EXPOSED verdict contested
Positioning a hammer or vibratory rig over a pile, reading the driving log against refusal criteria, rigging leads, and adjusting for soft spots or obstructions on a muddy marine or bridge site is physical work that no language model touches. The real automation pressure is mechanical — GPS-guided and semi-autonomous driving rigs that let one operator do more piles per shift — plus the paperwork side, where driving records, blow-count logs, and production reports are trivially digitized. Licensure is thin: OSHA and often crane/equipment certification, but no personally liable stamp, and the engineer of record owns the design call.
Most of this decline happened after 2021 — it is not the pandemic dip.
Median pay $62,600 → $73,300 -6.3% 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
+4.3%
Percentage only. The projection counts a different population from the 2,310 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 +4.3% more of these jobs by 2034, and at 65/100 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.
~300 openings a year on average, including replacing people who leave.
Pile DriverNozzle OperatorDriving OperatorDriving InspectorPile Driver EngineerPile Driver OperatorPile Driving LeadsmanPile Driving OperatorVibratory Pile DriverPile Driving InspectorPile Driving NozzlemanPile Driving TechnicianDiesel Pile Hammer OperatorHydraulic Press-In OperatorHoisting Pile Driving EngineerHydraulic Pile Hammer Operator
Holding it up: embodiment . Weakest point: trust premium .
Tasks largely resist digitisation Threading a 60-foot H-pile into leads, watching for pile run or drift, hearing a hammer lose stroke, and re-plumbing under load are judgments made through the seat and the hoist lines, not from a data feed — the only genuinely automatable core task is transcribing blow counts into the driving log, which is why this sits at 18 rather than 20.
Hands-on in uncontrolled environments You work off barges, cofferdams, and bridge falsework in weather, with pinch points between leads and template, live rigging overhead, and ground conditions that change pile to pile — there is no version of this that happens anywhere but on the deck.
Certification preferred, not legally required NCCCO or state crane-operator certification and OSHA 1926 Subpart CC training gate who touches the controls, which is a real barrier, but nothing you sign carries your name into court — the geotechnical engineer stamps the pile capacity and the driving criteria you follow, putting this at 9 rather than in licensed-professional territory.
Meaningful discretion You call whether that pile reached refusal or just hit a boulder, whether to stop driving before you break the head off, and when the barge or crane setup is no longer safe to load — real stop-work discretion inside a driving criteria and pile-order that someone else already fixed.
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 (18/20 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 (7/20) is whether buyers specifically pay for a person. Judgment and accountability (11/20) 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 27 of this occupation's 65 points (42%).
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.
No occupation passed every test: close enough to pile driver operators on skills and subject matter, at least 10 points more resistant, no big jump in training, no new licence, no pay cut, and not shrinking on its own. That happens for 223 of the 654 occupations here that aren't SAFE, and it is worth stating plainly rather than leaving the section off.
The usual reason is that exposure travels with the skill profile. The jobs most similar to yours tend to be exposed for the same reasons yours is, so the near neighbours don't clear the gap — and the ones that do are a different kind of work, not a transfer of what you already know. Read that as a limit of this method, not a verdict that you're stuck: it only compares whole occupations, and it cannot see specialisation, industry, or anything you'd bring that isn't in a federal skill survey.
Here is that claim on your own job rather than in the abstract. These are the three occupations closest to this one by skill and subject matter — the places the work would most naturally transfer — with what the register scores them:
That is the whole problem in three lines. The nearest work is not meaningfully safer, so there is no move here that trades a similar skill set for a better verdict. This is not us running out of ideas — it is what the neighbourhood looks like.
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 73/100 — SAFE.
Task-mix shift plus formal recognition: as GPS/auto-plumb rigs absorb positioning, the remaining human call is early refusal, unexpected obstruction, pile damage and driveability deviation from the engineer's criteria — decisions with immediate load-capacity consequences. If contract specs (state DOT special provisions) name the operator/inspector as the party who stops driving and triggers engineer notification, ownership becomes explicit.
State DOT and building-code adoption of a rule that pile installation records — driving logs, blow counts, refusal determinations — must be attested by a named certified pile driving inspector/operator on site, not by rig telemetry alone. ADSC/DFI and AASHTO already push documented driving criteria; NCCCO's Pile Driver Operator certification exists but carries no attestation duty. If a certification becomes a signature-with-liability requirement on the installation record, this rises.
Two genuine tiers exist: production driving on open uniform sites vs. restricted-access work — marine barge, underpinning next to existing structures, vibration-sensitive urban retrofit, obstruction-laden brownfield. If automation captures the production tier, the surviving job is disproportionately the improvisational tier (rigging leads, splicing, template work, follower use), which no rig automates.
The limit. Trust premium has no plausible route: buyers are GCs and public agencies purchasing installed capacity to spec, and no owner will pay a premium for a human at the controls rather than a cheaper compliant pile. Embodiment is maxed. Realistic ceiling is roughly 72-73, and the binding threat is mechanical productivity (fewer operators per project), which none of these levers offset.
| Los Angeles-Long Beach-Anaheim, CA | 130 | $106,660 +46% |
| Beaumont-Port Arthur, TX | 90 | $66,140 -10% |
| Boston-Cambridge-Newton, MA-NH | 90 | $121,900 +66% |
| Anchorage, AK | 80 | $89,880 +23% |
| Baton Rouge, LA | 80 | $60,630 -17% |
| Houston-Pasadena-The Woodlands, TX | 80 | $70,030 -4% |
| Miami-Fort Lauderdale-West Palm Beach, FL | 70 | $59,740 -18% |
| Sacramento-Roseville-Folsom, CA | 70 | $124,670 +70% |
| San Francisco-Oakland-Fremont, CA | 70 | $132,850 +81% |
| Sacramento-Roseville-Folsom, CA | 70 | $124,670 +70% |
| Boston-Cambridge-Newton, MA-NH | 90 | $121,900 +66% |
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 65. 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.