EXPOSED
The desk half of this job — load planning, weight-and-balance computation, manifest reconciliation, crew scheduling, delay reporting — is already handled by airline load-control software and will absorb more AI. The ramp half is not: directing loaders around a live aircraft, verifying hazmat placarding and cargo restraint by hand, catching a mis-tagged pallet before pushback, and owning the safety call when weather or a ground-damage event scrambles the plan. Scored for the modal ramp/cargo supervisor at a passenger or freight carrier, not a centralized load-control specialist.
Roughly flat across the period, with year-to-year wobble.
Median pay $53,850 → $58,170 -13.6% 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
+5.2% 10,300 → 10,800 on the projections basis
Growing, and only partly exposed
The BLS expects +5.2% more of these jobs by 2034, and at 57/100 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.
~1,100 openings a year on average, including replacing people who leave.
BoatswainDock BossGang BossGrip BossRamp BossChute BossHatch BossLoadmasterRoadmasterTrainmasterFarm ManagerPort StewardShip StewardYard ForemanYard ManagerCargo ManagerFleet ManagerFlight PurserRoute ManagerCab SupervisorCar SupervisorDriver ManagerHub SupervisorYard Conductor
Holding it up: embodiment . Weakest point: trust premium .
Mixed — a routine tier and a judgment tier The load sheet, ULD build plan, and manifest reconciliation are already generated by systems like Sabre/AHM tools with the supervisor pressing accept, but nobody has automated walking the hold to confirm a 463L pallet's net is tensioned, that a DGR shipment's segregation matches the NOTOC, or that the belt loader operator stops before contacting the fuselage — roughly half the shift resists, which is why this sits at 12 rather than 16.
Hands-on in uncontrolled environments This is ramp work in whatever the weather does: inside cargo holds at outside-air temperature, on wet aprons under jet blast, hand-checking tiedowns and lock latches, riding K-loaders, and doing it inside an active aircraft movement area where a positioning error becomes ground damage — 17 rather than 20 only because a meaningful share of the shift is spent at a terminal reconciling paperwork.
Certification preferred, not legally required No FAA airman certificate protects this role — the credentials are employer-issued and program-based (IATA/49 CFR 175 hazmat recurrent training, SIDA badge, GSE operating authorizations), and when a load is out of CG or an undeclared lithium shipment gets aboard, enforcement lands on the certificate holder — the airline — with the supervisor exposed to termination and badge pull rather than personal license revocation, which is what puts this at 8 instead of 3.
Exists to be accountable for ambiguous calls When a last-minute AVI or human-remains shipment arrives, a pallet weight is obviously wrong, or a thunderstorm cell forces ramp closure mid-load, the supervisor decides whether to offload, reweigh, re-sequence, or hold the departure — calls made in minutes against pushback pressure with the safety-of-flight consequence real, though bounded by the carrier's GOM and weight-and-balance limits, which keeps it at 14 rather than 18.
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 (12/20 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 (8/20) is whether the law requires a licensed human to sign. Trust premium (6/20) 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 28 of this occupation's 57 points (49%).
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 72/100 — SAFE.
Carrier SMS (Safety Management System, required under 14 CFR Part 5) designating the ramp/cargo supervisor as the accountable person for ground-damage and load-integrity hazard reports, making the stop-work / reject-the-aircraft call a documented, individually-attributed decision rather than a dispatcher's.
Task-mix shift: once load-control software absorbs manifest reconciliation, weight-and-balance math and delay coding, the residual job is exception handling — mis-tagged pallets, restraint verification, hazmat discrepancies, weather and ground-damage recovery. This raises the resistance of the remaining role without any new law, though it also shrinks headcount per station.
Little upward room; already 17. Airside ramp work in live-aircraft environments with weather, jet blast and non-standard cargo is among the least automatable settings, and autonomous ramp tugs/loaders (in trial at Amsterdam, Changi) automate the moving, not the supervising.
FAA rulemaking or carrier ops-spec language requiring a named, certificated person (e.g., a load planner/weight-and-balance signatory under the carrier's FAA-approved Weight and Balance Control Program in the Ops Specs) to personally sign the final loading instruction report and hazmat acceptance checklist, with AI output treated as advisory only. Precedent exists: 49 CFR 175.30 hazmat acceptance requires a trained person's verification, and IATA DGR requires a named acceptance-check signatory. A rule explicitly barring automated acceptance checks would harden this.
Post-accident NTSB recommendation after a load-shift or hazmat event traced to automated load planning, prompting FAA to require human countersignature on any AI-adjusted load plan change after doors close.
The limit. No plausible route to a higher trust premium: cargo shippers and passengers never see this role and cannot pay a premium for a human in it. Also note the headcount risk — consolidation of load control into centralized remote centers (already standard at major carriers and third-party providers) can cut the number of these positions even as the per-job scores rise.
| Dallas-Fort Worth-Arlington, TX | 690 | $53,220 -9% |
| Los Angeles-Long Beach-Anaheim, CA | 680 | $60,530 +4% |
| Cincinnati, OH-KY-IN | 460 | $34,110 -41% |
| Houston-Pasadena-The Woodlands, TX | 390 | $56,040 -4% |
| Chicago-Naperville-Elgin, IL-IN | 380 | $70,780 +22% |
| Miami-Fort Lauderdale-West Palm Beach, FL | 360 | $65,540 +13% |
| Philadelphia-Camden-Wilmington, PA-NJ-DE-MD | 300 | $80,820 +39% |
| Riverside-San Bernardino-Ontario, CA | 280 | $49,290 -15% |
| Atlanta-Sandy Springs-Roswell, GA | 130 | $81,380 +40% |
| Philadelphia-Camden-Wilmington, PA-NJ-DE-MD | 300 | $80,820 +39% |
| Charleston-North Charleston, SC | 40 | $80,140 +38% |
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 57. 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.