# Human Resources Managers

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

- **SOC code:** 11-3121.00
- **Canonical URL:** https://singulariki.com/roles/role-11-3121-00
- **Also known as:** 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
- **Frame:** "AI exposure" means task overlap (how codifiable the work is), not jobs lost or a forecast. Every figure below is traced to a named public dataset.

## What this work is

**Core tasks** (O*NET):
- Serve as a link between management and employees by handling questions, interpreting and administering contracts and helping resolve work-related problems.
- Plan, direct, supervise, and coordinate work activities of subordinates and staff relating to employment, compensation, labor relations, and employee relations.
- Perform difficult staffing duties, including dealing with understaffing, refereeing disputes, firing employees, and administering disciplinary procedures.
- Represent organization at personnel-related hearings and investigations.
- Negotiate bargaining agreements and help interpret labor contracts.
- Advise managers on organizational policy matters, such as equal employment opportunity and sexual harassment, and recommend needed changes.
- Plan and conduct new employee orientation to foster positive attitude toward organizational objectives.
- Identify staff vacancies and recruit, interview, and select applicants.
- Analyze and modify compensation and benefits policies to establish competitive programs and ensure compliance with legal requirements.
- 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.
- Investigate and report on industrial accidents for insurance carriers.
- Administer compensation, benefits, and performance management systems, and safety and recreation programs.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Personnel and Human Resources _(knowledge)_
- Oral Expression _(ability)_
- Active Listening _(essential_skill)_
- Oral Comprehension _(ability)_
- Written Comprehension _(ability)_
- English Language _(knowledge)_
- Reading Comprehension _(essential_skill)_
- Speaking _(essential_skill)_
- Management of Personnel Resources _(transferable_skill)_
- Administration and Management _(knowledge)_
- Writing _(essential_skill)_
- Coordination _(transferable_skill)_

**Skills in demand:**
- Active Listening _(Common Skill)_
- English Language _(Common Skill)_
- Reading Comprehension _(Common Skill)_
- Writing _(Common Skill)_
- Time Management _(Common Skill)_
- Speech Recognition _(Specialized Skill)_
- Social Perceptiveness _(Common Skill)_
- Inductive Reasoning _(Common Skill)_
- Deductive Reasoning _(Common Skill)_
- Critical Thinking _(Common Skill)_
- Complex Problem Solving _(Common Skill)_
- Active Learning _(Common Skill)_

**Tools & technology:**
- Microsoft Excel _(hot technology, in demand)_
- Microsoft Office software _(hot technology, in demand)_
- Microsoft Outlook _(hot technology, in demand)_
- Microsoft PowerPoint _(hot technology, in demand)_
- Workday software _(hot technology, in demand)_
- Facebook _(hot technology)_
- IBM SPSS Statistics _(hot technology)_
- Intuit QuickBooks _(hot technology)_
- Kronos Workforce Timekeeper _(hot technology)_
- Microsoft Access _(hot technology)_
- Microsoft Project _(hot technology)_
- Microsoft Visio _(hot technology)_

## AI exposure & outlook

- **AI task-overlap index:** 71st percentile (High) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 88th percentile (High) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 81st percentile (High) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 44th percentile (Moderate) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 4th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** yes — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** 5.0% growth (About average); 17.9k annual openings; 221.9k → 233k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $140,030; 215,520 employed.

## How people actually use AI here

Anthropic Economic Index — measured AI conversations mapped to this occupation's tasks:

- **Automation vs augmentation:** 33% automation, 48% augmentation (usage-weighted).
- **Autonomy median:** 4.0 (higher = AI acts more independently).
- **Dominant collaboration mode:** directive.

**Tasks most handed to AI here:**
- 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)_
- Develop, administer and evaluate applicant tests. _(1.0% of measured AI use; task iteration)_
- 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)_
- Advise managers on organizational policy matters such as equal employment opportunity and sexual harassment, and recommend needed changes. _(0.4% of measured AI use)_

**Example prompts (honest phrasings of the tasks above — 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.
- Help me develop, administer and evaluate applicant tests.
- Help me analyze and modify compensation and benefits policies to establish competitive programs and ensure compliance with legal requirements.
- Help me advise managers on organizational policy matters such as equal employment opportunity and sexual harassment, and recommend needed changes.

## Sources

- **O*NET** (30.3) — U.S. Department of Labor / National Center for O*NET Development. https://www.onetcenter.org/database.html
- **BLS Occupational Employment and Wage Statistics (OEWS)** (May 2024) — U.S. Bureau of Labor Statistics. https://www.bls.gov/oes/
- **BLS Employment Projections** (2024–2034) — U.S. Bureau of Labor Statistics. https://www.bls.gov/emp/
- **Anthropic Economic Index** (v4 (2026-01-15) + v2 (2025-03-27)) — Anthropic. https://www.anthropic.com/economic-index
- **Microsoft “Working with AI”** (working-with-ai) — Microsoft Research. https://www.microsoft.com/en-us/research/
- **“GPTs are GPTs” (Eloundou et al.)** (arXiv 2303.10130) — OpenAI / academic. https://arxiv.org/abs/2303.10130
- **AI Occupational Exposure (AIOE)** (Felten, Raj & Seamans) — academic. https://github.com/AIOE-Data/AIOE
- **Frey & Osborne (2013)** (frey-osborne-automation) — academic. https://www.oxfordmartin.ox.ac.uk/publications/the-future-of-employment/
- **Dingel & Neiman (2020)** (dingel-neiman-workathome) — academic. https://github.com/jdingel/DingelNeiman-workathome

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_Generated from Singulariki's joined dataset; data snapshot 2026-06-02T21:00:32.945303+00:00. https://singulariki.com/roles/role-11-3121-00_