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Human Resources Managers

Occupation · SOC 11-3121.00

Plan, direct, or coordinate human resources activities and staff of an organization.

Also called: Employee Relations Manager · HR Director (Human Resources Director) · HR Manager (Human Resources Manager) · HR VP (Human Resources Vice President) · HR Admin Director (Human Resources Administration Director) · HR Ops Manager (Human Resources Operations Manager) · Recruitment Director · Diversity Manager · Diversity and Inclusion Director · Efficiency Manager · Employee Welfare Manager · Employment Manager

Job family: Management Occupations

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A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch /roles/role-11-3121-00/context.md directly.

AI work map

A fast read on where AI already shows up in this occupation, where it stays a copilot, where humans remain in the loop, and what the labor market is doing. Built from observed Claude.ai conversations mapped to O*NET tasks and from published research — measures of usage and exposure, not advice or predictions that the job is going away.

Use as a copilot

Task areas where people work with AI — iterating, learning, or checking — staying in the loop rather than handing the task off.

  • Provide current and prospective employees with information about policies, job duties, working conditions, wages, opportunities for promotion and employee benefits. · 1.6%
  • Develop, administer and evaluate applicant tests. · 1.0%
  • Analyze and modify compensation and benefits policies to establish competitive programs and ensure compliance with legal requirements. · 0.7%
See collaboration patterns →

Keep a human in the loop

Task areas where a human was still judged necessary in a large share of observed conversations — not a safety ruling, an observed-need signal.

  • Provide current and prospective employees with information about policies, job duties, working conditions, wages, opportunities for promotion and employee benefits. · 98.8% need a human
  • Develop, administer and evaluate applicant tests. · 97.0% need a human
  • Advise managers on organizational policy matters such as equal employment opportunity and sexual harassment, and recommend needed changes. · 94.3% need a human
See the boundary tasks →

71st-percentile task overlap — yet about 17,900 openings a year (+5% projected, BLS), and observed AI use leans 4768% copilot, not hand-off (AEI) . What exposure means →

AI & job outlook

What today's research says about this occupation's exposure to AI, how AI is actually being used in it, and where employment is headed. These are positions within published studies — measures of exposure and usage, not predictions that this job will disappear.

Exposure to current AI

Each study uses its own scale, so the raw scores are not comparable across rows — the percentile (this job's rank among all U.S. occupations with data) is the comparable figure, and sizes the bars.

Measure Rank vs all occupations Percentile Score
Overall AI exposure (Felten et al.) High 88th 1.3
LLM task exposure, γ (OpenAI / Eloundou) High 81st 0.9
AI assistant applicability (Microsoft) Moderate 44th 0.1

OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.0), with simple added tooling (β 0.5), and including AI-powered software (γ 0.9). Higher means more of the job's tasks could be done at least twice as fast — not that they will be automated away.

Most of this job's tasks can be done remotely (Dingel–Neiman), which tends to track with higher digital and AI exposure.

Historical automation estimate (2013)

A pre-LLM (2013) estimate of how automatable this job is by computerization and robotics. Shown for historical context only — it is not part of any current AI ranking.

Frey–Osborne probability 0.0 · 4th percentile among occupations · Low

How AI is actually used in this job

Among measured AI assistant conversations mapped to this occupation (Anthropic Economic Index, 2026-01-15), these task types came up most. These are shares of observed AI conversations — not shares of the job, of worker time, or of what could be automated.

Analyze and modify compensation and benefits policies to establish competitive programs and ensure compliance with legal requirements. 0.7%
Analyze statistical data and reports to identify and determine causes of personnel problems and develop recommendations for improvement of organization's personnel policies and practices. 0.7%
Prepare personnel forecast to project employment needs. 0.2%

Job outlook

Independent U.S. Bureau of Labor Statistics employment projection for 2024–2034 — a labor-market forecast, not an AI-impact forecast.

Outlook About average · +5.0% by 2034
Projected annual openings 17,900
Employment 2024 → 2034 221,900 → 233,000

“Annual openings” counts new jobs plus replacements for workers who leave the occupation, so it can be large even when growth is modest.

