Skills it runs on
The capabilities O*NET rates most important for this occupation — the human ground the work is built on.
See all skills →Industrial Engineers
Occupation · SOC 17-2112.00
Design, develop, test, and evaluate integrated systems for managing industrial production processes, including human work factors, quality control, inventory control, logistics and material flow, cost analysis, and production coordination.
Also called: Engineer · Industrial Engineer · Process Engineer · Project Engineer · Continuous Improvement Engineer · Facilities Engineer · Operations Engineer · Plant Engineer · Quality Engineer · Research and Development Engineer (R and D Engineer) · District Plant Engineer · Documentation Engineer
Job family: Architecture and Engineering Occupations
Take this to your AI
A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch
/roles/role-17-2112-00/context.md directly.
AI work map
A fast read on where AI already shows up in this occupation, where it stays a copilot, where humans remain in the loop, and what the labor market is doing. Built from observed Claude.ai conversations mapped to O*NET tasks and from published research — measures of usage and exposure, not advice or predictions that the job is going away.
Market signal
Independent published positions, read together — not a forecast.
- Growing fast employment outlook (+11.0% by 2034)
- 25,200 openings/yr
- High AI exposure
- Median pay $101,140/yr
- Work is mostly on-site (not teleworkable)
- A reversal from 2013 — rated low automation risk then (18th), high AI task-overlap now (91st)
91st-percentile task overlap — yet about 25,200 openings a year (+11% projected, BLS) . What exposure means →
AI & job outlook
What today's research says about this occupation's exposure to AI, how AI is actually being used in it, and where employment is headed. These are positions within published studies — measures of exposure and usage, not predictions that this job will disappear.
Exposure to current AI
Each study uses its own scale, so the raw scores are not comparable across rows — the percentile (this job's rank among all U.S. occupations with data) is the comparable figure, and sizes the bars.
| Measure | Rank vs all occupations | Percentile | Score |
|---|---|---|---|
| Overall AI exposure (Felten et al.) High | 80th | 1.1 | |
| LLM task exposure, γ (OpenAI / Eloundou) High | 95th | 1.0 | |
| AI assistant applicability (Microsoft) High | 81st | 0.3 |
OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.1), with simple added tooling (β 0.5), and including AI-powered software (γ 1.0). Higher means more of the job's tasks could be done at least twice as fast — not that they will be automated away.
This job mostly cannot be done remotely (Dingel–Neiman) — its hands-on tasks sit outside what software-based AI reaches.
Historical automation estimate (2013)
A pre-LLM (2013) estimate of how automatable this job is by computerization and robotics. Shown for historical context only — it is not part of any current AI ranking.
Frey–Osborne probability 0.0 · 18th percentile among occupations · Low
How AI is actually used in this job
Among measured AI assistant conversations mapped to this occupation (Anthropic Economic Index, 2026-01-15), these task types came up most. These are shares of observed AI conversations — not shares of the job, of worker time, or of what could be automated.
| Recommend methods for improving utilization of personnel, material, and utilities. | 0.8% | |
| Confer with clients, vendors, staff, and management personnel regarding purchases, product and production specifications, manufacturing capabilities, or project status. | 0.3% |
Job outlook
Independent U.S. Bureau of Labor Statistics employment projection for 2024–2034 — a labor-market forecast, not an AI-impact forecast.
| Outlook | Growing fast · +11.0% by 2034 |
| Projected annual openings | 25,200 |
| Employment 2024 → 2034 | 351,100 → 389,600 |
“Annual openings” counts new jobs plus replacements for workers who leave the occupation, so it can be large even when growth is modest.
Where this work sits on the global GenAI gradient
The ILO's 2025 global study scores generative-AI exposure on the international ISCO-08 occupation system, not US SOC. Bridged through the published (and approximate, many-to-many) IBS O*NET-SOC ↔ ISCO-08 crosswalk, this US occupation corresponds to the international occupation below. Exposure here means how much of the work's tasks today's AI can attempt — task overlap, not automation, adoption, or jobs lost.
Industrial Engineers sits at the 68th percentile of 427
occupations on the global GenAI task-exposure gradient
— exposure rose from 2023 to 2025. Each dot is one occupation; the
ringed one is this work. Exposure is task overlap, not automation or jobs lost.
37% mean task exposure (2025)
68th percentile of 427 placed occupations
+4 pts shift 2023 → 2025
| International occupation (ISCO-08) | Task exposure (2025) | Most tasks fall in |
|---|---|---|
| Industrial and Production Engineers · 2141 | 37% | Minimal |
Read the whole six-band gradient on the GenAI exposure gradient page. The crosswalk is approximate: a US occupation can map to several international ones, and the ILO scores describe the international occupation, not this exact US role.
