Often handed to AI
Task areas most often handled directively in observed AI conversations — candidates to delegate with light review.
- Enter codes and instructions to program computer-controlled machinery. · 4.0%
Industrial Machinery Mechanics
Occupation · SOC 49-9041.00
Repair, install, adjust, or maintain industrial production and processing machinery or refinery and pipeline distribution systems. May also install, dismantle, or move machinery and heavy equipment according to plans.
Also called: Industrial Machinery Mechanic · Maintenance Technician · Mechanic · Overhauler · Industrial Mechanic · Loom Fixer · Loom Technician · Machine Adjuster · Machine Mechanic · Sewing Machine Mechanic · Anode Rebuilder · Appliance Fixer
Job family: Installation, Maintenance, and Repair Occupations
Take this to your AI
A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch
/roles/role-49-9041-00/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.
Keep a human in the loop
Task areas where a human was still judged necessary in a large share of observed conversations — not a safety ruling, an observed-need signal.
- Enter codes and instructions to program computer-controlled machinery. · 68.2% need a human
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 →Market signal
Independent published positions, read together — not a forecast.
- Growing fast employment outlook (+16.1% by 2034)
- 45,700 openings/yr
- Low AI exposure
- Observed AI use leans automation
- Median pay $63,760/yr
- Work is mostly on-site (not teleworkable)
- 2013 flagged this for computerization (56th); today's AI task-overlap is comparatively low (24th)
24th-percentile task overlap — yet about 45,700 openings a year (+16.1% projected, BLS), and observed AI use leans 2281% copilot, not hand-off (AEI) . 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.) Low | 13th | -1.1 | |
| LLM task exposure, γ (OpenAI / Eloundou) Moderate | 35th | 0.4 | |
| AI assistant applicability (Microsoft) Low | 31st | 0.1 |
OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.2), with simple added tooling (β 0.3), and including AI-powered software (γ 0.4). 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 0.7 · 56th percentile among occupations · Moderate
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.
| Enter codes and instructions to program computer-controlled machinery. | 1.7% | |
| Analyze test results, machine error messages, or information obtained from operators to diagnose equipment problems. | 0.4% |
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 · +16.1% by 2034 |
| Projected annual openings | 45,700 |
| Employment 2024 → 2034 | 439,600 → 510,300 |
“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 Machinery Mechanics sits at the 24th percentile of 427
occupations on the global GenAI task-exposure gradient
— exposure eased from 2023 to 2025. Each dot is one occupation; the
ringed one is this work. Exposure is task overlap, not automation or jobs lost.
17% mean task exposure (2025)
24th percentile of 427 placed occupations
−2 pts shift 2023 → 2025
| International occupation (ISCO-08) | Task exposure (2025) | Most tasks fall in |
|---|---|---|
| Agricultural and Industrial Machinery Mechanics and Repairers · 7233 | 17% | Not exposed |
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.
Working with AI in this job
How people actually apply AI to this occupation's tasks, from Claude.ai (Free and Pro) conversations in the Anthropic Economic Index, 2026-01-15. This is one AI assistant's consumer sample — not all AI, not the whole workforce. Autonomy and the collaboration mix are model-rated estimates; figures below the sample floor are hidden.
| Augmentation vs. automation | 22.8% working with AI · 73.7% handed to AI |
| Most common way people use AI here | Directive · AI does it; you give the instruction |
| Typical AI autonomy | 4.0 / 5 · higher = AI acts more independently |
| Used for work (vs. personal / coursework) | 64.2% |
What people delegate to AI
The role's most common tasks in AI conversations, each tagged with how people work with the AI on it. “Usage” is the share of observed conversations, not of the job.
| Task | How | Usage |
|---|---|---|
| Enter codes and instructions to program computer-controlled machinery. | Directive | 4.0% |
Where a human is still needed
Tasks where the model most often judged that a person remained necessary — a useful read on the current boundary, not a guarantee.
| Enter codes and instructions to program computer-controlled machinery. | 68.2% |
What people most often hand AI here
Example prompts phrased from the tasks people most often delegate to AI in this occupation (Anthropic Economic Index). Each shows the underlying measured task and its share of observed AI use. They are suggested phrasings of real tasks — starting points, not endorsed instructions.