Where this work sits on the global GenAI gradient

The ILO's 2025 global study scores generative-AI exposure on the international ISCO-08 occupation system, not US SOC. Bridged through the published (and approximate, many-to-many) IBS O*NET-SOC ↔ ISCO-08 crosswalk, this US occupation corresponds to the international occupation below. Exposure here means how much of the work's tasks today's AI can attempt — task overlap, not automation, adoption, or jobs lost.

36% mean task exposure (2025)
66th percentile of 427 placed occupations
+8 pts shift 2023 → 2025
International occupation (ISCO-08) Task exposure (2025) Most tasks fall in
Human Resource Managers · 1212 36% Minimal

Read the whole six-band gradient on the GenAI exposure gradient page. The crosswalk is approximate: a US occupation can map to several international ones, and the ILO scores describe the international occupation, not this exact US role.

Working with AI in this job

How people actually apply AI to this occupation's tasks, from Claude.ai (Free and Pro) conversations in the Anthropic Economic Index, 2026-01-15. This is one AI assistant's consumer sample — not all AI, not the whole workforce. Autonomy and the collaboration mix are model-rated estimates; figures below the sample floor are hidden.

Augmentation vs. automation 47.7% working with AI · 33.2% handed to AI
Most common way people use AI here Directive · AI does it; you give the instruction
Typical AI autonomy 4.0 / 5 · higher = AI acts more independently
Used for work (vs. personal / coursework) 84.2%

What people delegate to AI

The role's most common tasks in AI conversations, each tagged with how people work with the AI on it. “Usage” is the share of observed conversations, not of the job.

Task How Usage
Provide current and prospective employees with information about policies, job duties, working conditions, wages, opportunities for promotion and employee benefits. Learning 1.6%
Develop, administer and evaluate applicant tests. Iteration 1.0%
Analyze and modify compensation and benefits policies to establish competitive programs and ensure compliance with legal requirements. Iteration 0.7%
Advise managers on organizational policy matters such as equal employment opportunity and sexual harassment, and recommend needed changes. 0.4%

Where a human is still needed

Tasks where the model most often judged that a person remained necessary — a useful read on the current boundary, not a guarantee.

Provide current and prospective employees with information about policies, job duties, working conditions, wages, opportunities for promotion and employee benefits. 98.8%
Develop, administer and evaluate applicant tests. 97.0%
Advise managers on organizational policy matters such as equal employment opportunity and sexual harassment, and recommend needed changes. 94.3%
Analyze and modify compensation and benefits policies to establish competitive programs and ensure compliance with legal requirements. 92.9%

What people most often hand AI here

Example prompts phrased from the tasks people most often delegate to AI in this occupation (Anthropic Economic Index). Each shows the underlying measured task and its share of observed AI use. They are suggested phrasings of real tasks — starting points, not endorsed instructions.

  • Help me provide current and prospective employees with information about policies, job duties, working conditions, wages, opportunities for promotion and employee benefits.

    From: Provide current and prospective employees with information about policies, job duties, working conditions, wages, opportunities for promotion and employee benefits. · 1.6% of measured AI use · learning

  • Help me develop, administer and evaluate applicant tests.

    From: Develop, administer and evaluate applicant tests. · 1.0% of measured AI use · task iteration

  • Help me analyze and modify compensation and benefits policies to establish competitive programs and ensure compliance with legal requirements.

    From: Analyze and modify compensation and benefits policies to establish competitive programs and ensure compliance with legal requirements. · 0.7% of measured AI use · task iteration

  • Help me advise managers on organizational policy matters such as equal employment opportunity and sexual harassment, and recommend needed changes.

    From: Advise managers on organizational policy matters such as equal employment opportunity and sexual harassment, and recommend needed changes. · 0.4% of measured AI use

Tasks

All 26 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.

Work activities

Knowledge, skills & abilities

O*NET importance rating, from 1 (not important) to 5 (extremely important).

