Insurance Claims and Policy Processing Clerks
In short: today's best AI models could do about 85% 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 15% of the time, stays with people.
Process new insurance policies, modifications to existing policies, and claims forms. Obtain information from policyholders to verify the accuracy and completeness of information on claims forms, applications and related documents, and company records. Update existing policies and company records to reflect changes requested by policyholders and insurance company representatives.
214,260 people do this job in the US. $49,230 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 on1 h
- A person checks AI's work33 h
- Desk work AI can't do yet0 h
- Stays with people6 h
Insurance Claims and Policy Processing Clerks, now: of a 40-hour week, AI could take on 1 hours, 33 hours become checking its work, 0 hours are desk work it can't do yet, and 6 hours stay with people.
The largest pieces: Prepare and check claim forms (about 4 h, a person checks); Search and update records (about 4 h, a person checks); Determine coverage (about 3 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.
- 29%
- 56%
- 13%
- 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 85% 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, 8%. With Claude Mythos Preview (early), measured in April 2026, 85%. Today's estimate: 86%.
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, 0.89% went to this job's tasks in May 2026, the 29th largest of the 447 jobs that showed up at all; 3 of its 25 tasks showed up. Within each of Anthropic's methods, never across a change: 0.17% to 0.086% (released February and March 2025); 0.085% to 0.1% (August 2025 to February 2026); 0.96% to 0.89% (April to May 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.17% | 109 of 708 | 15 of 25 |
| Released March 2025 | 0.086% | 180 of 703 | 15 of 25 |
| The week of Aug 4, 2025 (released September 2025) | 0.085% | 173 of 655 | 5 of 25 |
| The week of Nov 13, 2025 (released January 2026) | 0.083% | 174 of 672 | 9 of 25 |
| The week of Feb 5, 2026 (released March 2026) | 0.1% | 161 of 677 | 9 of 25 |
| April 2026 (released June 2026) | 0.96% | 27 of 434 | 3 of 25 |
| May 2026 (released June 2026) | 0.89% | 29 of 447 | 3 of 25 |
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
14% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Guide customers on claims, the conversation, 5%
- Chase missing information, the conversation, 5%
- Take claim calls, the conversation, 2%
- Correspond on account status, the conversation, 2%
- Keep policyholder files, the hands-on work, 0.6%
What becomes checking the machine
83% 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 2% is desk work that is small if wrong, which can be handed over with lighter checks.
- Prepare and check claim forms, costly if wrong, 10%
- Search and update records, costly if wrong, 10%
- Determine coverage, costly if wrong, 8%
- Pay small claims, costly if wrong, 7%
- Calculate claim amounts, costly if wrong, 7%
- Record new policies and claims, costly if wrong, 6%
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 56% 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.
- Handling protected records. Much of the work touches protected personal records: knowing what may be shared with a model, and how, is part of the job.
- Briefing a model and checking its drafts. About 29% 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.
- 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 . 25 tasks from .
| Task | ||||
|---|---|---|---|---|
| Prepare insurance claim forms or related documents, and review them for completeness.Filling in the forms and reading them over.Done hourly or more by most who do it. | 10% | 21 min8 min to 50 min | Documents 50%, systems 50% | 100%Half by now |
| Organize or work with detailed office or warehouse records, using computers to enter, access, search or retrieve data.Working in the records system.Done hourly or more by most who do it. | 10% | 21 min8 min to 50 min | Systems 100% | 100%Half by now |
| Review insurance policy to determine coverage.Reading the policy against the claim.Done hourly or more by most who do it. | 8% | 25 min8 min to 50 min | Documents 100% | 100%Half by now |
| Pay small claims.Payments entered in the system.Done hourly or more by most who do it. | 7% | 21 min8 min to 38 min | Systems 100% | 100%Half by now |
| Calculate amount of claim.Working the figures, mostly in the system.Done hourly or more by most who do it. | 7% | 21 min8 min to 50 min | Documents 50%, systems 50% | 100%Half by now |
| Process and record new insurance policies and claims.Entries in the system.Done daily by most who do it. AI observed on this task. | 6% | 33 min13 min to 1.1 h | Systems 100% | 100%Half by now |
| Transmit claims for payment or further investigation.Sending the claim on in the system.Done hourly or more by most who do it. | 6% | 13 min4 min to 29 min | Systems 100% | 100%Half by now |
| Provide customer service, such as limited instructions on proceeding with claims or referrals to auto repair facilities or local contractors.Calls with customers.Done hourly or more by most who do it. | 5% | 13 min4 min to 25 min | Conversation 100% | Stays with people |
| Contact insured or other involved persons to obtain missing information.Calls and emails to the insured.Done more than weekly by most who do it. | 5% | 17 min8 min to 38 min | Conversation 100% | Stays with people |
| Correspond with insured or agent to obtain information or to inform them of account status or changes.Letters and calls.Done several times a day by most who do it. | 4% | 17 min8 min to 33 min | Documents 60%, conversation 40% | 60%Desk part half by now |
| Examine letters from policyholders or agents, original insurance applications, and other company documents to determine if changes are needed and effects of changes.Reading the letters and the policy.Done daily by most who do it. AI observed on this task. | 4% | 25 min8 min to 1.1 h | Documents 100% | 100%Half by now |
| Post or attach information to claim file.Entries in the claim file.Done hourly or more by most who do it. | 4% | 8 min3 min to 21 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.
- Customer Service Representatives64% now, 64% by 2028
- Credit Authorizers, Checkers, and Clerks86% now, 86% by 2028
- Eligibility Interviewers, Government Programs62% now, 62% by 2028
- Billing and Posting Clerks85% now, 85% by 2028
- Loan Interviewers and Clerks72% now, 72% by 2028
- Bookkeeping, Accounting, and Auditing Clerks88% now, 90% 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 Insurance Claims and Policy Processing Clerks is within reach of AI now?
- An estimated 86% of the working time is within reach of AI models now and 86% 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 Insurance Claims and Policy Processing 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: Prepare and check claim forms (100% of the task's time now); Search and update records (100% of the task's time now); and Determine coverage (100% of the task's time now).
- Which tasks of Insurance Claims and Policy Processing Clerks stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Guide customers on claims; Chase missing information; and Take claim calls. Together such tasks are about 12% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Insurance Claims and Policy Processing 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 reviewing work you did not do yourself; running AI inside the business systems; and handling protected records. By the end of 2028 on the long-run pace at four in five, about 14% of the working time stays with people, 83% becomes checking a model's work and 2% 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 Insurance Claims and Policy Processing Clerks?
- In the Claude.ai conversations Anthropic sampled for May 2026 and tied to a work task, 0.89% went to this job's tasks, the 29th largest share of the 447 jobs that showed up; 3 of its 25 tasks appeared. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 15%. 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 Insurance Claims and Policy Processing Clerks?
- 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 25 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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