-
Help me enter codes and instructions to program computer-controlled machinery.From: Enter codes and instructions to program computer-controlled machinery. · 4.0% of measured AI use · directive
Tasks
All 16 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.
- Repair or maintain the operating condition of industrial production or processing machinery or equipment. Core · importance 4.3
- Repair or replace broken or malfunctioning components of machinery or equipment. Core · importance 4.2
- Clean, lubricate, or adjust parts, equipment, or machinery. Core · importance 4.2
- Disassemble machinery or equipment to remove parts and make repairs. Core · importance 4.1
- Reassemble equipment after completion of inspections, testing, or repairs. Core · importance 4.1
- Examine parts for defects, such as breakage or excessive wear. Core · importance 4.1
- Operate newly repaired machinery or equipment to verify the adequacy of repairs. Core · importance 4.0
- Record repairs and maintenance performed. Core · importance 4.0
- Record parts or materials used and order or requisition new parts or materials, as necessary. Core · importance 4.0
- Observe and test the operation of machinery or equipment to diagnose malfunctions, using voltmeters or other testing devices. Core · importance 3.9
- Analyze test results, machine error messages, or information obtained from operators to diagnose equipment problems. Core · importance 3.8
- Study blueprints or manufacturers' manuals to determine correct installation or operation of machinery. Core · importance 3.8
- Cut and weld metal to repair broken metal parts, fabricate new parts, or assemble new equipment. Core · importance 3.8
- Enter codes and instructions to program computer-controlled machinery. Core · importance 3.7
- Demonstrate equipment functions and features to machine operators. Core · importance 3.7
- Assign schedules to work crews. Supplemental · importance 3.1
Work activities
- Disassemble equipment for maintenance or repair.
- Replace worn, damaged, or defective mechanical parts.
- Repair worn, damaged, or defective mechanical parts.
- Maintain work equipment or machinery.
- Inspect mechanical equipment to locate damage, defects, or wear.
- Reassemble equipment after repair.
- Observe equipment in operation to detect potential problems.
- Test mechanical equipment to ensure proper functioning.
- Clean equipment, parts, or tools to repair or maintain them in good working order.
- Adjust equipment to ensure optimal performance.
- Lubricate equipment to allow proper functioning.
- Analyze test or performance data to assess equipment operation.
- Maintain repair or maintenance records.
- Interpret blueprints, specifications, or diagrams to inform installation, development or operation activities.
- Record information about parts, materials or repair procedures.
- Order materials, supplies, or equipment.
- Cut materials according to specifications or needs.
- Operate welding equipment.
- Train others in operational procedures.
- Enter codes or other information into computers.
- Plan employee work schedules.
- Assign duties or work schedules to employees.
Knowledge, skills & abilities
O*NET importance rating, from 1 (not important) to 5 (extremely important).
Knowledge
| Mechanical | 4.3 | |
| English Language | 3.5 | |
| Production and Processing | 3.4 | |
| Engineering and Technology | 3.3 | |
| Design | 3.3 | |
| Mathematics | 3.1 |
Transferable skills
| Operations Monitoring | 4.0 | |
| Operation and Control | 4.0 | |
| Equipment Maintenance | 4.0 | |
| Troubleshooting | 4.0 | |
| Repairing | 4.0 | |
| Quality Control Analysis | 3.8 | |
| Complex Problem Solving | 3.1 | |
| Equipment Selection | 3.1 | |
| Judgment and Decision Making | 3.1 | |
| Coordination | 3.0 | |
| Time Management | 3.0 |
Abilities
| Problem Sensitivity | 3.9 | |
| Manual Dexterity | 3.9 | |
| Finger Dexterity | 3.9 | |
| Control Precision | 3.9 | |
| Near Vision | 3.9 | |
| Arm-Hand Steadiness | 3.8 | |
| Reaction Time | 3.8 | |
| Multilimb Coordination | 3.6 | |
| Information Ordering | 3.5 | |
| Hearing Sensitivity | 3.5 | |
| Visualization | 3.3 | |
| Selective Attention | 3.3 | |
| Written Comprehension | 3.1 | |
| Deductive Reasoning | 3.1 | |
| Static Strength | 3.1 | |
| Trunk Strength | 3.1 | |
| Extent Flexibility | 3.1 | |
| Auditory Attention | 3.1 |
Essential skills
| Critical Thinking | 3.6 | |
| Active Listening | 3.1 | |
| Active Learning | 3.1 | |
| Monitoring | 3.1 | |
| Speaking | 3.0 |
Skills in demand
Skills employers ask for in job postings for this occupation (Lightcast), with whether each is a common or specialized skill.