Knowledge

Personnel and Human Resources 4.9
English Language 4.3
Administration and Management 4.2
Customer and Personal Service 3.9
Education and Training 3.9
Law and Government 3.6

Abilities

Oral Expression 4.5
Oral Comprehension 4.4
Written Comprehension 4.4
Written Expression 4.1
Speech Clarity 4.1
Deductive Reasoning 4.0
Inductive Reasoning 4.0
Near Vision 4.0
Speech Recognition 4.0
Problem Sensitivity 3.9
Fluency of Ideas 3.8
Originality 3.8
Information Ordering 3.6
Selective Attention 3.5

Essential skills

Active Listening 4.4
Reading Comprehension 4.3
Speaking 4.3
Writing 4.1
Critical Thinking 4.0
Active Learning 4.0
Monitoring 4.0
Learning Strategies 3.8

Transferable skills

Management of Personnel Resources 4.3
Coordination 4.1
Social Perceptiveness 4.0
Complex Problem Solving 4.0
Judgment and Decision Making 4.0
Time Management 4.0
Negotiation 3.9
Instructing 3.9
Systems Evaluation 3.9
Persuasion 3.8
Service Orientation 3.8
Systems Analysis 3.6

Skills in demand

Skills employers ask for in job postings for this occupation (Lightcast), with whether each is a common or specialized skill.

Showing the top 40 of 53.

Tools & technology

Example Category
Microsoft Excel Spreadsheet software Hot technology In demand
Microsoft Office software Office suite software Hot technology In demand
Microsoft Outlook Electronic mail software Hot technology In demand
Microsoft PowerPoint Presentation software Hot technology In demand
Workday software Enterprise resource planning ERP software Hot technology In demand
Facebook Web page creation and editing software Hot technology
IBM SPSS Statistics Analytical or scientific software Hot technology
Intuit QuickBooks Accounting software Hot technology
Kronos Workforce Timekeeper Time accounting software Hot technology
Microsoft Access Data base user interface and query software Hot technology
Microsoft Project Project management software Hot technology
Microsoft Visio Process mapping and design software Hot technology
Microsoft Word Word processing software Hot technology
Oracle PeopleSoft Enterprise resource planning ERP software Hot technology
SAP software Enterprise resource planning ERP software Hot technology
Applicant tracking software Human resources software In demand
Oracle HRIS Human resources software In demand
AASoftTech Web Organization Chart Charting software
AccountantsWorld Payroll Relief Accounting software
ADP Enterprise HR Human resources software
ADP ezLaborManager Time accounting software
ADP HR/Benefits Solution Human resources software
ADP HR/Profile Human resources software
ADP Pay eXpert Time accounting software
ADP Workforce Now Human resources software
AllNetic Working Time Tracker Human resources software
Arrow Electronics N/Compass Human resources software
Atlas Business Solutions Staff Files Document management software
Authoria Adviser Human resources software
Automation Centre Personnel Tracker Data base user interface and query software
Ceridian Dayforce enterprise HCM Human resources software
Corel WordPerfect Office Suite Office suite software
Data Management TimeClock Plus Time accounting software
Defense Travel System Human resources software
Deltek Vision Enterprise resource planning ERP software
Exact Software Macola ES Labor Performance Time accounting software
Fidelity HR/Payroll Human resources software
Halogen e360 Human resources software
Halogen ePraisal Human resources software
Harpers Payroll Services HR la Carte Human resources software

Showing the top 40 of 102.

Work context

How characteristic each condition is of the job, on O*NET's 1–5 context scale (higher = more present in day-to-day work). Each condition links to how it varies across all occupations.

E-Mail 5.0
Telephone Conversations 4.8
Face-to-Face Discussions with Individuals and Within Teams 4.8
Contact With Others 4.7
Work With or Contribute to a Work Group or Team 4.5
Freedom to Make Decisions 4.3
Determine Tasks, Priorities and Goals 4.3
Spend Time Sitting 4.2
Frequency of Decision Making 4.1
Importance of Being Exact or Accurate 4.1
Conflict Situations 4.0
Indoors, Environmentally Controlled 4.0
Impact of Decisions on Co-workers or Company Results 4.0
Time Pressure 3.9
Coordinate or Lead Others in Accomplishing Work Activities 3.9
Written Letters and Memos 3.8
Work Outcomes and Results of Other Workers 3.6
Dealing With Unpleasant, Angry, or Discourteous People 3.6
Deal With External Customers or the Public in General 3.5
Health and Safety of Other Workers 3.5
Level of Competition 3.2
Importance of Repeating Same Tasks 3.2
Consequence of Error 3.0
Public Speaking 2.8
Physical Proximity 2.7
Degree of Automation 2.7
Spend Time Making Repetitive Motions 2.5
Spend Time Standing 2.3
Dealing with Violent or Physically Aggressive People 2.0
Exposed to Sounds, Noise Levels that are Distracting or Uncomfortable 2.0
In an Enclosed Vehicle or Operate Enclosed Equipment 1.9
Spend Time Walking or Running 1.9
Spend Time Using Your Hands to Handle, Control, or Feel Objects, Tools, or Controls 1.9
Indoors, Not Environmentally Controlled 1.7
Wear Common Protective or Safety Equipment such as Safety Shoes, Glasses, Gloves, Hearing Protection, Hard Hats, or Life Jackets 1.7
Exposed to Disease or Infections 1.7
Spend Time Bending or Twisting Your Body 1.6
Outdoors, Exposed to All Weather Conditions 1.6
Exposed to Extremely Bright or Inadequate Lighting Conditions 1.4
Outdoors, Under Cover 1.4

