Occupation · SOC 11-9199.10
Lead or manage the development and evaluation of potential wind energy business opportunities, including environmental studies, permitting, and proposals. May also manage construction of projects.
Also called: Business Development Director · Business Development Manager · Development Director · Development Manager · Project Development Leader · Renewable Project Management and Construction Director · Energy Director · Energy Project Director · Environmental Projects Advisor · Renewable Energy Civil Foreman · Renewable Energy Field Coordinator · Renewable Energy Project Handler
Job family: Management Occupations
A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch
/roles/role-11-9199-10/context.md directly.
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.
Task areas where a human was still judged necessary in a large share of observed conversations — not a safety ruling, an observed-need signal.
The capabilities O*NET rates most important for this occupation — the human ground the work is built on.
See all skills →Independent published positions, read together — not a forecast.
73rd-percentile task overlap — yet about 106,700 openings a year (+4.5% projected, BLS) . What exposure means →
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.
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 | 72nd | 1.0 | |
| LLM task exposure, γ (OpenAI / Eloundou) High | 95th | 1.0 | |
| AI assistant applicability (Microsoft) Moderate | 49th | 0.1 |
OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.1), with simple added tooling (β 0.5), and including AI-powered software (γ 1.0). 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.
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 0.3 · 37th percentile among occupations · Moderate
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.
| Create wind energy project plans, including project scope, goals, tasks, resources, schedules, costs, contingencies, or other project information. | 0.3% | |
| Provide verbal or written project status reports to project teams, management, subcontractors, customers, or owners. | 0.2% |
Independent U.S. Bureau of Labor Statistics employment projection for 2024–2034 — a labor-market forecast, not an AI-impact forecast.
| Outlook | About average · +4.5% by 2034 |
| Projected annual openings | 106,700 |
| Employment 2024 → 2034 | 1,333,700 → 1,393,500 |
“Annual openings” counts new jobs plus replacements for workers who leave the occupation, so it can be large even when growth is modest.
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 6 occupations below. Exposure here means how much of the work's tasks today's AI can attempt — task overlap, not automation, adoption, or jobs lost.
| International occupation (ISCO-08) | Task exposure (2025) | Most tasks fall in |
|---|---|---|
| Business Services and Administration Managers Not Elsewhere Classified · 1219 | 42% | Gradient 2 |
| Professional Services Managers Not Elsewhere Classified · 1349 | 38% | Minimal |
| Senior Officials of Special-interest Organizations · 1114 | 37% | Minimal |
| Policy and Planning Managers · 1213 | 36% | Not exposed |
| Mining Managers · 1322 | 35% | Minimal |
| Sports, Recreation and Cultural Centre Managers · 1431 | 32% | 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.
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.
| Typical AI autonomy | 4.0 / 5 · higher = AI acts more independently |
| Used for work (vs. personal / coursework) | 51.5% |
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 |
|---|---|---|
| Create wind energy project plans, including project scope, goals, tasks, resources, schedules, costs, contingencies, or other project information. | — | 0.3% |
Tasks where the model most often judged that a person remained necessary — a useful read on the current boundary, not a guarantee.
| Create wind energy project plans, including project scope, goals, tasks, resources, schedules, costs, contingencies, or other project information. | 81.8% |
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 create wind energy project plans, including project scope, goals, tasks, resources, schedules, costs, contingencies, or other project information. From: Create wind energy project plans, including project scope, goals, tasks, resources, schedules, costs, contingencies, or other project information. · 0.3% of measured AI use
All 15 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.
O*NET importance rating, from 1 (not important) to 5 (extremely important).
| Critical Thinking | 4.0 | |
| Reading Comprehension | 3.9 | |
| Writing | 3.9 | |
| Speaking | 3.9 | |
| Active Listening | 3.8 | |
| Monitoring | 3.5 | |
| Active Learning | 3.4 |
| Oral Comprehension | 4.0 | |
| Written Comprehension | 4.0 | |
| Deductive Reasoning | 4.0 | |
| Inductive Reasoning | 4.0 | |
| Oral Expression | 3.9 | |
| Written Expression | 3.9 | |
| Problem Sensitivity | 3.9 | |
| Speech Recognition | 3.9 | |
| Speech Clarity | 3.9 | |
| Near Vision | 3.8 | |
| Information Ordering | 3.5 | |
| Category Flexibility | 3.3 | |
| Fluency of Ideas | 3.1 | |
| Mathematical Reasoning | 3.1 | |
| Flexibility of Closure | 3.1 |
Skills employers ask for in job postings for this occupation (Lightcast), with whether each is a common or specialized skill.
| Example | Category | |
|---|---|---|
| Autodesk AutoCAD | Computer aided design CAD software | Hot technology |
| ESRI ArcGIS software | Geographic information system | Hot technology |
| Microsoft Excel | Spreadsheet software | Hot technology |
| Microsoft Office software | Office suite software | Hot technology |
| Microsoft Outlook | Electronic mail software | Hot technology |
| Microsoft PowerPoint | Presentation 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 |
| SAP software | Enterprise resource planning ERP software | Hot technology |
| Oracle Primavera Systems | Project management software | |
| Web browser software | Internet browser software | |
| Web conferencing software | Video conferencing software |
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.
