SAFE
The job is climbing poles and bucket trucks, pulling and splicing energized conductors, setting transformers, and restoring service in storms and mud at 3am — none of which current robotics can do. AI touches the paperwork edges: outage prediction, switching-order generation, load and fault analysis, dispatch routing, inspection imagery from drones and LiDAR. Grid buildout, electrification, and aging infrastructure mean demand rises while the physical work stays human; the real hazards to this job are utility cost-cutting and contractor labor structures, not software.
Headcount grew steadily across the period.
Median pay $72,520 → $95,320 +5.2% 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
+6.6% 127,400 → 135,800 on the projections basis
Hard to automate, and growing
The work resists current AI and the BLS projects +6.6% more of these jobs by 2034. Note that safe does not mean well paid — several of the fastest-growing resistant occupations are among the lowest paid on the register.
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.
~10,700 openings a year on average, including replacing people who leave.
ClimberLinemanLocatorSplicerCablemanLinesmanInstallerRelay ManLineworkerTroublemanCable LayerService ManCable TesterLine BuilderLine CrewmanLine ErectorPole ClimberRelay WorkerCable SplicerEmergency ManHot Stick ManLine MechanicLine RepairerPower Lineman
Holding it up: embodiment . Weakest point: trust premium .
Tasks largely resist digitisation Framing a new pole, hot-sticking a 12kV tap, phasing a bank of transformers, and rerouting a downed primary through unfamiliar backyard easements are decided and executed in the same motion at the top of the pole — a 17 rather than 20 because switching orders, work packets, mapping, and inspection triage are already being written by software before you leave the yard.
Hands-on in uncontrolled environments Bucket work in 25mph wind, climbing gaffs into an ice-loaded crossarm, digging out a padmount in mud, and working de-energized-but-verified next to backfeed from a customer generator is the full 20: uncontrolled environment, live hazard, no fixed workpiece geometry for a robot to reference.
Certification preferred, not legally required A 9 reflects that the trade runs on completed apprenticeship, CDL, OSHA 1910.269 and often a journeyman lineworker card plus employer qualification-to-work-energized rather than a state licence — nobody stamps a drawing in your name, so when a switching error causes a backfeed the utility and the general foreman absorb the exposure, though your qualified-worker status can be pulled personally.
Exists to be accountable for ambiguous calls A 14 is earned at the point where you decide a pole is too rotten to climb, that the line is truly dead despite the paperwork, or whether to backfeed a hospital from an alternate feeder during a storm restoration — ambiguous calls with lethal and citywide consequences, held down from higher only because clearance procedures and switching authority are formalized.
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 (17/20 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 (9/20) 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 (14/20) 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 31 of this occupation's 68 points (46%).
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.
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 82/100, still SAFE.
Post-wildfire liability regimes (California SB 901/AB 1054 wildfire fund, PG&E criminal plea conditions) that make documented human inspection sign-off a condition of cost recovery or insurance — drone/AI imagery accepted only when a qualified human attests to the condition finding.
Storm-restoration and re-energization decisions formally vested in the field crew leader rather than a remote control center — e.g. utility work rules giving the on-site qualified worker unilateral authority to refuse energization, as several IBEW contracts and post-Maui/Camp Fire operating procedures now do.
Task-mix shift: as drone/LiDAR inspection and AI outage prediction absorb routine patrol and paperwork, the remaining day concentrates on energized splicing, transformer setting, and ambiguous storm damage triage — the tier no software or robot touches.
OSHA 1910.269 / NESC-style rules or state PUC orders requiring a qualified line worker to personally verify and sign clearance/switching orders and grounding before energization — i.e. explicitly barring AI-generated switching orders from being executed without a named qualified employee's countersignature. IBEW local agreements already require two-person switching and personal grounding verification; codifying 'no autonomous switching authority' at the state PUC level would push this up.
Utility staffing rules or state PUC reliability orders mandating minimum in-house (non-contractor) qualified line crews per service territory, as debated after contractor-related wildfire and restoration failures. This is a labor-structure protection rather than a buyer preference for humans.
The limit. Trust premium has almost no route here: ratepayers do not choose their lineworker and cannot pay a premium for a human one. Embodiment is already maxed. The real downside risks are contractor conversion and utility headcount cuts, which no dimension on this register captures.
| Houston-Pasadena-The Woodlands, TX | 4,380 | $82,710 -13% |
| Dallas-Fort Worth-Arlington, TX | 3,930 | $77,910 -18% |
| New York-Newark-Jersey City, NY-NJ | 3,850 | $122,480 +28% |
| Phoenix-Mesa-Chandler, AZ | 2,810 | $75,420 -21% |
| Atlanta-Sandy Springs-Roswell, GA | 2,660 | $83,570 -12% |
| Los Angeles-Long Beach-Anaheim, CA | 2,140 | $130,440 +37% |
| Chicago-Naperville-Elgin, IL-IN | 1,830 | $123,430 +29% |
| Riverside-San Bernardino-Ontario, CA | 1,580 | $128,750 +35% |
| San Jose-Sunnyvale-Santa Clara, CA | 300 | $157,620 +65% |
| Eugene-Springfield, OR | 120 | $140,270 +47% |
| San Francisco-Oakland-Fremont, CA | 770 | $137,180 +44% |
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 68. 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.