EXPOSED
Orderlies transfer patients between beds, gurneys and wheelchairs, reposition immobile bodies, transport specimens and equipment, and clean rooms — none of which language models touch and none of which today's robots do safely around frail humans. The exposure is not AI replacing the work but software squeezing it: automated dispatch and transport-request systems, tracking of bed turnover, and AGV carts for supplies and linens erode the non-patient portion of the shift and let hospitals staff thinner. There is no license or personal liability shield here, and the discretion is real but narrow — recognizing that a patient looks wrong and escalating.
Dipped in 2020, then grew past where it started.
Median pay $28,980 → $38,290 +5.7% 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
+3.3% 54,000 → 55,800 on the projections basis
Growing, and only partly exposed
The BLS expects +3.3% more of these jobs by 2034, and at 56/100 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.
~7,800 openings a year on average, including replacing people who leave.
OrderlyAttendantWard AideTransporterWard HelperCart AttendantPatient EscortPatient SitterRadiology AideTransport AideWard AssistantWard AttendantMedical OrderlyHospital OrderlyPatient ObserverSecurity OrderlySurgical OrderlyHospital CorpsmanRadiology OrderlyInstitutional AideNew Patient EscortInfirmary AttendantMedical TransporterOperating Room Aide
Holding it up: embodiment . Weakest point: liability shield .
Tasks largely resist digitisation A two-person lateral transfer of a 300-pound sedated patient off a gurney, a manual reposition to prevent pressure ulcers, and a terminal clean of an isolation room are physical acts no software performs, which is why this sits at 15 rather than 18 — the AGV linen cart, the automated transport-ticket queue, and the bed-status board have already taken the fetching-and-dispatching slice of the shift.
Hands-on in uncontrolled environments The work happens in occupied patient rooms, ORs, morgues and elevators, with wet floors, C. diff precautions, combative or confused patients, and lifting loads that put orderlies among the highest musculoskeletal-injury rates in any US industry; 19 rather than 20 only because some of the shift is pushing carts down predictable corridors.
No licence, no signature requirement No state licence gates this job — most hospitals require a high school diploma, CPR, and in-house lift and bloodborne-pathogen training, and when a patient is dropped during a transfer the claim runs against the hospital and the supervising RN who ordered the move, so the 3 reflects only that a documented competency checklist exists at all.
Meaningful discretion Lift protocols, isolation precautions and transport orders are written down and you follow them; the 8 is for the calls that are genuinely yours — refusing an unsafe solo transfer, spotting that a patient has gone gray or unresponsive mid-transport and stopping to call it in, deciding a confused patient shouldn't be left on a gurney unattended.
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 (15/20 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 (3/20) is whether the law requires a licensed human to sign. Trust premium (11/20) is whether buyers specifically pay for a person. Judgment and accountability (8/20) 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 22 of this occupation's 56 points (39%).
Embodiment (19/20) 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.
Childcare Workers 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 70/100 — SAFE.
Task-mix shift as AGVs and tube systems absorb specimen and linen runs: what remains is hands-on repositioning, early-mobility ambulation protocols, and fall-risk observation. Recognizable marker would be hospitals formally reassigning orderlies to mobility-technician or 1:1 observation duty rather than cutting headcount
Hospital pressure-injury and fall metrics are CMS penalty-linked; if repositioning-turn documentation becomes an auditable, individually-attributed entry in the EHR (as some systems already do with turn-timer sensors), the role owns a consequential, named call
Private-duty and concierge patient-sitter/companion market where families pay directly for a named human to stay with a frail or dementia patient during hospitalization — already a paid service in some markets and explicitly not substitutable by monitoring cameras
Joint Commission or CMS Conditions of Participation naming the transporting or repositioning staff member as an accountable reporter in fall, pressure-injury (HAPI), and deterioration escalation pathways — e.g. a documented handoff signature required before a patient leaves a unit for imaging, and inclusion of transport staff in rapid-response activation criteria
State-level extension of nurse-aide certification (42 CFR 483.152-style training and registry, currently mandated in long-term care) to acute-care transport and handling staff, with registry-recorded abuse/neglect findings attaching to the individual. This creates a credential and personal record, not personal malpractice liability
State safe-patient-handling laws (already in ~11 states: WA, NY, CA AB 1136, NJ, MN) being extended to require a dedicated two-person lift/mobility team for any transfer of a patient above a weight or dependency threshold — this converts transfers from 'whoever is free' into a staffed function that dispatch software cannot thin out, and shifts the remaining shift toward the mobility/handling tier rather than errand-running
The limit. Liability shield has a hard low ceiling: no US jurisdiction licenses orderlies as independent practitioners and none is proposing to, so signature authority and personal malpractice exposure are not realistic routes. Embodiment is already near maximum and cannot rise. The dominant threat here is headcount thinning through staffing software, which staffing-ratio and lift-team mandates address directly while credentialing does not.
| New York-Newark-Jersey City, NY-NJ | 4,970 | $45,850 +20% |
| Los Angeles-Long Beach-Anaheim, CA | 1,890 | $49,760 +30% |
| Chicago-Naperville-Elgin, IL-IN | 1,770 | $39,640 +4% |
| Philadelphia-Camden-Wilmington, PA-NJ-DE-MD | 1,740 | $43,570 +14% |
| Boston-Cambridge-Newton, MA-NH | 1,330 | $39,800 +4% |
| Atlanta-Sandy Springs-Roswell, GA | 1,280 | $37,410 -2% |
| Miami-Fort Lauderdale-West Palm Beach, FL | 1,210 | $35,770 -7% |
| Baltimore-Columbia-Towson, MD | 960 | $37,760 -1% |
| San Francisco-Oakland-Fremont, CA | 480 | $69,870 +82% |
| San Jose-Sunnyvale-Santa Clara, CA | 300 | $65,790 +72% |
| Santa Rosa-Petaluma, CA | 40 | $63,780 +67% |
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 56. 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.