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Wind Energy Engineers

Design underground or overhead wind farm collector systems and prepare and develop site specifications.

Also known as: Engineer · Project Engineer · Turbine Engineer · Utility Engineer · Wind Farm Designer · Wind Farm Engineer

AI Task Exposure Score

High exposure

More exposed than 58% of 968 occupations · Rank #374 (1 = most exposed)

This score estimates how exposed the tasks in a role are to current and near-term AI capabilities. It does not predict whether a specific person will lose a job.

Your free role snapshot

Start with the work, not the headline

This occupation baseline already contains different kinds of work. These are the two ends of its current task range and one useful action you can take now.

Most exposed task

Write reports to document wind farm collector system test results.

Augmentable 60/100 exposure

Most durable task

Test wind turbine equipment to determine effects of stress or fatigue.

Durable 20/100 exposure

Useful next step

Make one change to the task mix

Compare one real week with the exposed tasks, test one supervised delegation, and redirect the saved time toward more durable work.

Want this mapped to your actual week? Know what to strengthen, what to delegate to AI with review, and what to do over the next 7, 30, and 90 days.

Build my 7/30/90-day action plan — $9

Most exposed tasks

No task is classified fully automatable in this release. The highest-exposure task relative to this role is shown in the free snapshot above; the assistive work is detailed next.

Augmentable tasks

Work where AI assists rather than replaces — the productivity frontier of this role.

  • Write reports to document wind farm collector system test results.60
  • Create or maintain wind farm layouts, schematics, or other visual documentation for wind farms.55
  • Create models to optimize the layout of wind farm access roads, crane pads, crane paths, collection systems, substations, switchyards, or transmission lines.50

Most durable tasks

Lowest exposure — typically judgment, relationships, physical presence, or accountability. This is the human moat.

  • Test wind turbine components, using mechanical or electronic testing equipment.20
  • Test wind turbine equipment to determine effects of stress or fatigue.20
  • Monitor wind farm construction to ensure compliance with regulatory standards or environmental requirements.22

Task exposure values and classifications are published, versioned estimates audited against the anchored rubric. This page reads them from the data release rather than generating them at request time. Bars show exposure contribution relative to this role’s task mix.

What this means

A score of 38 puts Wind Energy Engineers in the third quartile of analyzed occupations. In practice, exposure this high is about the mix: 0 of 16 analyzed tasks lean automatable, 9 augmentable, and 7 durable. The useful question isn’t “will AI take this job” — it’s which tasks go first, which get faster, and where to reposition time. That’s what the personalized report maps against your actual week.

Lower-exposure adjacent roles

No adjacent role in the current data release is at least 10 points lower with ≥50% skill overlap — we don’t label anything “safer” unless the data supports it.

Labor-market context

  • $122,930median wage
  • 154,070employed
  • 9,300annual openings
  • +2.1%projected growth

Context only — labor statistics are not inputs to the exposure score. See methodology.

Turn your actual week into a plan

Know which work to strengthen, what to delegate to AI with review, and what to do over the next 7, 30, and 90 days. Your $9 plan includes a confidence-rated personal score, task matrix, human moat, and only genuinely lower-exposure adjacent roles.

Build my 7/30/90-day action plan — $9

Related roles

Adjacent by skills or family — no exposure claim implied.

How this score was calculated

The score is the plain average of the AI-exposure values of this role’s 16 analyzed tasks (equal task weights in this release — no hidden factors):

  • Augmentable 9 tasks, averaging 48/100 exposure
  • Durable 7 tasks, averaging 25/100 exposure

score = (9×48 + 7×25) ÷ 16 ≈ 38

Every task’s exposure value was scored against a published anchored rubric that scores tasks as actually performed — physical, in-person, and accountability requirements included (data release 2026.07.12-r2). The band (High) is a corpus quartile; the percentile is tie-aware across all 968 occupations.

FAQ — Wind Energy Engineers

Will AI replace Wind Energy Engineers?
This score cannot predict whether this occupation or any individual job will be replaced. It shows which tasks current and near-term AI can perform or accelerate, which tasks remain more durable, and where a worker can adapt. Employer decisions, demand, regulation, and how the role changes are outside the score.
What does a score of 38 mean for a Wind Energy Engineers?
It means that, weighted across the 16 tasks we analyzed for this role, the task mix sits at 38 on a 0–100 exposure scale — in the third quartile of analyzed occupations. It measures task exposure to current and near-term AI capabilities, not the probability of losing a job.
Which tasks in this role are most exposed to AI?
This role has no strongly automatable task in the current data release.
Which parts of this job are most durable?
The most durable responsibilities are: Test wind turbine components, using mechanical or electronic testing equipment; Test wind turbine equipment to determine effects of stress or fatigue; Monitor wind farm construction to ensure compliance with regulatory standards or environmental requirements. Durable tasks typically depend on judgment, relationships, physical presence, or accountability.
Is this score personalized to me?
No — this page shows the occupation-level baseline. Two people with the same title often do different work. The $9 personalized report recalculates the score from the tasks you actually do and builds a concrete 7/30/90-day plan around them.

Score version jr-v1 · data release 2026.07.12-r2 · updated 2026-07-13 · baseline mapping: 16 of 16 tasks carry source-level provenance · methodology