tasks, the 196th largest share of the 447 jobs that showed up; 2 of its 13 tasks appeared. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 70%. 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 Customer Service Representatives?
- 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 13 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 3 worked examples of its tasks: a brief, a rubric written beforehand, one attempt by an AI model and its grade.
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