EXPOSED
The core of this job is physically driving the airfield: runway and taxiway inspections, FOD sweeps, lighting and marking checks, wildlife hazard patrols, escorting contractor vehicles in movement areas, and coordinating live with the tower by radio. AI and sensor systems will eat the paperwork tier — NOTAM drafting, Part 139 inspection logs, wildlife strike reports, weather monitoring, shift handover summaries — and automated FOD/incursion detection will reduce how often a human must look. What persists is the person on the airfield during a snow event, a disabled aircraft, or an emergency, making a runway-closure call and owning it under FAA scrutiny.
Headcount grew steadily across the period.
Median pay $52,650 → $56,850 -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
+4.2% 16,900 → 17,600 on the projections basis
Growing, and only partly exposed
The BLS expects +4.2% more of these jobs by 2034, and at 63/100 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.
~1,600 openings a year on average, including replacing people who leave.
Ramp AgentAirline AgentAirport AgentFlight FollowerOperations AgentAirline DispatcherAirport Ramp AgentAirport SupervisorOperations OfficerOperation SpecialistOperations CoordinatorFlight Operations AgentAirport Operations AgentAirport Security OfficerAirfield Services OfficerFlight Operations PlannerAirport Operations OfficerFlight Operations EngineerAirport Services SupervisorFlight Information ExpediterFlight Operations SpecialistAirport Operations SpecialistFlight Operations CoordinatorGround Operations Crew Member
Holding it up: embodiment . Weakest point: trust premium .
Mixed — a routine tier and a judgment tier At 13 the job splits cleanly: the recurring Part 139 self-inspection checklist, NOTAM issuance, condition reporting (FICON), and wildlife log entries are structured enough to be templated and increasingly sensor-fed, while snow removal sequencing, disabled-aircraft coordination, and judging whether a pavement crack or rubber buildup warrants closure keep it out of the 6-and-below band.
Hands-on in uncontrolled environments 17 reflects that most of a shift is in a vehicle on the movement area in whatever weather the airport has — driving runway edges at night looking for unseated light fixtures, walking FOD off a taxiway, firing pyrotechnics at gulls, checking friction after freezing rain, and standing on a ramp during an aircraft emergency — with only the last few points withheld because the ops desk, radio work, and reporting still pull you inside.
Certification preferred, not legally required 10 is the ceiling for a role with no personal FAA certificate: you need an airfield driver's permit and movement-area authorization, and Part 139 makes the airport certificate holder — not you — the entity FAA inspectors cite, so your findings can end a career without ever attaching a licence number to a signature.
Exists to be accountable for ambiguous calls 15 is earned by the closure decision: you decide alone, in minutes, whether a runway comes out of service for a bird carcass, a fuel spill, or a braking action report, knowing a wrong call either strands diverting aircraft or lets one land on a surface it shouldn't, and the FAA reconstruction of that decision has your radio transmissions in it.
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 (8/20) is whether buyers specifically pay for a person. Judgment and accountability (15/20) 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 33 of this occupation's 63 points (52%).
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 79/100 — SAFE.
Task-mix shift: once NOTAM drafting, Part 139 logs, wildlife strike reporting and weather monitoring are automated, the residual day is snow-event runway closure calls, disabled-aircraft coordination, ARFF/emergency-plan activation and construction-phasing safety risk assessment under SMS (Part 139.301 SMS requirements) — the judgment tier is genuine and separable here
Part 139 SMS implementation deadlines force airports to designate an accountable individual for airfield hazard risk acceptance, with documented safety risk assessments naming the decision-maker; if operations specialists are named as risk-acceptance authorities rather than data collectors, ownership of ambiguous calls becomes formal
FAA amends 14 CFR Part 139 (or its Advisory Circular 150/5200-18 inspection guidance) to require that a named, airport-certified operations person personally sign each self-inspection record and any runway condition (FICON/RCAM) assessment, with automated sensor output treated as advisory only — the FAA already requires trained personnel and RCAM assessments to be human-judged; codifying non-delegability to a certificated individual with personal enforcement exposure is the specific step
State or FAA rulemaking that makes movement-area vehicle escort and runway incursion prevention duties assignable only to a badged, certified human whose airfield driver certification can be suspended for a deviation — mirroring how ATC controller certificates work; airport incursion enforcement actions already name individuals
Structurally near-ceiling already; only a broadening of duties into winter operations equipment command, wildlife depredation under USDA/USFWS permits, and hands-on emergency scene control would nudge it — the environment (weather, wildlife, live aircraft, construction) resists sensor-only substitution
The limit. No realistic trust_premium route: passengers and airlines never see or select this role, and airports are cost-center buyers of it — any claim that travelers would pay for a human airfield inspector is false comfort. Also, capability pressure is real: FOD detection radar, camera-based incursion alerting and automated FICON tooling are being deployed now, and the main displacement risk is headcount thinning per airfield rather than the role vanishing.
| New York-Newark-Jersey City, NY-NJ | 2,090 | $42,000 -26% |
| Miami-Fort Lauderdale-West Palm Beach, FL | 1,530 | $58,630 +3% |
| Los Angeles-Long Beach-Anaheim, CA | 620 | $57,330 +1% |
| Boston-Cambridge-Newton, MA-NH | 280 | $56,020 -1% |
| Houston-Pasadena-The Woodlands, TX | 260 | $47,550 -16% |
| Charlotte-Concord-Gastonia, NC-SC | 250 | $46,060 -19% |
| Detroit-Warren-Dearborn, MI | 250 | $69,560 +22% |
| Orlando-Kissimmee-Sanford, FL | 250 | $48,980 -14% |
| Phoenix-Mesa-Chandler, AZ | 130 | $88,420 +56% |
| San Jose-Sunnyvale-Santa Clara, CA | 50 | $86,880 +53% |
| San Francisco-Oakland-Fremont, CA | 240 | $85,680 +51% |
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 63. 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.