Tools & technology
| Example | Category | |
|---|---|---|
| Microsoft Excel | Spreadsheet software | Hot technology |
| Microsoft Office software | Office suite software | Hot technology |
| Microsoft Outlook | Electronic mail software | Hot technology |
| Microsoft PowerPoint | Presentation software | Hot technology |
| Microsoft Word | Word processing software | Hot technology |
| SAP software | Enterprise resource planning ERP software | Hot technology |
| BIT Corp ProMACS PLC | Industrial control software | |
| Extranet Machine Tools Suite | Computer aided manufacturing CAM software | |
| Inventory tracking software | Inventory management software | |
| KEYENCE PLC Ladder Logic | Industrial control software | |
| Maintenance management software | Facilities management software | |
| Maintenance planning and control software | Data base user interface and query software | |
| Programmable logic controller PLC software | Industrial control software | |
| Supervisory control and data acquisition SCADA software | Industrial control software | |
| Web browser software | Internet browser software |
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 3 — Job Zone Three: Medium Preparation Needed
- Education
- Most occupations in this zone require training in vocational schools, related on-the-job experience, or an associate's degree.
- Typical entry-level education
- High school diploma or equivalent · BLS, the typical path — not a requirement
- Related experience
- Previous work-related skill, knowledge, or experience is required for these occupations. For example, an electrician must have completed three or four years of apprenticeship or several years of vocational training, and often must have passed a licensing exam, in order to perform the job.
- Preparation level
- SVP (6.0 to < 7.0) — total schooling plus on-the-job experience.
What to study: Mechanic and Repair 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.
| Post-Secondary Certificate | 47.2% | |
| High School Diploma | 39.1% | |
| Associate's Degree (or other 2-year degree) | 13.7% |
Interests & work styles
The interests and personal qualities O*NET associates with people who do this work.
Career interests (Holland / RIASEC)
| Realistic | 7.0 | |
| Conventional | 4.3 | |
| Investigative | 3.0 |
Interest areas
Work styles
| Dependability | 3.0 | |
| Attention to Detail | 2.6 | |
| Cautiousness | 2.1 | |
| Perseverance | 1.8 | |
| Integrity | 1.5 |
Wages & employment
U.S. · annual wages (BLS OEWS)
| 10th percentile | $45,090 |
| 25th percentile | $52,710 |
| Median (50th) | $63,760 |
| 75th percentile | $78,070 |
| 90th percentile | $92,730 |
| People employed | 421,940 |
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 | 223,700 | $64,680 |
| Wholesale Trade · Sector | 62,970 | $62,340 |
| Other Services (except Public Administration) · Sector | 52,870 | $60,290 |
| Mining, Quarrying, and Oil and Gas Extraction · Sector | 18,570 | $64,230 |
| Transportation and Warehousing · Sector | 10,160 | $76,030 |
| Utilities · Sector | 10,060 | $96,370 |
| Administrative and Support and Waste Management and Remediation Services · Sector | 8,490 | $59,050 |
| Construction · Sector | 7,670 | $59,790 |
| Real Estate and Rental and Leasing · Sector | 6,270 | $49,980 |
| Professional, Scientific, and Technical Services · Sector | 4,260 | $70,220 |
| Temporary Help Services · National industry | 2,990 | $48,880 |
| Machine Shops · National industry | 2,500 | $60,510 |
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 |
|---|---|---|
| Geothermal Electric Power Generation · National industry | 65.45× | 120 |
| Biomass Electric Power Generation · National industry | 25.82× | 130 |
| Hydroelectric Power Generation · National industry | 19.77× | 370 |
| Other Electric Power Generation · National industry | 15.71× | 150 |
| Mining, Quarrying, and Oil and Gas Extraction · Sector | 11.83× | 18,570 |
| Fossil Fuel Electric Power Generation · National industry | 11.58× | 2,260 |
| Nuclear Electric Power Generation · National industry | 11.12× | 1,130 |
| Manufacturing · Sector | 6.4× | 223,700 |
Related occupations
Part of the Advanced Manufacturing and Energy & Natural Resources career clusters.
