Human Resources Assistants, Except Payroll and Timekeeping
In short: today's best AI models could do about 70% 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 30% of the time, stays with people.
Compile and keep personnel records. Record data for each employee, such as address, weekly earnings, absences, amount of sales or production, supervisory reports, and date of and reason for termination. May prepare reports for employment records, file employment records, or search employee files and furnish information to authorized persons.
90,220 people do this job in the US. $50,610 a year.
Reviewed on October 1, 2026: what each task is made of, and what handing it over would ask.
A typical 40-hour week
- AI could take on3 h
- A person checks AI's work25 h
- Desk work AI can't do yet0 h
- Stays with people12 h
Human Resources Assistants, Except Payroll and Timekeeping, now: of a 40-hour week, AI could take on 3 hours, 25 hours become checking its work, 0 hours are desk work it can't do yet, and 12 hours stay with people.
The largest pieces: Maintain personnel documentation (about 7 h, a person checks); Prepare personnel reports (about 3 h, a person checks); Help administer benefits and claims (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.
- 28%
- 42%
- 21%
- 5%
- 4%
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 70% 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, 60%. Today's estimate: 70%.
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, 0.011% went to this job's tasks in May 2026, the 379th largest of the 447 jobs that showed up at all; 1 of its 19 tasks showed up. Within each of Anthropic's methods, never across a change: 0.12% to 0.073% (released February and March 2025); 0.071% to 0.14% (August 2025 to February 2026); none to 0.011% (April to May 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.12% | 149 of 708 | 8 of 19 |
| Released March 2025 | 0.073% | 206 of 703 | 7 of 19 |
| The week of Aug 4, 2025 (released September 2025) | 0.071% | 190 of 655 | 7 of 19 |
| The week of Nov 13, 2025 (released January 2026) | 0.13% | 123 of 672 | 8 of 19 |
| The week of Feb 5, 2026 (released March 2026) | 0.14% | 125 of 677 | 9 of 19 |
| April 2026 (released June 2026) | none | n/a | 0 of 19 |
| May 2026 (released June 2026) | 0.011% | 379 of 447 | 1 of 19 |
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 5% of this job's working time as physical work. For 5% of the working time, a robot has been shown doing most of the task somewhere: 4% in a purpose-built cell, 1% in a structured facility. 0.06 of 3, the 560th highest of the 923 jobs.
- Not physical 95%
- In a purpose-built cell 4%
- 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
30% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Interview applicants to verify details, the conversation, 6%
- Explain policies and benefits, the conversation, 6%
- Help administer benefits and claims, the conversation, 4%
- Give and score assessments, the in-person work, 3%
- Set up new hire orientations, the hands-on work, 3%
- Answer pay and benefits questions, the conversation, 2%
What becomes checking the machine
61% 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 9% is desk work that is small if wrong, which can be handed over with lighter checks.
- Maintain personnel documentation, costly if wrong, 17%
- Prepare personnel reports, costly if wrong, 8%
- Help administer benefits and claims, costly if wrong, 6%
- Record employee data, costly if wrong, 6%
- Check files for personnel actions, costly if wrong, 5%
- Give and score assessments, costly if wrong, 5%
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 42% 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 28% 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.
- The conversations. About 26% of the time is conversation and in-person work, which this site leaves with people: listening, explaining, persuading, calming.
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 . 19 tasks from .
