EXPOSED
The core of this job — climbing 300 feet inside a nacelle, torquing bolts to spec, swapping pitch motors, replacing gearbox oil, and troubleshooting hydraulic and 690V electrical faults in a swaying tower — is about as robot-proof as work gets today. What AI does take is the analytical layer: SCADA vibration and thermal data interpretation, fault-code triage, predictive maintenance scheduling, and the service reports techs write up after each climb. Score is held down not by automation risk but by weak regulatory and relationship moats: no state license gates the trade, and the customer is an asset-management office, not a person who asks for you by name.
Headcount grew steadily across the period.
Median pay $52,910 → $64,120 -3.1% in real terms
This line is counted by the Bureau of Labor Statistics — the one figure on this page that isn't a judgement of ours. Headcount moves on demand, offshoring, demographics and the business cycle, and automation is one term among several, often not the loudest.
So a falling line is not evidence that AI did it, and a rising one is not evidence that it won't. Both happen in this register: some occupations resist automation and shrink anyway, others are highly automatable and keep growing. The marked year is 2020.
BLS projection, 2024–2034
+49.9%
Percentage only. The projection counts a different population from the 9,980 above — it includes self-employed workers, which for this occupation is most of them, so the two headcounts are not comparable.
Growing, and only partly exposed
The BLS expects +49.9% more of these jobs by 2034, and at 61/100 the work is only partly exposed — some tasks are automatable, the core of the job is not. Nothing here is in tension.
Different clocks. The score is what current AI could do to this work today. The projection is how many of these jobs will exist in 2034. Everything between the two — how fast employers actually adopt, whether demand grows in the meantime — is why they can point opposite ways without either being wrong.
~2,300 openings a year on average, including replacing people who leave.
WindsmithTroubleshooterWind TechnicianEnergy TechnicianService TechnicianTurbine TechnicianWindmill TechnicianWind Energy MechanicWind Plant TechnicianWind Power TechnicianWind Turbine MechanicWind Turbine OperatorWind Energy TechnicianWind Turbine InstallerWind Turbine TechnicianField Service TechnicianTroubleshooting TechnicianRenewable Energy SpecialistRenewable Energy TechnicianSmall Wind Energy InstallerWind Farm Support SpecialistWind Commissioning TechnicianWind Energy Systems InstallerOnsite Technician (Onsite Tech)
Holding it up: embodiment . Weakest point: liability shield .
Tasks largely resist digitisation Pulling a slip ring, re-torquing yaw bolts with a 3,000 ft-lb hydraulic wrench, and rope-accessing a leading-edge blade repair in a nacelle that never sits still cannot be done remotely or by a drone — the 16 rather than 19 reflects that the diagnostic half of your day (reading SCADA vibration trends, deciding which fault code is real) is already being pre-chewed by condition-monitoring software before you leave the ground.
Hands-on in uncontrolled environments You work 250-400 feet up in a confined nacelle, in wind, cold, and grease, hauling tools by winch and doing fall-arrest transitions on a ladder — this is the ceiling case for physicality, and no controlled-environment carve-out applies.
Certification preferred, not legally required Nothing gates entry but employer-required GWO, OSHA 1910.269, NFPA 70E, and confined-space/rescue certs that the site or OEM demands; the turbine owner and the OEM engineer carry the liability for the asset, so you get 5 for training that can be revoked, not a license someone can sue you over personally.
Meaningful discretion Deciding whether a bearing temperature excursion means run-to-scheduled or curtail the unit now, and whether to lock out a machine over a supervisor's production pressure, is real discretion with millions in downtime attached — capped at 12 because OEM service bulletins, torque specs, and LOTO procedures dictate most of the actual work steps.
The verdict above describes this occupation as a whole. Almost nobody does the typical version of a job — tick what's actually in your week and see how your own mix sits.
Your task mix speaks to task resistance (16/20 here) — how much of the day's work current AI already does. That is the dimension the boxes above are about.
It cannot move the other three. Liability shield (5/20) is whether the law requires a licensed human to sign. Trust premium (8/20) is whether buyers specifically pay for a person. Judgment and accountability (12/20) is whether the role exists to own consequential calls. Those are facts about the occupation's standing, not about which tasks are in your week — a paralegal who does only trial exhibits still holds no licence. Together they are 25 of this occupation's 61 points (41%).
