EXPOSED
The core of this job is physical: dragging and coupling loading arms and hoses, climbing tank cars to open hatches, setting valves, grounding and bonding, watching gauges, and pulling samples — none of which today's robotics does at terminal scale. The real threat isn't AI reasoning but terminal automation that has been eating this occupation for decades: automated loading racks with card-reader driver kiosks, mass-flow meters, overfill sensors, and remote console control let one operator supervise many bays, and AI-assisted monitoring pushes that ratio further. Paperwork tasks — bills of lading, shipping papers, batch records, tank gauging math — are already largely software-handled.
Most of this decline happened after 2021 — it is not the pandemic dip.
Median pay $42,360 → $58,870 +11.2% 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
+4.3% 12,000 → 12,500 on the projections basis
Growing, and only partly exposed
The BLS expects +4.3% more of these jobs by 2034, and at 53/100 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.
~1,300 openings a year on average, including replacing people who leave.
LoaderUnloaderTankermanCar LoaderDock LoaderRail LoaderShip LoaderBarge LoaderCar UnloaderSpout TenderTruck LoaderPumper GaugerShip UnloaderTruck UnloaderCaustics LoaderLoad Out PersonLoader OperatorRail Car LoaderShipping LoaderTank Car LoaderLoading OperatorWarehouse LoaderTank Truck LoaderReceiving Operator
Holding it up: embodiment . Weakest point: trust premium .
Mixed — a routine tier and a judgment tier At 13 rather than 17, the hose-and-hatch work genuinely resists software, but you already work next to racks where a driver swipes a card, keys a product code, and the preset meter shuts off on its own — the loading itself is a solved control problem, and what's left is connect, inspect, and troubleshoot; that's what keeps it out of the 6-and-below band but off the top.
Hands-on in uncontrolled environments 17 reflects climbing to the dome of a car in the rain to open a hatch, torquing a stuck valve, dragging a 4-inch vapor hose into position, and doing it in a Class I Division 1 area where you're bonded and grounded — uncontrolled outdoor environments with confined-space and fall exposure, only short of 20 because the work happens on a fixed rack you know inch by inch rather than at unpredictable sites.
Certification preferred, not legally required 10 sits at the top of the certification band because HM-126 hazmat function-specific training under 49 CFR 172.704 and the CDL/tanker-endorsement world genuinely gate who touches the product, but the certificate is not a personal licence — when a car overfills or a placard is wrong, DOT and PHMSA cite the shipper of record and the terminal operator, not you.
Meaningful discretion 9 recognises the real calls you make — refusing a car with a bad valve or missing gasket, stopping a load on a pressure anomaly, deciding a sample looks off-spec — but those decisions run against written loading procedures, product-compatibility charts, and a supervisor you can raise on the radio, so the ambiguity is bounded rather than yours to own alone.
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 (13/20 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 (10/20) is whether the law requires a licensed human to sign. Trust premium (4/20) is whether buyers specifically pay for a person. Judgment and accountability (9/20) 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 23 of this occupation's 53 points (43%).
Embodiment (17/20) 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 69/100 — SAFE.
Task-mix shift: if metering, sequencing and paperwork are fully automated, the remaining role is the USCG/OSHA Person-in-Charge who calls emergency shutdown, judges compatibility and last-cargo/heel questions, and signs off on grounding-bonding adequacy in degraded conditions — a judgment tier this occupation genuinely has.
Same two-tier shift plus PSM/hot-work and confined-space entry work: if routine batch loading disappears, what remains is non-routine transfers, off-spec product, hose failures, sampling for custody-transfer disputes, and manual gauging when meters fail — none automatable at terminal scale.
PHMSA/DOT hazmat rules already require a person to certify shipping papers and perform pre-departure inspection under 49 CFR 172-174; a rule change explicitly barring unattended/automated certification of hazmat loading and naming a trained, qualified individual as the signer of record for each transfer (as USCG 33 CFR 154/156 already does with the Person-in-Charge for marine oil transfers) would raise this. Watch for PHMSA rulemaking on automated loading racks and for USCG interpretations of remote-monitored transfers.
A state or EPA consent decree following a major overfill/vapor-release incident at an automated rack requiring an attested human PIC physically present per bay during transfer, as several refinery consent decrees have imposed staffing and monitoring terms.
Little headroom; already 17. Only a shift toward more non-standard equipment (rail tank cars with varied fittings, barge transfers, cryogenic/LNG bunkering requiring manual connection under class-society witness) would nudge it.
The limit. No plausible route to trust_premium: buyers are refiners, chemical shippers and railroads purchasing throughput, and none pay a premium for a human loader. The dominant threat is fixed automation and staffing ratios, not AI reasoning, so liability rules that name a human signer help only if they also require physical presence per bay — a paper PIC supervising twelve remote bays does not preserve headcount.
| Chicago-Naperville-Elgin, IL-IN | 1,460 | $61,420 +4% |
| Houston-Pasadena-The Woodlands, TX | 970 | $61,220 +4% |
| St. Louis, MO-IL | 320 | $60,950 +4% |
| New Orleans-Metairie, LA | 210 | $62,200 +6% |
| Dallas-Fort Worth-Arlington, TX | 200 | $76,850 +31% |
| Cincinnati, OH-KY-IN | 120 | $50,380 -14% |
| New York-Newark-Jersey City, NY-NJ | 120 | $64,890 +10% |
| Baton Rouge, LA | 100 | $49,700 -16% |
| Billings, MT | 50 | $83,390 +42% |
| Providence-Warwick, RI-MA | 70 | $83,160 +41% |
| Corpus Christi, TX | 60 | $81,920 +39% |
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 53. 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.