Community Sentiment
Do you agree?
Do you agree with the AI automation risk score calculated for this occupation?
AI Automation Index
Will AI Replace Equal Opportunity Representatives and Officers?
Task-level automation exposure for Equal Opportunity Representatives and Officers: 18 O*NET tasks scored against their work activities, plus the simulator.
E-E-A-T Verified
Developed & audited by Gini Loh Automation Exposure
49%
weighted task index
18 of 18 tasks scored
Median Salary
$80,730 / year
BLS OEWS, May 2025 — this exact occupation
Employment Level
Very High
417,070 people hold this job — size, not growth
Projected 2025–35
+3.8%
employment change
32,700 openings a year · BLS line item
Pay by state
BLS OEWS publishes 54 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.
$48,950 – $111,030
Highest medians
District of Columbia $111,030
Massachusetts $102,060
New Jersey $100,000
California $96,980
Connecticut $91,810
Lowest medians
Puerto Rico $48,950
Oklahoma $63,000
Tennessee $63,960
West Virginia $64,270
Arkansas $64,680
State figures come from the 13-1041 row in the May 2025 state panel. States where the estimate was suppressed or too small to publish are absent.
What the score is made of
Each task is mapped to its work activities, scored for AI automation potential, and weighted by how important those activities are to the job. These are the components.
Automation potential 49%
Importance-weighted mean of the scored tasks. This is the headline index.
Physical work 0%
Share of weighted tasks in hands-on or machine-operating work activities.
Judgment & influence 18%
Share in analysis, decisions, teaching, directing, advising, or caring for others.
Routine administration 12%
Share in documenting, recording, and administrative activities.
Rewritten by O*NET 6%
Share of weighted tasks O*NET rewrote in a recent update. Reported, not folded into the score.
Consequence of error 10/100
Low
O*NET's own rating of how serious an uncorrectable mistake would be here — respondents, not us. Deliberately not in the index: the score measures what AI can do with the task content, and multiplying it by stakes would be our judgment dressed as data.
Constituent Task Mix
18 tasks for this occupation, weighted by work-activity importance. Shares below are of total task weight, not task count.
High exposure (≥ 60% of the task is automatable) 25%
4 tasks
Medium exposure (≥ 35%) 60%
12 tasks
Low exposure (below 35%) 14%
2 tasks
How would you survive?
Move your week away from the high-exposure tasks and toward the ones that need judgment. The simulator recalculates the index as you shift the mix.
Simulate Upskilling →Emerging & rewritten tasks
Tasks O*NET added or rewrote for this occupation in its recent updates (05/2025 – 08/2026), with who proposed them. Additions are not in the scored task inventory — they are new work O*NET is still measuring, so they appear here and nowhere in the index. A Revision replaces a task that is scored, which is why only those move the "Rewritten by O*NET" share.
- Revision 07/2015 · Incumbent
Develop guidelines for nondiscriminatory employment practices, such as affirmative action plans and equal opportunity employment policies.
Replaced: Develop guidelines for nondiscriminatory employment practices.
- New 07/2015 · Incumbent
Train employees on equal opportunity laws, guidelines, or policies, such as discrimination, diversity, harassment, or affirmative action.
Constituent Tasks
#10865 · Core · 45% automatable
Investigate employment practices or alleged violations of laws to document and correct discriminatory factors.
decision support — Judgment on personnel adherence needs human accountability
Evaluate personnel practices to ensure adherence to regulations.
#20719 · Core · 75% automatable
Prepare reports related to investigations of equal opportunity complaints.
text generation — Research reports drafted; human owns findings
Prepare research reports.
#20720 · Core · 20% automatable
Interview persons involved in equal opportunity complaints to verify case information.
interpersonal — Witness/suspect interviews need human presence
Interview witnesses, suspects, or claimants.
#10867 · Core · 45% automatable
Study equal opportunity complaints to clarify issues.
decision support — Judgment on personnel adherence needs human accountability
Evaluate personnel practices to ensure adherence to regulations.
#10866 · Core · 62% automatable
Interpret civil rights laws and equal opportunity regulations for individuals or employers.
information retrieval — AI explains policies; human handles live questions
Explain regulations, policies, or procedures.
#20721 · Core · 26% automatable
Meet with persons involved in equal opportunity complaints to arbitrate and settle disputes.
interpersonal — Dispute settlement needs live facilitation and authority
Interview witnesses, suspects, or claimants. Negotiate agreements to resolve disputes.
#20722 · Core · 55% automatable
Revision
Develop guidelines for nondiscriminatory employment practices.
decision support — AI drafts guidelines; authority and context are human
Establish organizational guidelines or policies.
#20723 · Core · 45% automatable
Monitor the implementation and impact of guidelines for nondiscriminatory employment practices.
decision support — Judgment on personnel adherence needs human accountability
Evaluate personnel practices to ensure adherence to regulations.
