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First-Line Supervisors of Mechanics, Installers, and Repairers

Occupation · SOC 49-1011.00

Directly supervise and coordinate the activities of mechanics, installers, and repairers. May also advise customers on recommended services. Excludes team or work leaders.

Also called: Maintenance Foreman · Maintenance Manager · Maintenance Supervisor · Service Manager · Electrical and Instrumentation Supervisor (E and I Supervisor) · Facilities Maintenance Supervisor · Facility Maintenance Supervisor · Maintenance Coordinator · Maintenance Planner · Maintenance Superintendent · AC Installer Supervisor (Air-Conditioning Installer Supervisor) · AC Supervisor (Air Conditioning Supervisor)

Job family: Installation, Maintenance, and Repair Occupations

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Download .md

A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch /roles/role-49-1011-00/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.

Often handed to AI

Task areas most often handled directively in observed AI conversations — candidates to delegate with light review.

  • Develop or implement electronic maintenance programs or computer information management systems. · 0.7%
  • Examine objects, systems, or facilities and analyze information to determine needed installations, services, or repairs. · 0.5%
See how AI is used here →

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.

  • Examine objects, systems, or facilities and analyze information to determine needed installations, services, or repairs. · 100.0% need a human
  • Develop or implement electronic maintenance programs or computer information management systems. · 83.8% need a human
See the boundary tasks →

51st-percentile task overlap — yet about 52,400 openings a year (+3.1% projected, BLS), and observed AI use leans 2834% 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.) Moderate 47th -0.0
LLM task exposure, γ (OpenAI / Eloundou) Moderate 64th 0.8
AI assistant applicability (Microsoft) Moderate 42nd 0.1

OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.0), with simple added tooling (β 0.4), and including AI-powered software (γ 0.8). 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 · 0th 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.

Examine objects, systems, or facilities and analyze information to determine needed installations, services, or repairs. 1.0%
Develop or implement electronic maintenance programs or computer information management systems. 0.9%
Counsel employees about work-related issues and assist employees to correct job-skill deficiencies. 0.2%
Compute estimates and actual costs of factors such as materials, labor, or outside contractors. 0.2%

Job outlook

Independent U.S. Bureau of Labor Statistics employment projection for 2024–2034 — a labor-market forecast, not an AI-impact forecast.

Outlook About average · +3.1% by 2034
Projected annual openings 52,400
Employment 2024 → 2034 617,500 → 636,500

“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 11 occupations below. Exposure here means how much of the work's tasks today's AI can attempt — task overlap, not automation, adoption, or jobs lost.

19% mean task exposure (2025)
30th percentile of 427 placed occupations
+3 pts shift 2023 → 2025
International occupation (ISCO-08) Task exposure (2025) Most tasks fall in
Electronics Mechanics and Servicers · 7421 25% Not exposed
Information and Communications Technology Installers and Servicers · 7422 24% Not exposed
Precision-instrument Makers and Repairers · 7311 21% Not exposed
Air Conditioning and Refrigeration Mechanics · 7127 21% Not exposed
Aircraft Engine Mechanics and Repairers · 7232 19% Not exposed
Motor Vehicle Mechanics and Repairers · 7231 18% Not exposed
Electrical Mechanics and Fitters · 7412 17% Not exposed
Agricultural and Industrial Machinery Mechanics and Repairers · 7233 17% Not exposed
Electrical Line Installers and Repairers · 7413 15% Not exposed
Musical Instrument Makers and Tuners · 7312 14% Not exposed
Bicycle and Related Repairers · 7234 13% 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 28.3% working with AI · 35.0% handed to AI
Most common way people use AI here Directive · AI does it; you give the instruction
Typical AI autonomy 3.5 / 5 · higher = AI acts more independently
Used for work (vs. personal / coursework) 78.3%

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
Develop or implement electronic maintenance programs or computer information management systems. Directive 0.7%
Examine objects, systems, or facilities and analyze information to determine needed installations, services, or repairs. Directive 0.5%

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.