Tasks
All 20 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.
- Estimate production costs, cost saving methods, and the effects of product design changes on expenditures for management review, action, and control. Core · importance 4.0
- Plan and establish sequence of operations to fabricate and assemble parts or products and to promote efficient utilization. Core · importance 3.9
- Analyze statistical data and product specifications to determine standards and establish quality and reliability objectives of finished product. Core · importance 3.8
- Confer with clients, vendors, staff, and management personnel regarding purchases, product and production specifications, manufacturing capabilities, or project status. Core · importance 3.8
- Communicate with management and user personnel to develop production and design standards. Core · importance 3.7
- Evaluate precision and accuracy of production and testing equipment and engineering drawings to formulate corrective action plan. Core · importance 3.7
- Recommend methods for improving utilization of personnel, material, and utilities. Core · importance 3.7
- Record or oversee recording of information to ensure currency of engineering drawings and documentation of production problems. Core · importance 3.7
- Draft and design layout of equipment, materials, and workspace to illustrate maximum efficiency using drafting tools and computer. Core · importance 3.6
- Direct workers engaged in product measurement, inspection, and testing activities to ensure quality control and reliability. Core · importance 3.6
- Develop manufacturing methods, labor utilization standards, and cost analysis systems to promote efficient staff and facility utilization. Core · importance 3.5
- Review production schedules, engineering specifications, orders, and related information to obtain knowledge of manufacturing methods, procedures, and activities. Core · importance 3.5
- Complete production reports, purchase orders, and material, tool, and equipment lists. Core · importance 3.4
- Coordinate and implement quality control objectives, activities, or procedures to resolve production problems, maximize product reliability, or minimize costs. Core · importance 3.4
- Implement methods and procedures for disposition of discrepant material and defective or damaged parts, and assess cost and responsibility. Core · importance 3.4
- Apply statistical methods and perform mathematical calculations to determine manufacturing processes, staff requirements, and production standards. Core · importance 3.4
- Study operations sequence, material flow, functional statements, organization charts, and project information to determine worker functions and responsibilities. Core · importance 3.3
- Regulate and alter workflow schedules according to established manufacturing sequences and lead times to expedite production operations. Supplemental · importance 3.2
- Formulate sampling procedures and designs and develop forms and instructions for recording, evaluating, and reporting quality and reliability data. Core · importance 3.1
- Schedule deliveries based on production forecasts, material substitutions, storage and handling facilities, and maintenance requirements. Supplemental · importance 3.1
Work activities
- Analyze project data to determine specifications or requirements.
- Develop technical methods or processes.
- Recommend technical design or process changes to improve efficiency, quality, or performance.
- Determine operational methods.
- Analyze design or requirements information for mechanical equipment or systems.
- Create graphical representations of industrial production systems.
- Review technical documents to plan work.
- Confer with technical personnel to prepare designs or operational plans.
- Devise research or testing protocols.
- Document technical design details.
- Supervise engineering or other technical personnel.
- Implement design or process improvements.
- Evaluate designs or specifications to ensure quality.
- Prepare procedural documents.
- Prepare contracts, disclosures, or applications.
- Prepare operational reports.
- Schedule operational activities.
- Estimate operational costs.
- Direct quality control activities.
- Discuss designs or plans with clients.
- Communicate technical information to suppliers, contractors, or regulatory agencies.
Knowledge, skills & abilities
O*NET importance rating, from 1 (not important) to 5 (extremely important).
Knowledge
Essential skills
| Reading Comprehension | 4.0 | |
| Active Listening | 4.0 | |
| Critical Thinking | 4.0 | |
| Speaking | 3.9 | |
| Writing | 3.8 | |
| Monitoring | 3.4 | |
| Mathematics | 3.3 | |
| Active Learning | 3.3 |
Abilities
| Oral Comprehension | 4.0 | |
| Written Comprehension | 4.0 | |
| Oral Expression | 4.0 | |
| Written Expression | 4.0 | |
| Deductive Reasoning | 4.0 | |
| Inductive Reasoning | 4.0 | |
| Problem Sensitivity | 3.9 | |
| Information Ordering | 3.6 | |
| Near Vision | 3.6 | |
| Category Flexibility | 3.4 | |
| Selective Attention | 3.4 | |
| Fluency of Ideas | 3.3 | |
| Originality | 3.3 | |
| Speech Recognition | 3.3 | |
| Speech Clarity | 3.3 | |
| Mathematical Reasoning | 3.1 |
Transferable skills
| Complex Problem Solving | 3.9 | |
| Systems Analysis | 3.3 | |
| Systems Evaluation | 3.3 | |
| Coordination | 3.1 | |
| Judgment and Decision Making | 3.1 |
Skills in demand
Skills employers ask for in job postings for this occupation (Lightcast), with whether each is a common or specialized skill.