#10869 · Core · 62% automatable
Coordinate, monitor, or revise complaint procedures to ensure timely processing and review of complaints.
data analysis — Organizational process monitoring is largely digital and analyzable
Monitor organizational processes.
#10875 · Core · 48% automatable
Provide information, technical assistance, or training to supervisors, managers, or employees on topics such as employee supervision, hiring, grievance procedures, or staff development.
interpersonal — Managerial training content draftable, facilitation is human
Train personnel on managerial topics.
#10871 · Core · 44% automatable
Conduct surveys and evaluate findings to determine if systematic discrimination exists.
decision support — Judgment on personnel adherence needs human accountability
Conduct surveys in organizations. Evaluate personnel practices to ensure adherence to regulations.
#10870 · Supplemental · 75% automatable
Prepare reports of selection, survey, or other statistics and recommendations for corrective action.
text generation — Research reports drafted; human owns findings
Prepare research reports.
#10879 · Supplemental · 45% automatable
Meet with job search committees or coordinators to explain the role of the equal opportunity coordinator, to provide resources for advertising, or to explain expectations for future contacts.
interpersonal — Business operations coordination is live and relational
Confer with personnel to coordinate business operations.
#10874 · Supplemental · 55% automatable
Counsel newly hired members of minority or disadvantaged groups, informing them about details of civil rights laws.
interpersonal — HR advice sensitive; accountability and context human
Advise others on human resources topics.
#10873 · Supplemental · 45% automatable
Review company contracts to determine actions required to meet governmental equal opportunity provisions.
decision support — Judgment on personnel adherence needs human accountability
Evaluate personnel practices to ensure adherence to regulations.
#10876 · Supplemental · 59% automatable
Verify that all job descriptions are submitted for review and approval and that descriptions meet regulatory standards.
text generation — Track and draft regulatory documentation; human verifies
Evaluate personnel practices to ensure adherence to regulations. Coordinate regulatory documentation activities.
#10878 · Supplemental · 35% automatable
Consult with community representatives to develop technical assistance agreements in accordance with governmental regulations.
interpersonal — Contract negotiation needs mandate and accountability
Negotiate contracts with clients or service providers.
#10880 · Supplemental · 40% automatable
Participate in the recruitment of employees through job fairs, career days, or advertising plans.
interpersonal — Recruitment coordination aided by AI, human decides
Coordinate personnel recruitment activities.
Embed this calculator on your site ↓
Bloggers & authors: Embed this interactive calculator directly in your articles or comparison guides. It loads dynamically via a responsive iframe (auto-resizing to prevent double scrollbars) and provides a direct, high-value tool for your audience.
<div class="giniloh-calculator-embed" data-calculator="equal-opportunity-representatives-and-officers"></div>
<script src="https://giniloh.com/embed.js" async></script> Method
How this was scored
- 1. Tasks. O*NET task statements for this occupation, from a release whose newest record is dated 08/2026.
- 2. Work activities. Each task maps to 1–5 Detailed Work Activities; each activity belongs to one of 41 Generalized Work Activities that O*NET rates for importance (1–5) in this occupation.
- 3. Automation potential. Every work activity carries one score for how far current AI can perform it end-to-end. Tasks inherit the mean of their activities.
- 4. Weighting. Task weight = 0.35 + 0.65 × (importance − 1)/4, scaled by how often the task is performed and by 0.7 for Supplemental tasks. Importance is the task's own O*NET rating where it exists (18,369 of 18,838 tasks); the rest inherit their work activities' importance. The index is the weighted mean.
Check: across the 910 occupations where O*NET also rates how far machine speed sets the pace, this index moves opposite to it (Spearman ρ = -0.49). The more a job is paced by equipment, the less of its task content AI can address — the relationship you would expect if the scoring is working.
Sources · O*NET 31.0 (task records to 08/2026) · BLS OEWS May 2025 · BLS projections 2025-2035 · rubric v2.1 · tasks for O*NET, not a forecast
See the full method →Related Article
Best AI Proof Jobs in a Changing Market
Worried robots are coming for your paycheck? You’re not alone—but the real story is far more hopeful. This guide cuts through the scare headlines to reveal exactly where smart, sustainable career opportunities exist right now. We’ve curated a list of true ai proof jobs—roles in healthcare, skilled trades, and cybersecurity that not only survive automation but thrive because of human judgment and empathy. You’ll get specific, money-making data on projected growth (the BLS says wind turbine technicians, for instance, will grow 44% by 2032), real salary ranges from active job listings, and a simple self-assessment quiz to identify your own most resilient path. Plus, we name companies hiring today and the niche job boards they use. Stop worrying and start planning—your secure career is closer than you think.
Read Article ->