COOKED
The core loop — read a print, set stops and speeds, load and unload parts, drill or bore to spec, gauge with calipers and micrometers — is exactly what CNC machining centers, automatic tool changers, and pallet loaders were built to absorb, and the modal worker here is tending rather than programming. Physical presence in a shop keeps a floor under this job, but it's a controlled, repeatable environment, which is where industrial automation is strongest and where a robot cell pays back fastest. No licensure, no client relationship, and very little discretion beyond scrapping a bad part; employment is already down to under 5,000 nationally, which tells you where the trend went.
Part 2020 shock, part continued decline in the years since.
Median pay $38,910 → $49,080 +0.9% 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
-19.6% 5,300 → 4,300 on the projections basis
Exposed, and shrinking
Both signals point the same way: the tasks are largely automatable and the BLS projects -19.6% by 2034. This is the case where the score and the forecast agree, and it is the one worth taking seriously.
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.
BorerJiggerReamerTapperDrillerBroacherHub BorerDice MakerRecentererSpot FacerTest BorerWheel BorerChoke ReamerTrade MarkerCountersinkerDrill PresserPlate DrillerBarrel DrillerBillet DrillerCollet DrillerDrill OperatorPunch OperatorJigger OperatorTapper Operator
Holding it up: embodiment . Weakest point: liability shield .
Mixed — a routine tier and a judgment tier Setting a drill jig, indicating a workpiece true, changing a dull twist drill and holding a bore to a few tenths still needs a person on a manual or semi-auto machine, but the print-to-part loop is fully proceduralized and a CNC machining center with a tool changer does the same hole pattern unattended — a 9 rather than a 4 because deep-hole work, odd fixturing and short-run job-shop parts still get set up by hand.
Hands-on in uncontrolled environments You are standing at the machine loading castings, clamping in a vise, blowing chips, flooding coolant and pulling parts to the surface plate — but it's a bolted-down machine on a shop floor with known part geometry, not a job site, which is why this sits at 13 and not at the 17-plus of a field millwright.
No licence, no signature requirement Nothing you drill requires you to hold a licence or sign for it; NIMS credentials and blueprint-reading certificates help you get hired but the shop's quality department and the customer's PPAP paperwork carry the liability, so there is no legal barrier stopping a robot from doing the operation.
Executes defined procedures on defined inputs Your calls are bounded by the setup sheet and the feed-and-speed chart — pull a chipped drill, re-indicate a part that's running out, scrap one that's oversize, flag the inspector — real decisions with real consequences for scrap cost, but every one of them has a defined right answer, which is why this is a 4 and not a 10.
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 (9/20 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 (2/20) is whether buyers specifically pay for a person. Judgment and accountability (4/20) 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 7 of this occupation's 29 points (24%).
Embodiment (13/20) 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.
Sheet Metal 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 42/100 — EXPOSED.
Task-mix shift within the shrinking headcount: if the remaining 4,680 jobs consolidate into short-run, one-off boring work on large weldments, castings and repair parts (line boring, mill-turn of oversized housings) where fixturing and datum-finding must be improvised per part and no CNC program pays back, the residual job is setup judgment rather than tending. Watch job postings shifting from 'machine tender' to 'manual boring mill / line boring machinist' in job-shop and MRO segments.
Migration of the work to field/in-situ boring — on-site line boring of excavator pins, turbine casings, ship sterntubes, bridge bearings — where the machine is clamped to the workpiece in an unstructured environment rather than the part being brought to a shop. This is a real and growing MRO niche (portable line boring service firms); reclassification of these workers into 51-4032 would raise the physical-unpredictability component.
Formal assignment of first-article and in-process disposition authority to the operator under a customer PPAP or AS9102 first-article regime — the operator, not a separate inspector or engineer, owns the accept/scrap/rework call on parts where scrap cost is high (large castings, long-lead forgings). Some job shops already collapse inspection into the setter role as inspection headcount is cut.
Extension of code-stamp / traceability regimes down to the operator level: e.g. AS9100 or NADCAP audit requirements, or an ASME Section III nuclear-component rule, mandating that a named, qualified operator sign the setup and first-article record for safety-critical hole locations, with that signature auditable in a fashion that attaches personal consequence. Today AS9100 requires records but rarely names the operator as the accountable signer.
The limit. Even with all of these, this is a sub-5,000-worker occupation with no licensure and no client-facing relationship; trust_premium has no plausible route — nobody specifies a human-drilled hole — and the realistic ceiling is roughly the low 40s, reached mainly by the occupation shrinking into its field-service and one-off-setup tier rather than by any institutional protection appearing.
| Los Angeles-Long Beach-Anaheim, CA | 400 | $49,080 +0% |
| Tulsa, OK | 180 | $58,210 +19% |
| San Jose-Sunnyvale-Santa Clara, CA | 130 | $50,920 +4% |
| Chicago-Naperville-Elgin, IL-IN | 110 | $35,660 -27% |
| Houston-Pasadena-The Woodlands, TX | 90 | $46,460 -5% |
| Detroit-Warren-Dearborn, MI | 80 | $63,320 +29% |
| New York-Newark-Jersey City, NY-NJ | 80 | $50,810 +4% |
| Pittsburgh, PA | 80 | $40,170 -18% |
| Boston-Cambridge-Newton, MA-NH | 60 | $79,120 +61% |
| Detroit-Warren-Dearborn, MI | 80 | $63,320 +29% |
| Tulsa, OK | 180 | $58,210 +19% |
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 29. 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.