SAFE
The core of this job is cutting, dissecting, controlling bleeding, and improvising inside a living body when anatomy doesn't match the textbook — surgical robots today are master-slave tools that amplify a surgeon's hands, not replace them. AI is already competitive on the screen-based periphery: reading imaging, drafting operative notes, coding procedures, and triaging pre-op risk. What it cannot do is stand at the table and own the decision to convert an approach mid-case, or sit with a family after a complication.
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
+3.9% 25,100 → 26,000 on the projections basis
Hard to automate, and growing
The work resists current AI and the BLS projects +3.9% 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.
~600 openings a year on average, including replacing people who leave.
NeurosurgeonBrain SurgeonCardiac SurgeonPlastic SurgeonThoracic SurgeonVascular SurgeonColorectal SurgeonSurgical OncologistNeurological SurgeonCardiovascular SurgeonReconstructive Surgeon
The BLS uses Surgeons, All Other for work that doesn't fit any named occupation, so it covers roles that have little in common with each other. Two consequences worth knowing before you read anything below:
Holding it up: embodiment . Weakest point: task resistance .
Tasks largely resist digitisation Dissecting through scarred or distorted planes, achieving hemostasis when a vessel tears unexpectedly, and deciding intraoperatively to convert laparoscopic to open are tasks with no digital substitute; 17 rather than 20 because pre-op imaging review, operative note dictation, CPT coding, and risk stratification are already being handed to models.
Hands-on in uncontrolled environments You are scrubbed, gowned, and physically inside a body cavity whose anatomy varies patient to patient, working under retraction and bleeding — nothing about tying a knot deep in a pelvis or palpating tissue for tumor margins can happen off-site, which is why this sits at the ceiling.
Licensed human required and personally liable State medical licensure, board certification, hospital credentialing and privileging by procedure, and a surgical consent form carrying your name mean malpractice exposure for a retained instrument or wrong-site case lands personally on you, not on any device manufacturer or software vendor.
Exists to be accountable for ambiguous calls Deciding whether an unresectable finding means aborting versus proceeding, when to accept a damage-control approach and come back another day, and how to weigh a frail patient's odds against no operation are calls made with incomplete information and no protocol to hide behind; slightly below ceiling because guidelines, tumor boards, and M&M review do constrain the space.
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 (20/20) is whether the law requires a licensed human to sign. Trust premium (18/20) is whether buyers specifically pay for a person. Judgment and accountability (18/20) 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 99/100, still SAFE.
As AI absorbs the screen-based periphery (imaging pre-reads, op-note drafting, CPT coding, pre-op risk stratification), the residual day becomes almost entirely intraoperative judgment and improvisation — the tier machines cannot touch. Watch for CMS/AMA acceptance of AI-drafted operative documentation as billable without surgeon re-dictation.
Formal designation of a 'responsible surgeon of record' for autonomous or semi-autonomous robotic steps — e.g. FDA post-market requirements for supervised-autonomy devices (as flagged in FDA's discussion of adaptive AI/ML device oversight) naming a human owner of each intraoperative decision node.
Hospital credentialing or malpractice-insurer rules requiring disclosed consent when any autonomous robotic step is used, creating an explicit patient election of a fully human-performed operation.
The limit. Embodiment and liability_shield are already at 20; the composite is near ceiling and these levers move it by rounding at most. Nothing here changes the occupation's standing in practice.
| New York-Newark-Jersey City, NY-NJ | 4,290 | $399,990 -3% |
| Houston-Pasadena-The Woodlands, TX | 560 | $80,140 -81% |
| Boston-Cambridge-Newton, MA-NH | 520 | $386,300 -7% |
| San Diego-Chula Vista-Carlsbad, CA | 490 | — |
| Dallas-Fort Worth-Arlington, TX | 470 | $494,800 +20% |
| Urban Honolulu, HI | 410 | — |
| Indianapolis-Carmel-Greenwood, IN | 360 | $459,300 +11% |
| Chicago-Naperville-Elgin, IL-IN | 340 | $462,620 +12% |
| Milwaukee-Waukesha, WI | 140 | $762,360 +84% |
| Greenville-Anderson-Greer, SC | 70 | $630,540 +52% |
| Charleston, WV | 60 | $619,320 +50% |
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.