EXPOSED
The analytical half of this job — compiling production data, calculating cycle times and yields, building layout drawings from measurements, writing work instructions and process documentation, and preparing cost and efficiency reports — is exactly the pattern-and-text work current AI plus MES/sensor data does cheaply. What holds is the plant-floor half: walking the line, timing actual operators, catching the informal workarounds that never appear in the data, and physically piloting a fixture or layout change. There is no license or signature requirement here, so the moat is presence and shop-floor credibility, not regulation.
Dipped in 2020, then grew past where it started.
Median pay $56,550 → $66,120 -6.5% 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
+1.7% 74,600 → 75,900 on the projections basis
Exposed, but growing
AI can already do a lot of these tasks, and the BLS still expects +1.7% 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.
~6,300 openings a year on average, including replacing people who leave.
PlannerSchedulerScientistSoda TesterYarn TesterCloth TesterPaper TesterTool PlannerWoolen TesterNanotechnicianAnalysis TesterLine TechnicianTest TechnicianLiaison EngineerMachine OperatorMaterial PlannerMethods EngineerNanotechnologistProcess OperatorQuality EngineerCellophane TesterEfficiency ExpertProduction ExpertReal Time Analyst
Holding it up: embodiment . Weakest point: liability shield .
Mixed — a routine tier and a judgment tier Time studies, cycle-time calculations, yield tabulations, layout CAD updates and standard-work documentation are already generated from MES/PLC and machine-vision data, but the parts that require standing at station 6 to see the operator's undocumented workaround, or running a fixture trial across three shifts to find out why it fails on second shift, still need a person — so roughly half the task list holds, not more.
Some physical or field component You are on the floor with a tape measure, stopwatch, and calipers doing takt observations, staging pilot cells, and moving conveyor and bench positions during changeovers, but it is a controlled indoor plant with fixed equipment and a maintenance crew doing the actual rigging — physical, not a field trade in weather or confined space.
No licence, no signature requirement There is no state license or PE stamp attached to this role; the process change you spec goes out under the plant engineering manager's or PE's approval, and the ISO/AS9100 documentation you write is signed off by quality management, so nothing in your work product is legally yours to defend.
Meaningful discretion You decide which station to time, which of two layout options to pilot, and whether an observed cycle is representative or an outlier — real calls with cost consequences — but they run inside standard-work methodology, lean/Six Sigma protocol and existing routings, and a capital or safety-relevant change goes up to engineering for the decision.
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 (2/20) is whether the law requires a licensed human to sign. Trust premium (6/20) 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 16 of this occupation's 36 points (44%).
Embodiment (11/20) 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.
Engineers, All Other EXPOSED
Mechanical Engineers EXPOSED
Electrical Engineers EXPOSED
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 49/100, still EXPOSED.
If MES/digital-twin systems absorb the report-writing, cycle-time math and layout drafting tier, the residual role becomes time-study validation against actual operator behavior, root-cause investigation of variance the data can't explain, and physical pilot runs — a genuinely two-tier job where the surviving tier is observation-and-judgment heavy
If OSHA's ergonomics/musculoskeletal rulemaking or a state analogue (e.g. California's Cal/OSHA indoor heat and ergonomic standards) requires a named, qualified person to document and attest to workstation ergonomic assessments, the ergonomics-assessment portion of this role gains a signature requirement; similarly if machine-safeguarding risk assessments under ANSI B11.0 / ISO 12100 become an audited, individually-signed deliverable in OEM contracts
If line changeovers shift further toward high-mix/low-volume and reshored small-batch production (semiconductor fab tooling, medical device, defense suppliers under DoD reshoring contracts), more of the work is physically re-fixturing, re-balancing and re-timing unstable stations rather than optimizing a stable line
If aerospace/medical quality regimes (AS9100, FDA 21 CFR 820 process validation, IATF 16949 PPAP) increasingly name an individual technologist as the person who owns process validation and change-control sign-off — and audits trace nonconformance back to that name — the role owns consequential calls with traceable ownership
The limit. Ceiling is low. Trust premium has no realistic route: the buyer is an internal manufacturing manager who wants cost per unit down and has no preference for a human analyst. Liability gains, if any, attach to the PE or the quality manager above this role rather than to the technician; the credential here is an associate degree or certificate, not a license, and no state board is moving to license industrial engineering technicians.
| Minneapolis-St. Paul-Bloomington, MN-WI | 4,340 | $73,060 +10% |
| Detroit-Warren-Dearborn, MI | 2,770 | $76,190 +15% |
| Phoenix-Mesa-Chandler, AZ | 1,760 | $65,120 -2% |
| Boston-Cambridge-Newton, MA-NH | 1,580 | $74,250 +12% |
| Cincinnati, OH-KY-IN | 1,480 | $77,600 +17% |
| Houston-Pasadena-The Woodlands, TX | 1,470 | $77,190 +17% |
| Chicago-Naperville-Elgin, IL-IN | 1,430 | $74,890 +13% |
| New York-Newark-Jersey City, NY-NJ | 1,390 | $75,260 +14% |
| Beaumont-Port Arthur, TX | 70 | $121,320 +83% |
| Midland, TX | 30 | $114,140 +73% |
| San Jose-Sunnyvale-Santa Clara, CA | 1,000 | $90,660 +37% |
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 36. 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.