Equal Opportunity Representatives and Officers
In short: today's best AI models could do about 51% 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 87% by the end of 2028 if progress keeps its long-run pace. The people and hands-on work, about 13% of the time, stays with people.
Monitor and evaluate compliance with equal opportunity laws, guidelines, and policies to ensure that employment practices and contracting arrangements give equal opportunity without regard to race, religion, color, national origin, sex, age, or disability.
$80,730 a year (for the broader BLS group this job sits in).
A typical 40-hour week
Not yet reviewed task by task- AI could take on21 h
- A person checks AI's work0 h
- Desk work AI can't do yet14 h
- Stays with people5 h
Equal Opportunity Representatives and Officers, now: of a 40-hour week, AI could take on 21 hours, 0 hours become checking its work, 14 hours are desk work it can't do yet, and 5 hours stay with people.
The largest pieces: Prepare reports related to investigations of equal opportunity complaints (about 5 h); Monitor the implementation and impact of guidelines for nondiscriminatory employment practices (about 3 h); Study equal opportunity complaints to clarify issues (about 2 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.
- 87%
- 13%
- 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.
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, 0%. With Claude Mythos Preview (early), measured in April 2026, 10%. Today's estimate: 51%.
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, no reportable share went to this job's tasks in May 2026; 0 of its 18 tasks showed up. Within each of Anthropic's methods, never across a change: 0.024% to 0.027% (released February and March 2025); 0.0069% to 0.03% (August 2025 to February 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.024% | 421 of 708 | 5 of 18 |
| Released March 2025 | 0.027% | 373 of 703 | 4 of 18 |
| The week of Aug 4, 2025 (released September 2025) | 0.0069% | 500 of 655 | 1 of 18 |
| The week of Nov 13, 2025 (released January 2026) | 0.032% | 312 of 672 | 3 of 18 |
| The week of Feb 5, 2026 (released March 2026) | 0.03% | 332 of 677 | 2 of 18 |
| April 2026 (released June 2026) | none | n/a | 0 of 18 |
| May 2026 (released June 2026) | none | n/a | 0 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 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.
The tasks
Sorted by . 18 tasks from .
| Task | Kind | |||
|---|---|---|---|---|
| Prepare reports related to investigations of equal opportunity complaints.Done daily by most who do it. | 14% | 5 h2.5 h to 1.7 work days | 92%Half by now | |
| Investigate employment practices or alleged violations of laws to document and correct discriminatory factors.Done hourly or more by most who do it. | 14% | 1.7 work days3.3 h to 4.2 work days | 31%Half by Mar 2027 | |
| Conduct surveys and evaluate findings to determine if systematic discrimination exists.Done yearly or less by most who do it. | 14% | 2.5 work days6.7 h to 1.3 work weeks | 20%Half by May 2027 | |
| Monitor the implementation and impact of guidelines for nondiscriminatory employment practices.Done more than monthly by most who do it. | 14% | 6.7 h1.7 h to 2.1 work days | 61%Half by now | |
| Develop guidelines for nondiscriminatory employment practices.Done more than yearly by most who do it. | 8% | 1.7 work days3.3 h to 4.2 work days | 31%Half by Mar 2027 | |
| Study equal opportunity complaints to clarify issues.Done daily by most who do it. | 6% | 1.7 h25 min to 5 h | 94%Half by now | |
| Interpret civil rights laws and equal opportunity regulations for individuals or employers.Done daily by most who do it. AI observed on this task. | 6% | 1.3 h25 min to 2.5 h | 100%Half by now | |
| Coordinate, monitor, or revise complaint procedures to ensure timely processing and review of complaints.Done more than yearly by most who do it. | 5% | 5 h1.7 h to 2.1 work days | 73%Half by now | |
| Meet with persons involved in equal opportunity complaints to arbitrate and settle disputes.Done more than monthly by most who do it. | 5% | 3.3 h1.3 h to 1 work day | Stays with people | |
| Interview persons involved in equal opportunity complaints to verify case information.Done more than weekly by most who do it. | 5% | 1.7 h50 min to 3.3 h | Stays with people | |
| Prepare reports of selection, survey, or other statistics and recommendations for corrective action.Done more than monthly by most who do it. | 2% | 6.7 h2.5 h to 2.5 work days | 69%Half by now | |
| Consult with community representatives to develop technical assistance agreements in accordance with governmental regulations.Done yearly or less by most who do it. | 1% | 5 h1.7 h to 1.7 work days | Stays with people |
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.
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.
- Labor Relations Specialists33% now, 54% by 2028
- Human Resources Managers39% now, 60% by 2028
- Eligibility Interviewers, Government Programs62% now, 62% by 2028
- Human Resources Specialists63% now, 69% by 2028
- Compliance Managers42% now, 74% by 2028
- Arbitrators, Mediators, and Conciliators63% now, 95% by 2028
Where this job works
The industry groups that employ the most of it (BLS, May 2025). Counts are for the broader BLS group this job sits in.
Where the most of these jobs are
The metro areas with the most people in it (BLS, May 2025). Counts are for the broader BLS group this job sits in.
Questions about this job
- How much of the work of Equal Opportunity Representatives and Officers is within reach of AI now?
- An estimated 51% of the working time is within reach of AI models now and 87% by the end of 2028, on METR's long-run pace at four in five (82% to 87% across the three paces the site shows). 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 Equal Opportunity Representatives and Officers 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 reports related to investigations of equal opportunity complaints (92% of the task's time now, 100% by the end of 2028); Monitor the implementation and impact of guidelines for nondiscriminatory employment practices (61% of the task's time now, 100% by the end of 2028); and Study equal opportunity complaints to clarify issues (94% of the task's time now, 100% by the end of 2028).
- Which tasks of Equal Opportunity Representatives and Officers stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Meet with persons involved in equal opportunity complaints to arbitrate and settle disputes; Interview persons involved in equal opportunity complaints to verify case information; and Consult with community representatives to develop technical assistance agreements in accordance with governmental regulations. Together such tasks are about 13% of the working time.
- Do people already use AI for the work of Equal Opportunity Representatives and Officers?
- In the Claude.ai conversations Anthropic sampled for May 2026, no reportable share went to this job's tasks. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 12%. 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 Equal Opportunity Representatives and Officers?
- 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 18 tasks O*NET lists for the occupation, each with an estimated length checked against GDPval and a share of the working time, each classed as desk, people or body work, 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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