How to get in

Job zone
Zone 4 — Job Zone Four: Considerable Preparation Needed
Education
Most of these occupations require a four-year bachelor's degree, but some do not.
Typical entry-level education
Bachelor's degree · BLS, the typical path — not a requirement
Related experience
A considerable amount of work-related skill, knowledge, or experience is needed for these occupations. For example, an accountant must complete four years of college and work for several years in accounting to be considered qualified.
Preparation level
SVP (7.0 to < 8.0) — total schooling plus on-the-job experience.

What to study: Business, Management, Marketing, and Related Support Services , Communication, Journalism, and Related Programs , Psychology . Fields of study crosswalked to this occupation (NCES CIP–SOC), not a requirement.

Education of current workers

Share of people in this occupation at each level of education.

Bachelor's Degree 81.8%
Post-Baccalaureate Certificate 9.1%
Post-Secondary Certificate 4.5%
Master's Degree 4.5%

Interests & work styles

The interests and personal qualities O*NET associates with people who do this work.

Work styles

Dependability 9.0
Attention to Detail 8.0
Integrity 7.0
Cooperation 6.0
Social Orientation 5.0
Self-Control 4.0

Career interests (Holland / RIASEC)

Enterprising 7.0
Conventional 5.5
Social 3.9

Interest areas

Human Resources 6.9
Management/Administration 6.7
Professional Advising 5.0
Office Work 4.4
Business Initiatives 4.1
Public Speaking 3.8
Law 3.4

Wages & employment

U.S. · annual wages (BLS OEWS)

222k2024233k2034 (proj.)+5.0% · About average
Projected U.S. employment, 2024–2034 (BLS Employment Projections). A labor-market forecast for the occupation, not an AI-impact forecast.
10th percentile $83,790
25th percentile $105,590
Median (50th) $140,030
75th percentile $189,960
90th percentile
People employed 215,520

Industries that employ this occupation

Where these workers are employed, by number of jobs (national, BLS OEWS). Pay shown is the occupation's national median, not industry-specific.

Industry Workers National median pay
Professional, Scientific, and Technical Services · Sector 33,790 $163,970
Management of Companies and Enterprises · Sector 31,650 $163,180
Manufacturing · Sector 20,250 $137,570
Administrative and Support and Waste Management and Remediation Services · Sector 19,340 $118,700
Health Care and Social Assistance · Sector 18,810 $120,010
Finance and Insurance · Sector 16,370 $164,680
Educational Services · Sector 14,730 $128,020
Information · Sector 9,880 $196,770
Wholesale Trade · Sector 8,870 $154,930
Temporary Help Services · National industry 6,020 $99,410
Transportation and Warehousing · Sector 5,030 $126,800
Other Services (except Public Administration) · Sector 4,150 $133,370

Where this work is most concentrated

Industries where this occupation is far more common than in the economy as a whole. The location quotient is how many times more concentrated it is here (a value of 5 means five times its economy-wide share).

Industry Concentration Workers
Management of Companies and Enterprises · Sector 8.06× 31,650
Information · Sector 2.43× 9,880
Direct Health and Medical Insurance Carriers · National industry 2.31× 1,450
Professional, Scientific, and Technical Services · Sector 2.24× 33,790
Finance and Insurance · Sector 1.88× 16,370
Television Broadcasting Stations · National industry 1.87× 170
Research and Development in the Social Sciences and Humanities · National industry 1.65× 140
Engineering Services · National industry 1.63× 2,640

Part of the Management & Entrepreneurship and Public Service & Safety career clusters.

