← Risk register SOC 17-2112 · reviewed 2026-08-11

Industrial Engineers

365,740 US workers · median $102,440/yr · Engineering

EXPOSED

Much of the day-to-day — time-and-motion data crunching, throughput and capacity models, layout drafting, cost-benefit spreadsheets, work-instruction and SOP writing, Six Sigma report decks — is exactly the structured analysis and document work AI now does quickly. What holds is the part that happens on the plant floor: walking the line, seeing why the model's assumptions are wrong, negotiating a changed process with operators and supervisors who have to live with it, and owning the decision when a $2M line reconfiguration goes sideways. PE licensure exists for IEs but is rarely a legal requirement to practice, so the regulatory shield is thin compared to civil or electrical.

10-year outlook: Headcount holds roughly flat but the job shifts from producing analyses to validating machine-generated ones and driving them onto the floor; pure modeling-and-reporting IE roles shrink first.

US employment, 2019–2025+25.4%
291,710365,740 workers

Headcount grew steadily across the period.

Median pay $88,020 → $102,440 -6.9% in real terms (nominal +16.4%, less ~25% US inflation over the period)

The job count is not the verdict

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

+11% 351,100 → 389,600 on the projections basis

Exposed, but growing

AI can already do a lot of these tasks, and the BLS still expects +11% 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.

~25,200 openings a year on average, including replacing people who leave.

One email if this score changes. Watch as many occupations as you like from the same address — no account, and nothing is sent on a schedule, only when a verdict actually moves.

Also known as — 24 job titles this covers

Titles reported by people doing this work, from the US Department of Labor's O*NET survey. If your job title is here, this page is about your work even though the name doesn't match.

EngineerErgonomistMetrologistFactory ExpertField EngineerPlant EngineerDesign EngineerFailure AnalystSystem EngineerFactory EngineerLiaison EngineerMethods EngineerProcess EngineerProject EngineerQuality EngineerSalvage EngineerEfficiency ExpertFacility EngineerProduction ExpertCognitive EngineerEfficiency AnalystEquipment EngineerInterface DesignerLogistics Engineer

Score — 43/100 resistance

Holding it up: judgment & accountability (12/20). Weakest point: liability shield (5/20).

Five dimensions, 0–20 each, summed. Higher means more protected. The arithmetic is shown so you can check it: 10 + 9 + 5 + 7 + 12 = 43. · Scored 2026-08-11, and re-examined when evidence accumulates rather than on a schedule.

Task resistance 10/20

Mixed — a routine tier and a judgment tier At 10, roughly half the workweek — pulling MES/ERP data into throughput models, running discrete-event simulations, drafting value-stream maps and standard work sheets, building line-balance calculations — is already reproducible by tooling, while the other half (standing at a bottleneck station watching an operator's actual reach and cycle, discovering the routing file has been wrong for two years) still requires a person physically present to notice what no data set recorded.

Embodiment 9/20

Some physical or field component A 9 reflects that the plant, warehouse, or hospital floor is a real and recurring workplace — gemba walks, time studies with a stopwatch at the station, verifying machine clearances against the layout, commissioning a new cell — but you are not the one wrenching on the fixture or wiring the conveyor, and a large share of the job is done in a spreadsheet or simulation package at a desk.

Liability shield 5/20

Certification preferred, not legally required A 5, not 0, because PE licensure and the Industrial and Systems Engineering exam exist and matter for some defense, utility, and consulting work, and Six Sigma Black Belt or CQE certification is often written into the job posting — but no statute stops an unlicensed analyst from redesigning a production line, and the signature on a capital request is usually the plant manager's, not yours.

Trust premium 7/20

Some relationship component At 7, the credibility you build with a shift supervisor who has been burned by three prior efficiency projects is what makes a process change actually stick, but you are typically an internal staff function serving whichever plant you are assigned to, and the deliverable — a validated layout, a cycle-time reduction — is judged on the number, not on who produced it.

Judgment & accountability 12/20

Meaningful discretion A 12 recognises that you choose which constraint to attack, which line to shut down for a rebuild, and whether the simulation's confidence interval is enough to commit capital — decisions with seven-figure and headcount consequences — but they are made inside a stage-gate process with a capital approval committee, operations management, and often EHS review above you, so the ambiguity is shared rather than owned outright.

Confidence: medium · reviewed 2026-08-11 · how scoring works

What this job involves — and which parts are yours

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.

AI already does these at usable quality

These still need a person

Active moats on the surviving side: judgment, physical-presence

How to future-proof this job

Training paths for your skill gaps: Khan Academy — physics, chemistry and biology from the ground up free · MIT OpenCourseWare — operations management free · edX — operations management and process monitoring courses free to audit · MIT OpenCourseWare — circuits, systems and diagnostic method, free and ungated free · Coursera — project coordination and cross-team delivery free to audit · Coursera — work planning and personal productivity free to audit · MIT OpenCourseWare — finance and accounting free · edX — supply chain and inventory management free to audit · freeCodeCamp — full curriculum, certification at the end free · Coursera — decision making under uncertainty free to audit

All 35 skills ranked by how many jobs they open →

Where this experience transfers — occupations you could move toward

Computed from U.S. Dept. of Labor O*NET skill and knowledge profiles: high overlap with what you already do, a materially higher resistance score, no large jump in required training, and no licence you would have to start a new pipeline to get. Targets that pay meaningfully less, that are themselves COOKED, or whose own headcount is falling are excluded — a move into a shrinking trade is not an escape.