| Task | ||||
|---|---|---|---|---|
| Process, verify, and maintain personnel related documentation, including staffing, recruitment, training, grievances, performance evaluations, classifications, and employee leaves of absence.Checking and filing the paperwork in the personnel system.Done daily by most who do it. AI observed on this task. | 17% | 50 min17 min to 2.1 h | Systems 70%, documents 30% | 100%Half by now |
| Provide assistance in administering employee benefit programs and worker's compensation plans.Enrollments and claims entered and followed up with the carriers.Done more than monthly by most who do it. | 11% | 50 min17 min to 1.7 h | Systems 60%, conversation 40% | 60%Desk part half by now |
| Administer and score applicant and employee aptitude, personality, and interest assessment instruments.Running the test session and scoring it in the system.Done more than monthly by most who do it. | 8% | 1.3 h25 min to 2.5 h | Systems 60%, in person 40% | 60%Desk part half by now |
| Compile and prepare reports and documents pertaining to personnel activities.Pulling the figures from the system and writing the report.Done more than monthly by most who do it. AI observed on this task. | 8% | 1.7 h50 min to 3.3 h | Documents 70%, systems 30% | 100%Half by now |
| Interview job applicants to obtain and verify information used to screen and evaluate them.Interviews, with notes.Done more than weekly by most who do it. | 7% | 50 min25 min to 1.7 h | Conversation 80%, documents 20% | 20%Desk part half by now |
| Record data for each employee, including such information as addresses, weekly earnings, absences, amount of sales or production, supervisory reports on performance, and dates of and reasons for terminations.Entries in the personnel system.Done more than weekly by most who do it. | 6% | 25 min8 min to 50 min | Systems 100% | 100%Half by now |
| Prepare and set up for new employee orientations.Preparing the packets and the room.Done more than monthly by most who do it. Robots: in a purpose-built cell, AmbiKit (Ambi Robotics) (deployed). Anthropic's rating. | 6% | 1.7 h38 min to 3.3 h | Documents 50%, hands-on 50% | 50%Desk part half by now |
| Explain company personnel policies, benefits, and procedures to employees or job applicants.Walking employees and applicants through the policies, by phone and at the desk.Done daily by most who do it. AI observed on this task. | 6% | 21 min8 min to 50 min | Conversation 70%, in person 30% | Stays with people |
| Examine employee files to answer inquiries and provide information for personnel actions.Reading the file and pulling what the action needs.Done daily by most who do it. | 5% | 25 min8 min to 1.3 h | Systems 60%, documents 40% | 100%Half by now |
| Process and review employment applications to evaluate qualifications or eligibility of applicants.Reading applications against the requirements and logging the result.Done daily by most who do it. AI observed on this task. | 4% | 25 min8 min to 1.3 h | Documents 60%, systems 40% | 100%Half by now |
| Gather personnel records from other departments or employees.Requesting and collecting the forms from departments and employees.Done daily by most who do it. | 3% | 25 min8 min to 50 min | Documents 50%, conversation 50% | 50%Desk part half by now |
| Request information from law enforcement officials, previous employers, and other references to determine applicants' employment acceptability.Calls and letters to references and agencies, with the answers recorded.Done more than weekly by most who do it. | 3% | 50 min17 min to 1.7 h | Documents 50%, conversation 50% | 50%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 Specialists63% now, 69% by 2028
- Human Resources Managers39% now, 60% by 2028
- Eligibility Interviewers, Government Programs62% now, 62% by 2028
- Payroll and Timekeeping Clerks85% now, 85% by 2028
- Compensation, Benefits, and Job Analysis Specialists43% now, 80% by 2028
- First-Line Supervisors of Office and Administrative Support Workers54% now, 58% 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 Human Resources Assistants, Except Payroll and Timekeeping is within reach of AI now?
- An estimated 70% of the working time is within reach of AI models now and 70% 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 Human Resources Assistants, Except Payroll and Timekeeping 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: Maintain personnel documentation (100% of the task's time now); Prepare personnel reports (100% of the task's time now); and Help administer benefits and claims (60% of the task's time now).
- Which tasks of Human Resources Assistants, Except Payroll and Timekeeping stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Explain policies and benefits. Together such tasks are about 6% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Human Resources Assistants, Except Payroll and Timekeeping 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 30% of the working time stays with people, 61% becomes checking a model's work and 9% 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 Human Resources Assistants, Except Payroll and Timekeeping?
- In the Claude.ai conversations Anthropic sampled for May 2026 and tied to a work task, 0.011% went to this job's tasks, the 379th largest share of the 447 jobs that showed up; 1 of its 19 tasks appeared. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 40%. 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 Human Resources Assistants, Except Payroll and Timekeeping?
- Anthropic's robot exposure rating (September 2026) finds 5% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 5% of the working time, 1% in a structured facility. Its index is 0.06 of 3. One example: Unicard Systems self-service card issuance kiosk for "make badges and passes". 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 19 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 October 1, 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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