Examine objects, systems, or facilities and analyze information to determine needed installations, services, or repairs. 100.0%
Develop or implement electronic maintenance programs or computer information management systems. 83.8%

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 develop or implement electronic maintenance programs or computer information management systems.

    From: Develop or implement electronic maintenance programs or computer information management systems. · 0.7% of measured AI use · directive

  • Help me examine objects, systems, or facilities and analyze information to determine needed installations, services, or repairs.

    From: Examine objects, systems, or facilities and analyze information to determine needed installations, services, or repairs. · 0.5% of measured AI use · directive

Tasks

All 22 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.

Work activities

Knowledge, skills & abilities

O*NET importance rating, from 1 (not important) to 5 (extremely important).

Essential skills

Monitoring 4.0
Speaking 3.8
Critical Thinking 3.8
Reading Comprehension 3.6
Active Listening 3.6
Active Learning 3.3
Learning Strategies 3.1

Abilities

Oral Comprehension 4.0
Written Comprehension 4.0
Oral Expression 4.0
Deductive Reasoning 3.9
Inductive Reasoning 3.9
Near Vision 3.9
Problem Sensitivity 3.8
Information Ordering 3.8
Speech Recognition 3.8
Speech Clarity 3.8
Flexibility of Closure 3.3
Selective Attention 3.3
Far Vision 3.3
Written Expression 3.1
Category Flexibility 3.1
Perceptual Speed 3.1

Knowledge

Administration and Management 4.0
Mechanical 3.8
Customer and Personal Service 3.7
Administrative 3.3
Personnel and Human Resources 3.2
English Language 3.2

Transferable skills

Management of Personnel Resources 3.9
Coordination 3.8
Judgment and Decision Making 3.8
Time Management 3.8
Quality Control Analysis 3.6
Operations Monitoring 3.4
Systems Analysis 3.3
Social Perceptiveness 3.1
Complex Problem Solving 3.1
Troubleshooting 3.1
Systems Evaluation 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 48.

Tools & technology

Example Category
Microsoft Excel Spreadsheet software Hot technology In demand
Microsoft Office software Office suite software Hot technology In demand
Microsoft Outlook Electronic mail software Hot technology In demand
Autodesk AutoCAD Computer aided design CAD software Hot technology
Microsoft Access Data base user interface and query software Hot technology
Microsoft PowerPoint Presentation software Hot technology
Microsoft Project Project management software Hot technology
Microsoft SharePoint Document management software Hot technology
Microsoft Windows Operating system software Hot technology
Microsoft Word Word processing software Hot technology
Oracle Primavera Enterprise Project Portfolio Management Project management software Hot technology
SAP software Enterprise resource planning ERP software Hot technology
Yardi software Data base user interface and query software Hot technology
Automated inventory software Inventory management software
ComputerEase construction accounting software Project management software
Computerized maintenance management system CMMS Facilities management software
Cost accounting software Accounting software
Database software Data base user interface and query software
Email software Electronic mail software
HCSS HeavyBid Project management software
HCSS HeavyJob Project management software
IBM Domino Communications server software
IBM Notes Electronic mail software
Infor ERP SyteLine Enterprise resource planning ERP software
Maintenance management software Facilities management software
Microsoft Dynamics Enterprise resource planning ERP software
Microsoft Internet Explorer Internet browser software
Oracle JD Edwards EnterpriseOne Enterprise resource planning ERP software
Payroll software Time accounting software
Programmable logic controller PLC software Industrial control software
Recordkeeping software Data base user interface and query software
Scheduling software Calendar and scheduling software
Supervisory control and data acquisition SCADA software Industrial control software
Vehicle management software Data base user interface and query software
WorkTech MAXIMO Enterprise resource planning ERP 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.

