Eligibility Interviewers, Government Programs
In short: today's best AI models could do about 62% 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 38% of the time, stays with people.
Determine eligibility of persons applying to receive assistance from government programs and agency resources, such as welfare, unemployment benefits, social security, and public housing.
154,800 people do this job in the US. $54,210 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 on0 h
- A person checks AI's work25 h
- Desk work AI can't do yet0 h
- Stays with people15 h
Eligibility Interviewers, Government Programs, now: of a 40-hour week, AI could take on 0 hours, 25 hours become checking its work, 0 hours are desk work it can't do yet, and 15 hours stay with people.
The largest pieces: Evaluate data for eligibility (about 6 h, a person checks); Grant, modify or deny assistance (about 5 h, a person checks); Keep case records and reports (about 5 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.
- 26%
- 36%
- 16%
- 22%
- 0%
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 62% 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, 1%. With Claude Mythos Preview (early), measured in April 2026, 60%. Today's estimate: 62%.
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, 0.064% went to this job's tasks in May 2026, the 207th largest of the 447 jobs that showed up at all; 2 of its 17 tasks showed up. Within each of Anthropic's methods, never across a change: 0.098% to 0.052% (released February and March 2025); 0.067% to 0.077% (August 2025 to February 2026); 0.057% to 0.064% (April to May 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.098% | 171 of 708 | 6 of 17 |
| Released March 2025 | 0.052% | 263 of 703 | 6 of 17 |
| The week of Aug 4, 2025 (released September 2025) | 0.067% | 200 of 655 | 4 of 17 |
| The week of Nov 13, 2025 (released January 2026) | 0.066% | 202 of 672 | 3 of 17 |
| The week of Feb 5, 2026 (released March 2026) | 0.077% | 197 of 677 | 5 of 17 |
| April 2026 (released June 2026) | 0.057% | 215 of 434 | 2 of 17 |
| May 2026 (released June 2026) | 0.064% | 207 of 447 | 2 of 17 |
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
37% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Interview applicants, the in-person work, 12%
- Recertify recipients, the in-person work, 6%
- Explain eligibility and rights, the conversation, 6%
- Answer questions about benefits, the conversation, 4%
- Verify answers with employers, the conversation, 3%
- Investigate fraud, the conversation, 2%
What becomes checking the machine
62% 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.
- Evaluate data for eligibility, costly if wrong, 15%
- Grant, modify or deny assistance, costly if wrong, 13%
- Keep case records and reports, costly if wrong, 11%
- Compute and authorize assistance, costly if wrong, 7%
- Interview applicants, costly if wrong, 3%
- Recertify recipients, 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.
- 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.
- The conversations. About 37% of the time is conversation and in-person work, which this site leaves with people: listening, explaining, persuading, calming.
- Running AI inside the business systems. About 36% 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.
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 . 17 tasks from .
| Task | ||||
|---|---|---|---|---|
| Interview and investigate applicants for public assistance to gather information pertinent to their applications.Interviews in the office, some by phone, with the entries.Done daily by most who do it. | 15% | 1.1 h25 min to 1.7 h | In person 60%, systems 20%, conversation 20% | 20%Desk part half by now |
| Compile, record, and evaluate personal and financial data to verify completeness and accuracy, and to determine eligibility status.Reading the personal and financial data for completeness and eligibility.Done daily by most who do it. | 15% | 42 min25 min to 1.3 h | Documents 60%, systems 40% | 100%Half by now |
| Initiate procedures to grant, modify, deny, or terminate assistance, or refer applicants to other agencies for assistance.Actions entered in the system, with the notices to applicants.Done daily by most who do it. | 13% | 29 min13 min to 50 min | Systems 60%, documents 40% | 100%Half by now |
| Keep records of assigned cases, and prepare required reports.Case records kept and reports written.Done daily by most who do it. | 11% | 38 min17 min to 1.3 h | Systems 60%, documents 40% | 100%Half by now |
| Interview benefits recipients at specified intervals to certify their eligibility for continuing benefits.Interviews in the office or by phone, with the entries.Done daily by most who do it. | 9% | 38 min17 min to 1.1 h | In person 50%, systems 30%, conversation 20% | 30%Desk part half by now |
| Compute and authorize amounts of assistance for programs, such as grants, monetary payments, and food stamps.Amounts worked out and authorized in the system.Done daily by most who do it. | 7% | 25 min13 min to 50 min | Systems 60%, documents 40% | 100%Half by now |
| Interpret and explain information such as eligibility requirements, application details, payment methods, and applicants' legal rights.Explanations at the desk and by phone.Done daily by most who do it. | 6% | 17 min8 min to 38 min | Conversation 50%, in person 50% | Stays with people |
| Investigate claimants for the possibility of fraud or abuse.Records examined and calls made to check a claimant's statements.Done more than yearly by most who do it. | 4% | 2.5 h50 min to 6.7 h | Documents 60%, conversation 40% | 57%Desk part half by now |
| Check with employers or other references to verify answers and obtain further information.Calls to employers and references, with the record noted.Done more than weekly by most who do it. | 4% | 21 min8 min to 50 min | Conversation 70%, systems 30% | 30%Desk part half by now |
| Answer applicants' questions about benefits and claim procedures.Questions at the desk and by phone.Done daily by most who do it. AI observed on this task. | 4% | 13 min4 min to 25 min | Conversation 50%, in person 50% | Stays with people |
| Prepare applications and forms for applicants for such purposes as school enrollment, employment, and medical services.Forms prepared for enrollment, employment and medical services.Done more than weekly by most who do it. | 2% | 29 min13 min to 50 min | Documents 50%, systems 50% | 100%Half by now |
| Provide applicants with assistance in completing application forms, such as those for job referrals or unemployment compensation claims.Helping the applicant at the desk and entering the form.Done more than weekly by most who do it. | 2% | 25 min13 min to 50 min | In person 70%, systems 30% | 30%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.
- Human Resources Assistants, Except Payroll and Timekeeping70% now, 70% by 2028
- Human Resources Specialists63% now, 69% by 2028
- Interviewers, Except Eligibility and Loan50% now, 50% by 2028
- Compensation, Benefits, and Job Analysis Specialists43% now, 80% by 2028
- Social and Community Service Managers36% now, 51% by 2028
- Insurance Claims and Policy Processing Clerks86% now, 86% 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 Eligibility Interviewers, Government Programs is within reach of AI now?
- An estimated 62% of the working time is within reach of AI models now and 62% 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 Eligibility Interviewers, Government Programs 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: Evaluate data for eligibility (100% of the task's time now); Grant, modify or deny assistance (100% of the task's time now); and Keep case records and reports (100% of the task's time now).
- Which tasks of Eligibility Interviewers, Government Programs stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Explain eligibility and rights; and Answer questions about benefits. Together such tasks are about 10% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Eligibility Interviewers, Government Programs 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; handling protected records; and the conversations. By the end of 2028 on the long-run pace at four in five, about 37% of the working time stays with people, 62% becomes checking a model's work and 0% 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 Eligibility Interviewers, Government Programs?
- In the Claude.ai conversations Anthropic sampled for May 2026 and tied to a work task, 0.064% went to this job's tasks, the 207th largest share of the 447 jobs that showed up; 2 of its 17 tasks appeared. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 6%. 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 Eligibility Interviewers, Government Programs?
- 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 17 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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