Showing the top 40 of 54.
Tools & technology
Showing the top 40 of 102.
Work context
How characteristic each condition is of the job, on O*NET's 1–5 context scale (higher = more present in day-to-day work). Each condition links to how it varies across all occupations.
How to get in
- Job zone
- Zone 4 — Job Zone Four: Considerable Preparation Needed
- Education
- Most of these occupations require a four-year bachelor's degree, but some do not.
- Typical entry-level education
- Bachelor's degree · BLS, the typical path — not a requirement
- Related experience
- A considerable amount of work-related skill, knowledge, or experience is needed for these occupations. For example, an accountant must complete four years of college and work for several years in accounting to be considered qualified.
- Preparation level
- SVP (7.0 to < 8.0) — total schooling plus on-the-job experience.
What to study: Engineering , Engineering/Engineering-Related Technologies/Technicians . Fields of study crosswalked to this occupation (NCES CIP–SOC), not a requirement.
Education of current workers
Share of people in this occupation at each level of education.
| Bachelor's Degree | 58.6% | |
| Some College Courses | 15.8% | |
| Master's Degree | 11.1% | |
| High School Diploma | 7.5% | |
| Post-Baccalaureate Certificate | 4.4% | |
| Associate's Degree (or other 2-year degree) | 2.6% |
Interests & work styles
The interests and personal qualities O*NET associates with people who do this work.
Interest areas
| Engineering | 5.6 | |
| Mathematics/Statistics | 4.7 | |
| Mechanics/Electronics | 3.5 | |
| Management/Administration | 3.3 | |
| Accounting | 2.7 | |
| Information Technology | 2.7 | |
| Office Work | 2.3 | |
| Business Initiatives | 2.3 |
Career interests (Holland / RIASEC)
| Conventional | 5.3 | |
| Investigative | 5.0 | |
| Realistic | 5.0 | |
| Enterprising | 3.3 |
Work styles
| Dependability | 5.0 | |
| Attention to Detail | 4.0 | |
| Intellectual Curiosity | 3.0 | |
| Innovation | 2.1 |
Wages & employment
U.S. · annual wages (BLS OEWS)
| 10th percentile | $70,000 |
| 25th percentile | $81,910 |
| Median (50th) | $101,140 |
| 75th percentile | $127,480 |
| 90th percentile | $157,140 |
| People employed | 350,230 |
Industries that employ this occupation
Where these workers are employed, by number of jobs (national, BLS OEWS). Pay shown is the occupation's national median, not industry-specific.
| Industry | Workers | National median pay |
|---|---|---|
| Manufacturing · Sector | 237,030 | $100,060 |
| Professional, Scientific, and Technical Services · Sector | 50,290 | $106,420 |
| Engineering Services · National industry | 20,150 | $101,930 |
| Management of Companies and Enterprises · Sector | 15,770 | $115,210 |
| Wholesale Trade · Sector | 15,570 | $101,700 |
| Transportation and Warehousing · Sector | 7,860 | $97,440 |
| Testing Laboratories and Services · National industry | 4,630 | $102,360 |
| Machine Shops · National industry | 3,050 | $83,820 |
| Information · Sector | 2,170 | $128,220 |
| Mining, Quarrying, and Oil and Gas Extraction · Sector | 2,110 | $148,850 |
| Construction · Sector | 2,000 | $96,320 |
| Other Services (except Public Administration) · Sector | 1,380 | $92,320 |
Where this work is most concentrated
Industries where this occupation is far more common than in the economy as a whole. The location quotient is how many times more concentrated it is here (a value of 5 means five times its economy-wide share).
| Industry | Concentration | Workers |
|---|---|---|
| Testing Laboratories and Services · National industry | 11.96× | 4,630 |
| Manufacturing · Sector | 8.18× | 237,030 |
| Engineering Services · National industry | 7.67× | 20,150 |
| Machine Shops · National industry | 5.17× | 3,050 |
| Management of Companies and Enterprises · Sector | 2.47× | 15,770 |
| Professional, Scientific, and Technical Services · Sector | 2.06× | 50,290 |
| Mining, Quarrying, and Oil and Gas Extraction · Sector | 1.62× | 2,110 |
| Nuclear Electric Power Generation · National industry | 1.42× | 120 |
Related occupations
Part of the Advanced Manufacturing career cluster.