- Maintenance Workers, Machinery · 49-9043.00 Compare →
- Electric Motor, Power Tool, and Related Repairers · 49-2092.00 Compare →
- Multiple Machine Tool Setters, Operators, and Tenders, Metal and Plastic · 51-4081.00 Compare →
- Mobile Heavy Equipment Mechanics, Except Engines · 49-3042.00 Compare →
- Engine and Other Machine Assemblers · 51-2031.00 Compare →
- Milling and Planing Machine Setters, Operators, and Tenders, Metal and Plastic · 51-4035.00 Compare →
- Grinding, Lapping, Polishing, and Buffing Machine Tool Setters, Operators, and Tenders, Metal and Plastic · 51-4033.00 Compare →
- Control and Valve Installers and Repairers, Except Mechanical Door · 49-9012.00 Compare →
- Millwrights · 49-9044.00 Compare →
- Lathe and Turning Machine Tool Setters, Operators, and Tenders, Metal and Plastic · 51-4034.00 Compare →
- Aircraft Structure, Surfaces, Rigging, and Systems Assemblers · 51-2011.00 Compare →
- Electrical and Electronic Equipment Assemblers · 51-2022.00 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 Machinery Mechanics — 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.
- High school diploma or equivalent · typical entry level
- Job zone 3 — Job Zone Three: Medium Preparation Needed · preparation tier
- Mechanic and Repair Technologies/Technicians · field of study
Zoom out
On the global GenAI exposure gradient this work sits around the 24th percentile of 427 international occupations.
Write a report on thisheadline · factoids · citation
Industrial Machinery Mechanics show 24th-percentile AI task overlap — and about 45,700 annual U.S. openings
- Industrial Machinery Mechanics rank in the 24th percentile (Low 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 45,700 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 (+16.1%) from 2024 to 2034.BLS Employment Projections 2024–34
- Median annual pay is $63,760, across about 421,940 U.S. workers.BLS OEWS (May 2024)
- Of the AI use actually observed for this work, 23% looks like augmentation (drafting, iterating, checking) rather than hands-off automation — from a Claude.ai usage sample, not a census.2026-01-15-v4-plus-2025-03-27-v2
Copy the whole kit
Industrial Machinery Mechanics show 24th-percentile AI task overlap — and about 45,700 annual U.S. openings • Industrial Machinery Mechanics rank in the 24th percentile (Low 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 45,700 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 (+16.1%) from 2024 to 2034. (BLS Employment Projections 2024–34) • Median annual pay is $63,760, across about 421,940 U.S. workers. (BLS OEWS (May 2024)) • Of the AI use actually observed for this work, 23% looks like augmentation (drafting, iterating, checking) rather than hands-off automation — from a Claude.ai usage sample, not a census. (2026-01-15-v4-plus-2025-03-27-v2) Source: Singulariki — "Industrial Machinery Mechanics". https://singulariki.com/roles/role-49-9041-00 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 Machinery Mechanics." 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-49-9041-00
APA
Singulariki. (2026). Industrial Machinery Mechanics. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-49-9041-00
BibTeX
@misc{singulariki-role-49-9041-00,
title = {Industrial Machinery Mechanics},
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-49-9041-00}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.