COOKED
The core of this job — quoting fares, booking and reissuing tickets, processing cancellations, answering itinerary questions, confirming schedules — has been migrating to self-service kiosks, airline apps and chatbots for two decades, and generative AI closes the remaining gap on complex fare rules and rebooking logic. What holds employment up is the physical airport floor: checking bags and tagging them, verifying documents and IDs, boarding and door closeout, and handling angry passengers during a weather meltdown. That tier is real but shrinking, and it carries no license, no signature requirement, and no client relationship the buyer pays extra for.
Roughly flat across the period, with year-to-year wobble.
Median pay $38,380 → $44,390 -7.5% 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
+2.8% 131,900 → 135,600 on the projections basis
Exposed, but growing
AI can already do a lot of these tasks, and the BLS still expects +2.8% more of these jobs by 2034. Demand for the output is growing faster than the work is being automated away — the mechanism BLS gives for software developers, and the combination people most often misread as an error.
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.
~14,400 openings a year on average, including replacing people who leave.
Gate AgentCabin AgentDepot AgentTrain ClerkFlight AgentRoad AdvisorTicket AgentTicket ClerkTravel ClerkAirline AgentAirport AgentBaggage AgentBaggage ClerkBooking AgentStation AgentTicket SellerTourist AgentAircraft AgentBoarding AgentCheck In AgentReservationistTour CounselorTravel AdvisorDeparture Clerk
Holding it up: embodiment . Weakest point: liability shield .
Core tasks are already automatable Fare quoting in a GDS, PNR reissues, seat assignments, refund processing and schedule confirmation are already done end-to-end by web check-in, kiosks and airline chatbots — a 4 rather than a 10 because even the hard parts (Fare rule interpretation, involuntary rebooking under IROPS) are rule-tables an LLM reads better than a new hire, leaving little that genuinely needs a person at a keyboard.
Some physical or field component An 8 reflects the half of the workforce that lifts and tags bags at the counter, works the belt and jet bridge, checks passports against the manifest and physically closes the aircraft door — but it's an indoor terminal with fixed equipment, not an uncontrolled site, and the call-center and corporate-travel half of this SOC never leaves a desk.
No licence, no signature requirement No state licence, no certificate you can lose: agents work under the carrier's DOT/TSA authority, and when a document check goes wrong the airline pays the Immigration fine — the 1 is for badge-level security clearance (SIDA, CBP document training), which is a background check, not a credential that protects your job.
Executes defined procedures on defined inputs Overbooking, denied boarding compensation, misconnect rebooking and fare exceptions are all governed by contract of carriage terms and supervisor override thresholds you're trained to escalate past — a 6 because the real discretion (waiver authority, when to hold a flight) sits with duty managers and ops control, not the agent at the podium.
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 (4/20 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 (1/20) is whether the law requires a licensed human to sign. Trust premium (5/20) is whether buyers specifically pay for a person. Judgment and accountability (6/20) 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 12 of this occupation's 24 points (50%).
Embodiment (8/20) 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.
Flight Attendants SAFE
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 35/100 — EXPOSED.
If TSA/airline security rules continue to require a human agent to physically verify travel documents and visas against the passenger's face at check-in for international departures (IATA Timatic liability for carrier fines sits with the airline, and DHS has not authorized unattended document verification for most foreign passports), the residual floor tier holds; expansion would come from any new rule requiring in-person agent verification of minors traveling alone, mobility assistance handoffs (Air Carrier Access Act enforcement, DOT's 2024 wheelchair-handling rulemaking), or lithium-battery/dangerous-goods declarations at bag drop
Genuine two-tier structure: if fare quoting and routine rebooking fully automate, what remains is weather-meltdown triage, misconnect protection across interline agreements, and denied-boarding negotiation, which raises the resistance of the residual job even as headcount falls
If irregular-operations authority stays with the gate agent — deciding involuntary denied boarding, hotel/meal vouchers, and rebooking priority under DOT's 2024 automatic-refund and family-seating rules, where the carrier owes compensation and someone must make the call in minutes — the remaining job is the exception tier, not the booking tier
If a state or federal rule reinstates personal accountability for a named human at the point of ticketing — e.g. restoration of something like ARC/IATA accredited-agent personal bonding for issuance, or a CBP requirement that a designated agent attest to APIS data accuracy — a signature requirement would exist; nothing of this kind is currently in motion
The limit. No realistic route to a meaningful trust premium: buyers have demonstrated for twenty years they will not pay extra for a human to book a flight, and the airport-floor tier is a cost center the carrier wants to shrink. Even with every lever above, this occupation stays in the low-to-mid range and headcount continues to fall; the levers raise the resistance of the surviving role, not the number of roles.
| Dallas-Fort Worth-Arlington, TX | 10,630 | $38,250 -14% |
| New York-Newark-Jersey City, NY-NJ | 7,210 | $41,600 -6% |
| Miami-Fort Lauderdale-West Palm Beach, FL | 6,750 | $39,190 -12% |
| Chicago-Naperville-Elgin, IL-IN | 6,660 | $47,850 +8% |
| Los Angeles-Long Beach-Anaheim, CA | 5,340 | $51,130 +15% |
| Atlanta-Sandy Springs-Roswell, GA | 5,040 | $47,860 +8% |
| Houston-Pasadena-The Woodlands, TX | 4,640 | $29,870 -33% |
| Orlando-Kissimmee-Sanford, FL | 4,050 | $40,540 -9% |
| Detroit-Warren-Dearborn, MI | 1,490 | $72,880 +64% |
| Pensacola-Ferry Pass-Brent, FL | 80 | $60,280 +36% |
| Albuquerque, NM | 510 | $57,390 +29% |
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 24. 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.