Telephone Conversations 4.8
Contact With Others 4.8
Face-to-Face Discussions with Individuals and Within Teams 4.5
Determine Tasks, Priorities and Goals 4.5
Importance of Being Exact or Accurate 4.4
E-Mail 4.4
Work Outcomes and Results of Other Workers 4.4
Freedom to Make Decisions 4.4
Work With or Contribute to a Work Group or Team 4.3
Health and Safety of Other Workers 4.3
Coordinate or Lead Others in Accomplishing Work Activities 4.2
Frequency of Decision Making 4.1
Impact of Decisions on Co-workers or Company Results 4.0
Exposed to Sounds, Noise Levels that are Distracting or Uncomfortable 4.0
Wear Common Protective or Safety Equipment such as Safety Shoes, Glasses, Gloves, Hearing Protection, Hard Hats, or Life Jackets 4.0
Time Pressure 3.9
Importance of Repeating Same Tasks 3.9
Exposed to Contaminants 3.8
Spend Time Using Your Hands to Handle, Control, or Feel Objects, Tools, or Controls 3.8
Exposed to Hazardous Equipment 3.5
Exposed to Very Hot or Cold Temperatures 3.4
Deal With External Customers or the Public in General 3.4
Indoors, Not Environmentally Controlled 3.4
Physical Proximity 3.4
Indoors, Environmentally Controlled 3.4
Outdoors, Exposed to All Weather Conditions 3.3
Spend Time Bending or Twisting Your Body 3.1
Spend Time Sitting 3.1
In an Enclosed Vehicle or Operate Enclosed Equipment 3.0
Spend Time Standing 3.0
Spend Time Making Repetitive Motions 2.9
Level of Competition 2.9
Written Letters and Memos 2.9
Spend Time Walking or Running 2.9
Conflict Situations 2.9
Exposed to Hazardous Conditions 2.7
Dealing With Unpleasant, Angry, or Discourteous People 2.7
Exposed to Minor Burns, Cuts, Bites, or Stings 2.7
Consequence of Error 2.5
Exposed to High Places 2.4

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: Business, Management, Marketing, and Related Support Services , Construction Trades , 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.

High School Diploma 54.1%
Some College Courses 16.9%
Post-Secondary Certificate 13.1%
Bachelor's Degree 7.6%
Associate's Degree (or other 2-year degree) 3.2%
Less than a High School Diploma 3.0%
Doctoral Degree 2.0%

Interests & work styles

The interests and personal qualities O*NET associates with people who do this work.

Career interests (Holland / RIASEC)

Enterprising 6.0
Conventional 4.8
Realistic 4.1
Social 3.6

Interest areas

Management/Administration 5.6
Mechanics/Electronics 5.1
Human Resources 3.8
Engineering 3.6
Physical/Manual Labor 2.6
Teaching/Education 2.3
Construction/Woodwork 2.3
Transportation/Machine Operation 2.2

Work styles

Dependability 5.0
Attention to Detail 4.0
Cautiousness 3.0
Leadership Orientation 2.6

Wages & employment

U.S. · annual wages (BLS OEWS)

$48k10th$61k25th$78kMedian$100k75th$124k90th
Annual wages by percentile — U.S. (BLS OEWS). The light band spans the 10th–90th percentile; the darker band is the middle half (25th–75th); the line is the median.
618k2024637k2034 (proj.)+3.1% · About average
Projected U.S. employment, 2024–2034 (BLS Employment Projections). A labor-market forecast for the occupation, not an AI-impact forecast.
10th percentile $48,460
25th percentile $61,240
Median (50th) $78,300
75th percentile $99,630
90th percentile $124,280
People employed 600,680

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
Retail Trade · Sector 72,420 $64,480
Construction · Sector 64,640 $80,270
Other Services (except Public Administration) · Sector 63,560 $68,770
Manufacturing · Sector 63,050 $92,510
Real Estate and Rental and Leasing · Sector 58,270 $65,080
Wholesale Trade · Sector 41,680 $80,830
Transportation and Warehousing · Sector 39,960 $92,210
Plumbing, Heating, and Air-Conditioning Contractors · National industry 27,660 $79,260
Utilities · Sector 24,670 $122,610
Administrative and Support and Waste Management and Remediation Services · Sector 22,600 $72,920
Health Care and Social Assistance · Sector 18,110 $69,290
Educational Services · Sector 17,180 $74,470