Nuclear Engineers EXPOSED · 57/100 · you already have ~85% of the skill profile

Skills to close: Science, Operations Analysis, Operations Monitoring, Troubleshooting

Architectural and Engineering Managers EXPOSED · 56/100 · you already have ~85% of the skill profile

Skills to close: Coordination, Time Management

Mining and Geological Engineers, Including Mining Safety Engineers SAFE · 68/100 · you already have ~83% of the skill profile

Skills to close: Management of Financial Resources, Management of Material Resources, Programming, Judgment and Decision Making

What would move this back up — beyond any one person

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 60/100, still EXPOSED.

5 specific changes that would raise this score
  • already happening task resistance +3

    Task-mix shift is genuine here: the routine tier (time studies, capacity spreadsheets, SOP drafting, DMAIC decks) automates first, leaving the tier that requires being on the floor to detect why the model's assumptions are false and to negotiate a process change operators will actually follow. Recognisable if IE job postings shift toward continuous-improvement leadership, shopfloor change management, and automation commissioning rather than analysis deliverables.

  • plausible liability shield +5

    State industrial-exemption rollback: if a state board narrows the industrial exemption in its Engineering Practice Act so that manufacturing facility layouts, guarding, and process safety documents must be sealed by a licensed PE (as several states have debated for utility and manufacturing plants), IE sign-off becomes personally liable rather than optional. Watch also OSHA PSM (29 CFR 1910.119) process hazard analysis and machine-guarding certifications being tied explicitly to a named licensed engineer, and insurer requirements: workers' comp and property carriers (FM Global, Travelers) conditioning coverage on a credentialed engineer certifying ergonomic/line-change assessments.

  • plausible judgment accountability +4

    Capital-approval governance that names an accountable engineer: if corporate CapEx policies and audit requirements (SOX-adjacent internal controls over capital projects) require a named engineer of record to attest to throughput/ROI assumptions behind an automation or line-reconfiguration investment, the ambiguity call becomes formally owned. Similarly, if AI-model-governance rules (e.g., internal frameworks aligned to NIST AI RMF) require a human to sign as accountable for digital-twin and scheduling model outputs used in production decisions.

  • plausible embodiment +3

    If IE scope absorbs commissioning and validation of robotic cells, AMRs, and cobot workcells — physically walking off clearances, verifying guarding and light curtains, running FAT/SAT on the floor — the role gains irreducible in-plant presence. Visible in aerospace/auto plants where IEs already own automation ramp-up and in pharma where installation/operational qualification (IQ/OQ under FDA 21 CFR 211) must be witnessed on site.

  • unlikely trust premium +2

    Narrow route only: union or works-council agreements that require a human engineer, not a vendor algorithm, to conduct and present time standards and ergonomic assessments — UAW-style contract language on work standards and line speed is the existing precedent. This is a bargaining-table premium, not a consumer one; it would not extend to internal corporate clients generally.

The limit. The binding constraint is that IEs mostly serve internal corporate clients who buy outcomes, not a signature or a person, and the industrial exemption keeps PE licensure optional in most states. Without an exemption rollback the liability shield stays thin, so realistic total ceiling is roughly the mid-50s — the floor is presence and ownership on the plant floor, not credential scarcity.

These are conditions, not forecasts — what would have to happen, not what will. Specific rules, cases and bills are named so you can go and check whether they exist and where they stand; verify before relying on any of them. Nothing here is legal or financial advice.

Where this work is, and what it pays there

BLS metro figures for 352 areas. The verdict above does not change by city — the rubric judges what the work involves, not where it happens — but pay and headcount do, and the national median hides a very wide range.

Most of these jobs

Detroit-Warren-Dearborn, MI 17,350 $104,110 +2%
Minneapolis-St. Paul-Bloomington, MN-WI 13,970 $104,730 +2%
Chicago-Naperville-Elgin, IL-IN 12,750 $101,760 -1%
Los Angeles-Long Beach-Anaheim, CA 11,460 $113,040 +10%
Dallas-Fort Worth-Arlington, TX 10,680 $105,640 +3%
Boston-Cambridge-Newton, MA-NH 9,010 $118,970 +16%
Houston-Pasadena-The Woodlands, TX 8,620 $111,690 +9%
New York-Newark-Jersey City, NY-NJ 8,540 $105,840 +3%

Best paid

Anchorage, AK 110 $171,910 +68%
Charleston, WV 160 $143,860 +40%
Midland, TX 320 $141,120 +38%

Percentages are against this occupation's national median of $102,440. Counts are jobs in that metro, not vacancies. Metros where the BLS suppressed the cell are absent rather than shown as zero.

Who is actually doing this

The score above is about what the work exposes. This is reporting about real deployments in this occupation — the difference between "could be automated" and "somebody automated it."

Toyota

1 of 1 reported case, with sources

Quick take — do you do this job?

Has AI actually changed your work? One tap, anonymous, and the running tally is public. Nothing else is asked of you.

Self-reported and unverified — a sentiment signal, not a survey. One response per person per occupation; you can change your answer.

Field reports — what people say has changed

No field reports yet. A written account takes a paragraph rather than a tap, goes to an editor before it appears, and is the one thing on this page the rubric cannot produce on its own.

File a field report

Concrete beats general: a tool that arrived, a task that moved, a headcount decision you watched happen. Don't include anything that identifies you or your employer if that would put you at risk.

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