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Management & Leadership · Updated Aug 2026

Wind Energy Operations Managers

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

JVS 2.0.0-phase4b
AI Exposure
60/100
High

How much of this occupation’s work can be materially affected by current AI systems.

Replacement Risk
44/100
Moderate

How likely exposure is to translate into reduced human demand.

Includes provisional estimates for AI adoption pressure and labour-market resilience. How this is measured

Evidence quality
Confidence81/100
Task coverage82%

Confidence reflects task coverage, mapping and capability-evidence quality, and how much of the score rests on provisional inputs.

Task-level evidence

What is driving the score?

Occupation scores are built from the task mix—not a single prediction about a job title.

JVS 2.0.0-phase4b
TaskImportanceAI impactExposure
Supervise employees or subcontractors to ensure quality of work or adherence to safety regulations or policies.High
68
Track and maintain records for wind operations, such as site performance, downtime events, parts usage, or substation events.High
67
Oversee the maintenance of wind field equipment or structures, such as towers, transformers, electrical collector systems, roadways, or other site assets.High
64
Train or coordinate the training of employees in operations, safety, environmental issues, or technical issues.High
68
Maintain operations records, such as work orders, site inspection forms, or other documentation.High
51
Develop relationships and communicate with customers, site managers, developers, land owners, authorities, utility representatives, or residents.High
62
Provide technical support to wind field customers, employees, or subcontractors.High
51
Order parts, tools, or equipment needed to maintain, restore, or improve wind field operations.Medium
63
Establish goals, objectives, or priorities for wind field operations.Medium
66
Develop processes or procedures for wind operations, including transitioning from construction to commercial operations.Medium
66
Recruit or select wind operations employees, contractors, or subcontractors.High
68
Estimate costs associated with operations, including repairs or preventive maintenance.Medium
21
Most exposed

Where AI can do more

Routine, digitized, and highly repeatable tasks face the greatest pressure.

  1. Supervise employees or subcontractors to ensure quality of work or adherence to safety regulations or policies.68
  2. Train or coordinate the training of employees in operations, safety, environmental issues, or technical issues.68
  3. Recruit or select wind operations employees, contractors, or subcontractors.68
  4. Track and maintain records for wind operations, such as site performance, downtime events, parts usage, or substation events.67
Hardest to automate

Where people still matter

These tasks score lowest on automation feasibility—physical presence, judgement, accountability and real-world variability all resist end-to-end automation.

  1. Estimate costs associated with operations, including repairs or preventive maintenance.01
  2. Track and maintain records for wind operations, such as site performance, downtime events, parts usage, or substation events.02
  3. Oversee the maintenance of wind field equipment or structures, such as towers, transformers, electrical collector systems, roadways, or other site assets.03
  4. Maintain operations records, such as work orders, site inspection forms, or other documentation.04
  5. Develop relationships and communicate with customers, site managers, developers, land owners, authorities, utility representatives, or residents.05
Where else this work leads

Related occupations

Occupations O*NET links to this one. Relatedness reflects shared work, not a claim that these roles are safer.

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Beyond AI capability

Adoption and labour-market outlook

Structural factors are kept separate from raw capability so you can see what actually resists automation. Adoption pressure and labour-market resilience are still provisional models—25% of this occupation’s replacement-risk weight rests on them.

Human dependency72
Physical dependency64
Adoption pressure62
Labour-market resilience75
Methodology & sources

O*NET 30.3 occupational data interpreted through the JobsVsAI capability, automation and structural-constraint models.

Confidence81/100
CalculatedAug 21, 2026
Read methodology →