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
Power and Communication Line and Related Structures Construction · National industry 14.65× 13,360
Wind Electric Power Generation · National industry 11.12× 430
Utilities · Sector 10.93× 24,670
Fossil Fuel Electric Power Generation · National industry 10.84× 3,010
Hydroelectric Power Generation · National industry 10.13× 270
Farm and Garden Machinery and Equipment Merchant Wholesalers · National industry 8.57× 3,810
Nuclear Electric Power Generation · National industry 7.05× 1,020
Real Estate and Rental and Leasing · Sector 6.32× 58,270

Part of the Advanced Manufacturing , Construction , Energy & Natural Resources and Supply Chain & Transportation career clusters.

Exposure quadrant: AI task-overlap percentile vs Median pay First-Line Supervisors of Mechanics, Installers, and Repairers sits at the 51st percentile of AI task-overlap and the 67th percentile of median pay, placed here against 9 adjacent occupations on the same two axes. Lower overlap · higher pay Higher overlap · higher pay Higher overlap · lower pay Lower overlap · lower pay First-Line Supervisors of Mechanics, Installers, and Repairers First-Line Supervisors of Farming, Fishing, and Forestry Workers First-Line Supervisors of Landscaping, Lawn Service, and Groundskeeping Workers First-Line Supervisors of Housekeeping and Janitorial Workers First-Line Supervisors of Production and Operating Workers General and Operations Managers First-Line Supervisors of Non-Retail Sales Workers First-Line Supervisors of Office and Administrative Support Workers AI task-overlap percentile → ↑ Median pay
AI task-overlap percentile (horizontal) vs. median-pay percentile (vertical), across all scored occupations. This occupation is highlighted; related occupations are plotted alongside it. Overlap measures shared tasks with AI, not automation.

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 First-Line Supervisors of Mechanics, Installers, and Repairers — not advice or a forecast. Each is a real cross-link you can follow into the evidence.

Write a report on thisheadline · factoids · citation

First-Line Supervisors of Mechanics, Installers, and Repairers show 51st-percentile AI task overlap — and about 52,400 annual U.S. openings

  • First-Line Supervisors of Mechanics, Installers, and Repairers rank in the 51st percentile (Moderate 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 52,400 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 about average (+3.1%) from 2024 to 2034.BLS Employment Projections 2024–34
  • Median annual pay is $78,300, across about 600,680 U.S. workers.BLS OEWS (May 2024)
  • Of the AI use actually observed for this work, 28% 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
First-Line Supervisors of Mechanics, Installers, and Repairers show 51st-percentile AI task overlap — and about 52,400 annual U.S. openings

• First-Line Supervisors of Mechanics, Installers, and Repairers rank in the 51st percentile (Moderate 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 52,400 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 about average (+3.1%) from 2024 to 2034. (BLS Employment Projections 2024–34)
• Median annual pay is $78,300, across about 600,680 U.S. workers. (BLS OEWS (May 2024))
• Of the AI use actually observed for this work, 28% 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 — "First-Line Supervisors of Mechanics, Installers, and Repairers". https://singulariki.com/roles/role-49-1011-00
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.

Data compiled June 2, 2026. Figures are estimates, not advice.

Cite this page
Plain

Singulariki. "First-Line Supervisors of Mechanics, Installers, and Repairers." 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-49-1011-00

APA

Singulariki. (2026). First-Line Supervisors of Mechanics, Installers, and Repairers. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-49-1011-00

BibTeX
@misc{singulariki-role-49-1011-00,
  title  = {First-Line Supervisors of Mechanics, Installers, and Repairers},
  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-49-1011-00}
}

Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.

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