# Wind Energy Operations Managers

> Manage wind field operations, including personnel, maintenance activities, financial activities, and planning.

- **SOC code:** 11-9199.09
- **Canonical URL:** https://singulariki.com/roles/role-11-9199-09
- **Also known as:** Site Manager, Wind Operations Supervisor, Wind Plant Manager, Wind Site Manager, Service Site Manager, Turbine Site Manager, Wind Facilities Manager, Wind Plant Operations 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):
- Supervise employees or subcontractors to ensure quality of work or adherence to safety regulations or policies.
- Train or coordinate the training of employees in operations, safety, environmental issues, or technical issues.
- Track and maintain records for wind operations, such as site performance, downtime events, parts usage, or substation events.
- Oversee the maintenance of wind field equipment or structures, such as towers, transformers, electrical collector systems, roadways, or other site assets.
- Prepare wind field operational budgets.
- Develop relationships and communicate with customers, site managers, developers, land owners, authorities, utility representatives, or residents.
- Maintain operations records, such as work orders, site inspection forms, or other documentation.
- Provide technical support to wind field customers, employees, or subcontractors.
- Recruit or select wind operations employees, contractors, or subcontractors.
- Estimate costs associated with operations, including repairs or preventive maintenance.
- Monitor and maintain records of daily facility operations.
- Establish goals, objectives, or priorities for wind field operations.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Oral Expression _(ability)_
- Administration and Management _(knowledge)_
- Active Listening _(essential_skill)_
- Oral Comprehension _(ability)_
- Written Comprehension _(ability)_
- Written Expression _(ability)_
- Problem Sensitivity _(ability)_
- Speech Recognition _(ability)_
- Speech Clarity _(ability)_
- Mechanical _(knowledge)_
- Reading Comprehension _(essential_skill)_
- Speaking _(essential_skill)_

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

**Tools & technology:**
- Autodesk AutoCAD _(hot technology)_
- Microsoft Excel _(hot technology)_
- Microsoft Office software _(hot technology)_
- Microsoft Outlook _(hot technology)_
- Microsoft PowerPoint _(hot technology)_
- Microsoft Project _(hot technology)_
- Microsoft Word _(hot technology)_
- SAP software _(hot technology)_
- Computerized diagnostic software
- Computerized maintenance management system CMMS
- Employee scheduling software
- Gensuite

## AI exposure & outlook

- **AI task-overlap index:** 62nd percentile (Moderate) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 72nd percentile (High) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 67th percentile (High) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 49th percentile (Moderate) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 37th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** no — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** 4.5% growth (About average); 106.7k annual openings; 1,333.7k → 1,393.5k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $136,550; 630,980 employed.

## 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-11-9199-09_