Embodiment (20/20) is also a property of the work rather than the worker, but we don't tag individual tasks as physical or not, so the picker can't tell you anything about it. That's a limit of this tool, not a claim.
Did we get the list right? Tell us what's missing — the tasks are written from the outside, and you're reading this from the inside.
Ship Engineers SAFE
The moves above are yours to make. This is the other half: what would have to change in the world for the occupation itself to score higher. None of it is in any one person's gift, but it is where the floor actually comes from. Scores here are not a one-way ratchet. Only two of the five dimensions — task resistance and embodiment — track what machines can do. The other three track law, what buyers will pay for, and who is answerable, and those move in both directions, often in response to the same pressure AI creates. If every lever below landed, this occupation would score around 76/100 — SAFE.
Insurer/warranty-driven sign-off: OEM warranty terms (Vestas, GE Vernova, Siemens Gamesa) and turbine property insurers requiring a named certified technician (GWO Advanced Rescue, OEM torque-certification) to attest to bolt-torque and blade-repair records, so that an unsigned or AI-generated record voids coverage. Already partly in motion via GWO certification schemes and post-2019 gearbox/blade claim tightening.
Task-mix shift as SCADA analytics absorbs the routine tier: if predictive maintenance eliminates scheduled inspection climbs, the remaining work concentrates in unplanned major-component exchange, blade composite repair, and diagnosing faults the model flagged wrongly — a genuine judgment tier. Watch for O&M contracts priced per-event rather than per-scheduled-visit.
A state or federal rule making high-voltage wind work a licensed electrical trade — e.g. states extending journeyman/master electrician licensure to the 690V nacelle side rather than exempting generation equipment, or OSHA adopting a wind-specific standard (currently wind O&M is regulated only via general industry/1910 subpart S and fall-protection rules) requiring a named qualified person to sign off on lockout/tagout and energized work permits with personal liability. IBEW and IREC have pushed generation-side licensure carve-outs before.
Formalizing the technician's authority to refuse or halt: a union contract or company safety policy giving the lead tech unilateral, documented power to declare a turbine unsafe to enter (wind speed, icing, arc-flash risk) and to override a remote operations center's dispatch order. Offshore wind (Vineyard, Revolution) is importing this from North Sea marine practice.
The limit. Trust premium has no realistic route: the buyer is an asset-management or OEM service desk procuring crews under fleet-wide O&M contracts, and no individual technician is requested by name. Embodiment is already maxed at 20 and cannot rise. Realistic ceiling is roughly the mid-70s, and it comes almost entirely from licensure and warranty-attestation moats, not from anything about the physical work.
| Houston-Pasadena-The Woodlands, TX | 1,120 | $64,050 +0% |
| Dallas-Fort Worth-Arlington, TX | 400 | $57,890 -10% |
| Denver-Aurora-Centennial, CO | 160 | $74,740 +17% |
| Austin-Round Rock-San Marcos, TX | 130 | $61,930 -3% |
| Sioux Falls, SD-MN | 100 | $62,650 -2% |
| Bismarck, ND | 70 | $66,700 +4% |
| Charlotte-Concord-Gastonia, NC-SC | 40 | $77,950 +22% |
| Greeley, CO | 30 | $62,150 -3% |
| Charlotte-Concord-Gastonia, NC-SC | 40 | $77,950 +22% |
| Denver-Aurora-Centennial, CO | 160 | $74,740 +17% |
| Bismarck, ND | 70 | $66,700 +4% |
We have no reported case of a named organisation automating this occupation. Not one deployment, not one announcement.
That is worth saying out loud next to a score of 61. The verdict above is about what the work exposes — what current AI could do to these tasks. It is not a claim that anyone has done it. For this occupation those two things have come apart completely: the capability argument is on this page, and the evidence column is empty.
Has AI actually changed your work? One tap, anonymous, and the running tally is public. Nothing else is asked of you.
Rather than check back: get the digest and we'll tell you what changed — or watch a single occupation from its own page.