Exposure quadrant: AI task-overlap percentile vs Median pay Human Resources Managers sits at the 71st percentile of AI task-overlap and the 97th percentile of median pay, placed here against 12 adjacent occupations on the same two axes. Lower overlap · higher pay Higher overlap · higher pay Higher overlap · lower pay Lower overlap · lower pay Human Resources Managers Labor Relations Specialists Social and Community Service Managers First-Line Supervisors of Office and Administrative Support Workers Project Management Specialists Human Resources Specialists Human Resources Assistants, Except Payroll and Timekeeping Industrial-Organizational Psychologists AI task-overlap percentile → ↑ Median pay
AI task-overlap percentile (horizontal) vs. median-pay percentile (vertical), across all scored occupations. This occupation is highlighted; related occupations are plotted alongside it. Overlap measures shared tasks with AI, not automation.

Side-by-side comparisons place two occupations’ pay, preparation, skills, and AI exposure on the same page — same data, same scale, no forecast.

What you can do with this

Options the data surfaces for Human Resources Managers — not advice or a forecast. Each is a real cross-link you can follow into the evidence.

Skills that travel

Capabilities this work builds that are used across many other occupations.

Paths in

How people typically prepare for this work.

Zoom out

On the global GenAI exposure gradient this work sits around the 66th percentile of 427 international occupations.

Write a report on thisheadline · factoids · citation

Human Resources Managers show 71st-percentile AI task overlap — and about 17,900 annual U.S. openings

  • Human Resources Managers rank in the 71st percentile (High band) for AI task overlap across U.S. occupations — a measure of how much of the work today's AI can attempt, not how much is automated.Eloundou et al. (GPTs are GPTs) + Felten AIOE
  • The occupation is projected to see about 17,900 U.S. job openings per year (2024–34), counting growth and replacement — a labor-demand projection made independently of AI.BLS Employment Projections 2024–34
  • BLS projects employment to be about average (+5%) from 2024 to 2034.BLS Employment Projections 2024–34
  • Median annual pay is $140,030, across about 215,520 U.S. workers.BLS OEWS (May 2024)
  • Of the AI use actually observed for this work, 48% looks like augmentation (drafting, iterating, checking) rather than hands-off automation — from a Claude.ai usage sample, not a census.2026-01-15-v4-plus-2025-03-27-v2
Copy the whole kit
Human Resources Managers show 71st-percentile AI task overlap — and about 17,900 annual U.S. openings

• Human Resources Managers rank in the 71st percentile (High band) for AI task overlap across U.S. occupations — a measure of how much of the work today's AI can attempt, not how much is automated. (Eloundou et al. (GPTs are GPTs) + Felten AIOE)
• The occupation is projected to see about 17,900 U.S. job openings per year (2024–34), counting growth and replacement — a labor-demand projection made independently of AI. (BLS Employment Projections 2024–34)
• BLS projects employment to be about average (+5%) from 2024 to 2034. (BLS Employment Projections 2024–34)
• Median annual pay is $140,030, across about 215,520 U.S. workers. (BLS OEWS (May 2024))
• Of the AI use actually observed for this work, 48% looks like augmentation (drafting, iterating, checking) rather than hands-off automation — from a Claude.ai usage sample, not a census. (2026-01-15-v4-plus-2025-03-27-v2)

Source: Singulariki — "Human Resources Managers". https://singulariki.com/roles/role-11-3121-00
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.

AssetsShare imageMethodology & sourcesPress & newsroomThe newsroom

Every line is built only from figures this page already shows and cites. AI task overlap means what today's AI can attempt — not automation, job loss, or a forecast.

Sources for this page

Every figure above traces to a named public dataset and the exact release below — not hand-written opinion. See the full methodology for what each measure does and does not mean.

Data compiled June 2, 2026. Figures are estimates, not advice.

Cite this page
Plain

Singulariki. "Human Resources Managers." Singulariki: a source-backed encyclopedia of work. Built from O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026. https://singulariki.com/roles/role-11-3121-00

APA

Singulariki. (2026). Human Resources Managers. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-11-3121-00

BibTeX
@misc{singulariki-role-11-3121-00,
  title  = {Human Resources Managers},
  author = {{Singulariki}},
  year   = {2026},
  note   = {O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026},
  url    = {https://singulariki.com/roles/role-11-3121-00}
}

Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.

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