What to study: Business, Management, Marketing, and Related Support Services , Communication, Journalism, and Related Programs , Computer and Information Sciences and Support Services , Health Professions and Related Programs , History , Homeland Security, Law Enforcement, Firefighting and Related Protective Services , Library Science , Multi/Interdisciplinary Studies , Natural Resources and Conservation , Psychology , Public Administration and Social Service Professions , Social Sciences , Theology and Religious Vocations , Visual and Performing Arts . Fields of study crosswalked to this occupation (NCES CIP–SOC), not a requirement.
Share of people in this occupation at each level of education.
| Bachelor's Degree | 66.8% | |
| Associate's Degree (or other 2-year degree) | 18.3% | |
| Master's Degree | 12.3% | |
| Post-Baccalaureate Certificate | 2.6% |
The interests and personal qualities O*NET associates with people who do this work.
| Enterprising | 6.7 | |
| Conventional | 4.8 | |
| Investigative | 3.9 | |
| Realistic | 3.4 | |
| Social | 2.4 | |
| Artistic | 1.7 |
U.S. · annual wages (BLS OEWS)
| 10th percentile | $68,860 |
| 25th percentile | $100,010 |
| Median (50th) | $136,550 |
| 75th percentile | $179,190 |
| 90th percentile | $227,590 |
| People employed | 630,980 |
Wages and employment are reported by BLS for the broader occupation group this specialty belongs to (SOC 11-9199), not for the specialty alone.
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 | 94,490 | $164,060 |
| Management of Companies and Enterprises · Sector | 50,980 | $163,830 |
| Manufacturing · Sector | 46,390 | $160,640 |
| Finance and Insurance · Sector | 44,890 | $162,780 |
| Information · Sector | 38,680 | $167,740 |
| Educational Services · Sector | 32,840 | $102,450 |
| Administrative and Support and Waste Management and Remediation Services · Sector | 32,500 | $109,990 |
| Health Care and Social Assistance · Sector | 31,360 | $108,810 |
| Wholesale Trade · Sector | 25,860 | $137,780 |
| Construction · Sector | 19,840 | $110,040 |
| Other Services (except Public Administration) · Sector | 19,110 | $111,320 |
| Retail Trade · Sector | 13,510 | $95,720 |
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 |
|---|---|---|
| Wind Electric Power Generation · National industry | 9.11× | 370 |
| Research and Development in the Social Sciences and Humanities · National industry | 6.07× | 1,510 |
| Management of Companies and Enterprises · Sector | 4.43× | 50,980 |
| Direct Health and Medical Insurance Carriers · National industry | 3.92× | 7,200 |
| Solar Electric Power Generation · National industry | 3.33× | 190 |
| Information · Sector | 3.25× | 38,680 |
| Nuclear Electric Power Generation · National industry | 2.7× | 410 |
| Labor Unions and Similar Labor Organizations · National industry | 2.65× | 1,150 |
Part of the Arts, Entertainment, & Design , Management & Entrepreneurship and Public Service & Safety career clusters.
Side-by-side comparisons place two occupations’ pay, preparation, skills, and AI exposure on the same page — same data, same scale, no forecast.
Options the data surfaces for Wind Energy Development Managers — not advice or a forecast. Each is a real cross-link you can follow into the evidence.
Capabilities this work builds that are used across many other occupations.
Occupations O*NET rates as related — the nearby moves on the map.
How people typically prepare for this work.
On the global GenAI exposure gradient this work sits around the 68th percentile of 427 international occupations.
Wind Energy Development Managers show 73rd-percentile AI task overlap — and about 106,700 annual U.S. openings
Wind Energy Development Managers show 73rd-percentile AI task overlap — and about 106,700 annual U.S. openings • Wind Energy Development Managers rank in the 73rd 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 106,700 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 (+4.5%) from 2024 to 2034. (BLS Employment Projections 2024–34) • Median annual pay is $136,550, across about 630,980 U.S. workers. (BLS OEWS (May 2024)) Source: Singulariki — "Wind Energy Development Managers". https://singulariki.com/roles/role-11-9199-10 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.
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.
Singulariki. "Wind Energy Development 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-11-9199-10
Singulariki. (2026). Wind Energy Development Managers. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-11-9199-10
@misc{singulariki-role-11-9199-10,
title = {Wind Energy Development 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-11-9199-10}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.