SAFE
The core of this job is manual: reducing fractures, placing hardware, performing arthroplasties and arthroscopies in a sterile OR with soft-tissue variability no current robot handles autonomously — surgical robots like Mako are surgeon-guided tools, not replacements. AI is already competitive at reading radiographs and MRIs and will absorb documentation, coding, and pre-op templating, but the operative decision (operate vs. conservative management, which implant, what to do when anatomy differs from the plan) sits with a licensed, personally liable surgeon. Patients choose the individual who will cut them, and malpractice law makes that choice legally load-bearing.
Most of this decline happened after 2021 — it is not the pandemic dip.
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.
BLS projection, 2024–2034
+4.1% 14,700 → 15,300 on the projections basis
Hard to automate, and growing
The work resists current AI and the BLS projects +4.1% more of these jobs by 2034. Note that safe does not mean well paid — several of the fastest-growing resistant occupations are among the lowest paid on the register.
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.
~400 openings a year on average, including replacing people who leave.
DoctorSurgeonPhysicianHand SurgeonTrauma DoctorSpinal SurgeonTrauma SurgeonGeneral SurgeonPhysician SurgeonOrthopedic SurgeonMedical Doctor (MD)Orthopaedic SurgeonOrthopedic PhysicianSurgical EndoscopistFoot and Ankle SurgeonOrthopedic Hand SurgeonUpper Extremity SurgeonOrthopedic Spine SurgeonOrthopedic Trauma SurgeonGeneral Orthopedic SurgeonOrthopedic Surgery PhysicianTotal Joint Orthopedic SurgeonPodiatric Foot and Ankle SpecialistTransverse Abdominal Muscle Surgeon (TRAM Surgeon)
Holding it up: embodiment . Weakest point: trust premium .
Tasks largely resist digitisation Cementing a revision hip through scarred tissue, judging fracture reduction by feel under fluoro, and salvaging a case when the femoral canal fractures on broaching are tasks no software performs; the 3-point deduction reflects that dictation, ICD-10/CPT coding, pre-op CT templating, and initial radiograph reads are already being handed off to algorithms.
Hands-on in uncontrolled environments You are scrubbed, gowned, standing over a bleeding surgical field for two to four hours, using a mallet, saw, and reamer on live bone while lead-aproned under a C-arm — this is the ceiling case for physical work in an environment whose variability (osteoporotic bone, aberrant vessels, unexpected nonunion) is discovered by hand mid-procedure.
Licensed human required and personally liable State medical licensure, ABOS board certification, hospital credentialing and privileging by specific procedure, plus a malpractice premium among the highest of any specialty mean the operative note carries your name and your name alone; the single point off is because informed consent, device-manufacturer liability for implant failure, and hospital enterprise coverage absorb a sliver of exposure that would otherwise be entirely yours.
Exists to be accountable for ambiguous calls Operate now or brace for six weeks, hemi versus total, when to abandon a limb salvage for amputation, whether an infected arthroplasty gets a washout or a two-stage revision — these are irreversible, contested calls made with incomplete information and no protocol that resolves them, and you defend them at M&M and in deposition.
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 (17/20 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 (19/20) is whether the law requires a licensed human to sign. Trust premium (17/20) is whether buyers specifically pay for a person. Judgment and accountability (20/20) 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 56 of this occupation's 93 points (60%).
Embodiment (20/20) 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 98/100, still SAFE.
Rises if hospital-published surgeon-specific outcome scorecards (already live in the UK's National Joint Registry consultant-level reporting and CMS's move toward provider-level THA/TKA complication rates) become standard in US, since named-surgeon volume/revision data pushes patients to select individuals rather than institutions or 'the robot'. Also raised by continued growth of direct-pay orthopedic centers (e.g., Surgery Center of Oklahoma model) where the buyer explicitly purchases a named operator.
Rises modestly as AI absorbs the readable tier — radiograph/MRI interpretation, pre-op templating, dictation, coding, prior-auth letters — leaving a day composed disproportionately of operative work and ambiguous operate-vs-conservative conversations. This is a genuine two-tier job and the shift is underway with FDA-cleared fracture-detection tools.
Embodiment and accountability are already at ceiling; liability could reach 20 if state medical boards or CMS formalize that autonomous or semi-autonomous robotic surgical steps require a credentialed surgeon of record physically scrubbed and signing an intraoperative attestation — analogous to the ACGME/CMS teaching-physician 'key portion presence' rule already applied to resident-performed cases, extended by rule to robotic autonomy. Watch FDA's device labeling for surgeon-supervision conditions on any autonomous orthopedic cutting system.
The limit. Embodiment (20) and judgment_accountability (20) are already maxed; total headroom is ~5 points at most. At 93/100 the score is bounded by measurement, not by exposure — any further movement is cosmetic.
| New York-Newark-Jersey City, NY-NJ | 1,520 | $341,430 -5% |
| Indianapolis-Carmel-Greenwood, IN | 420 | — |
| Atlanta-Sandy Springs-Roswell, GA | 400 | $239,200 -33% |
| San Diego-Chula Vista-Carlsbad, CA | 230 | $204,290 -43% |
| Seattle-Tacoma-Bellevue, WA | 180 | $576,130 +61% |
| Houston-Pasadena-The Woodlands, TX | 150 | $83,160 -77% |
| Charlotte-Concord-Gastonia, NC-SC | 140 | $572,910 +60% |
| Boulder, CO | 130 | $211,600 -41% |
| Dallas-Fort Worth-Arlington, TX | 100 | $666,930 +86% |
| Seattle-Tacoma-Bellevue, WA | 180 | $576,130 +61% |
| Charlotte-Concord-Gastonia, NC-SC | 140 | $572,910 +60% |
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 93. 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.