- Industrial Engineering Technologists and Technicians · 17-3026.00 Compare →
- Manufacturing Engineers · 17-2112.03 Compare →
- Industrial Production Managers · 11-3051.00 Compare →
- Validation Engineers · 17-2112.02 Compare →
- Mechanical Engineers · 17-2141.00 Compare →
- Logistics Engineers · 13-1081.01 Compare →
- Mechatronics Engineers · 17-2199.05 Compare →
- Electrical Engineers · 17-2071.00 Compare →
- Materials Engineers · 17-2131.00 Compare →
- Human Factors Engineers and Ergonomists · 17-2112.01 Compare →
- Mechanical Engineering Technologists and Technicians · 17-3027.00 Compare →
- Quality Control Systems Managers · 11-3051.01 Compare →
Side-by-side comparisons place two occupations’ pay, preparation, skills, and AI exposure on the same page — same data, same scale, no forecast.
What you can do with this
Options the data surfaces for Industrial Engineers — not advice or a forecast. Each is a real cross-link you can follow into the evidence.
Skills that travel
Capabilities this work builds that are used across many other occupations.
Adjacent roles
Occupations O*NET rates as related — the nearby moves on the map.
Paths in
How people typically prepare for this work.
- Bachelor's degree · typical entry level
- Job zone 4 — Job Zone Four: Considerable Preparation Needed · preparation tier
- Engineering · field of study
- Engineering/Engineering-Related Technologies/Technicians · field of study
Zoom out
On the global GenAI exposure gradient this work sits around the 68th percentile of 427 international occupations.
Write a report on thisheadline · factoids · citation
Industrial Engineers show 91st-percentile AI task overlap — and about 25,200 annual U.S. openings
- Industrial Engineers rank in the 91st percentile (High band) for AI task overlap across U.S. occupations — a measure of how much of the work today's AI can attempt, not how much is automated.Eloundou et al. (GPTs are GPTs) + Felten AIOE
- The occupation is projected to see about 25,200 U.S. job openings per year (2024–34), counting growth and replacement — a labor-demand projection made independently of AI.BLS Employment Projections 2024–34
- BLS projects employment to be growing fast (+11%) from 2024 to 2034.BLS Employment Projections 2024–34
- Median annual pay is $101,140, across about 350,230 U.S. workers.BLS OEWS (May 2024)
Copy the whole kit
Industrial Engineers show 91st-percentile AI task overlap — and about 25,200 annual U.S. openings • Industrial Engineers rank in the 91st percentile (High band) for AI task overlap across U.S. occupations — a measure of how much of the work today's AI can attempt, not how much is automated. (Eloundou et al. (GPTs are GPTs) + Felten AIOE) • The occupation is projected to see about 25,200 U.S. job openings per year (2024–34), counting growth and replacement — a labor-demand projection made independently of AI. (BLS Employment Projections 2024–34) • BLS projects employment to be growing fast (+11%) from 2024 to 2034. (BLS Employment Projections 2024–34) • Median annual pay is $101,140, across about 350,230 U.S. workers. (BLS OEWS (May 2024)) Source: Singulariki — "Industrial Engineers". https://singulariki.com/roles/role-17-2112-00 Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.
AssetsShare imageMethodology & sourcesPress & newsroomThe newsroom
Every line is built only from figures this page already shows and cites. AI task overlap means what today's AI can attempt — not automation, job loss, or a forecast.
Sources for this page
Every figure above traces to a named public dataset and the exact release below — not hand-written opinion. See the full methodology for what each measure does and does not mean.
- O*NET 30.3 U.S. Department of Labor / National Center for O*NET Development
- BLS Occupational Employment and Wage Statistics (OEWS) May 2024 U.S. Bureau of Labor Statistics
- BLS Employment Projections 2024–2034 U.S. Bureau of Labor Statistics
- Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27) Anthropic
- Microsoft “Working with AI” working-with-ai Microsoft Research
- “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130 OpenAI / academic
- AI Occupational Exposure (AIOE) Felten, Raj & Seamans academic
- ILO / Gmyrek et al. GenAI exposure gradient 2025 International Labour Organization
- IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022 Institute for Structural Research (IBS)
- Frey & Osborne (2013) frey-osborne-automation academic
- Dingel & Neiman (2020) dingel-neiman-workathome academic
Data compiled June 2, 2026. Figures are estimates, not advice.
Cite this page
Plain
Singulariki. "Industrial Engineers." Singulariki: a source-backed encyclopedia of work. Built from O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026. https://singulariki.com/roles/role-17-2112-00
APA
Singulariki. (2026). Industrial Engineers. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-17-2112-00
BibTeX
@misc{singulariki-role-17-2112-00,
title = {Industrial Engineers},
author = {{Singulariki}},
year = {2026},
note = {O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026},
url = {https://singulariki.com/roles/role-17-2112-00}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.