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Time Machine

Maintenance and Repair Workers, General

Scrub through 166years of this role's history, from when it first emerged, through every wave of technology that reshaped it, to the cited projections for where it's heading next.

2026drag to travel through time
187519001925195019752000now
Country
2026
Known today as Maintenance and Repair Workers, General (BLS SOC 49-9071)
US Employment
1.53M
OEWS is a point-in-time survey snapshot, not a continuous time series; BLS advises against using it for year-over-year trend comparison.
Median Annual Wage
$49,590
≈ $48,319 in 2024 dollars
Each dot is a cited figure over time; the dotted line only links them (values between aren't measured). Hollow dots are estimates.
Tools of the era

The tools that defined the work

Select an era to see how it reshaped the work.

  • Hand tools + gas lighting era

    The first building maintenance workers used the same hand tools as the trades they drew from: pipe wrenches, hammers, chisels, hand saws, and caulking irons. Lighting came from gas jets — and when they malfunctioned, the maintenance worker dealt with open flame in confined spaces. Boiler rooms ran on coal. Elevator machinery was hydraulic. Every repair was physical, every diagnosis was sensory — listening for a loose joint, feeling pipe temperature with bare hands, smelling a gas leak before it reached dangerous concentration. The craftsperson was the instrument.

    Work toolChanging equipment
  • Portable electric drill (Black & Decker, 1916)

    Black & Decker invented the world's first portable electric drill in 1916 — incorporating a pistol grip and trigger switch that allowed one-handed operation. Before this, drilling in the field meant a brace-and-bit or a trip back to a stationary machine. The portable drill brought power to the work site rather than moving work to the machine. Building maintenance workers were among the first commercial users: boring mounting holes for fixtures, drilling through structural members to run new pipe or conduit, cutting openings in walls.

    Effect on the work

    The portable drill increased drilling productivity by roughly 10x versus hand brace for repetitive tasks; Black & Decker surpassed $1M in annual sales by 1920 and opened offices in eight US cities.

    Work toolChanging equipment
  • Portable multimeter (AVO meter, 1923) + standardized power tools

    Donald Macadie, a British Post Office engineer, invented the first multimeter in 1920, frustrated by carrying separate ammeters, voltmeters, and ohmmeters on telecom line work. The first commercial AVO (Amps-Volts-Ohms) meter went on sale in 1923. For building maintenance workers, this meant a single instrument for diagnosing electrical faults — measuring circuit continuity, checking voltage at outlets, testing motor windings. Black & Decker began marketing its electric drill to non-professionals in 1923, launching the consumer power-tools market. Together, the multimeter and portable power drill defined the maintenance technician's basic toolkit for the next 40 years.

    Work toolChanging equipment
  • Cordless tools (Black & Decker cordless drill, 1961) + fluorescent lighting era

    In 1961, Black & Decker introduced the first cordless electric drill, developed in partnership with NASA for use in zero-gravity spacecraft assembly. The consumer cordless drill followed by the mid-1960s. For maintenance workers, cordless tools meant climbing ladders and scaffolding without trailing extension cords — a meaningful safety and productivity improvement. The widespread shift to fluorescent lighting in commercial buildings (beginning in the late 1930s but dominant by the 1960s) also transformed maintenance requirements: ballasts, starters, and fluorescent tubes replaced incandescent bulbs, adding an electrical-maintenance dimension to what had been a simple lamp-changing task.

    Work toolChanging equipment
  • OSHA compliance era — safety documentation and lockout/tagout

    On December 29, 1970, President Nixon signed the Occupational Safety and Health Act, creating OSHA and giving the federal government authority to set and enforce workplace safety standards. For maintenance workers, OSHA's most consequential early standards were: electrical safety (requiring lockout/tagout procedures before working on energized equipment), confined-space entry (requiring permits, atmospheric testing, and a standby attendant for work in boiler rooms, crawl spaces, and mechanical pits), and fall protection. Prior to OSHA, an estimated 38 US workers died each day on the job. The compliance burden was significant — adding documentation, training, and equipment requirements — but it also raised the professional standing of maintenance work by making clear what the job's actual hazards were.

    Compliance systemsControls and audit files
  • CMMS — computerized maintenance management systems (Maximo, 1985)

    The first commercial Computerized Maintenance Management System was Maximo, released in May 1985 by Project Software & Development (PSDI) as a turnkey file-based system on an IBM PC. Maximo introduced the concept of the work order as a digital object: a maintenance task with an asset ID, scheduled date, labor hours, parts consumed, and completion notes — all tracked in a database rather than on paper. For maintenance workers, CMMS changed the job in two ways: they now had a formal record of everything they had touched, and preventive maintenance schedules could be tracked systematically rather than relying on the worker's memory or a paper calendar. The software-side of maintenance work was born.

    Effect on the work

    CMMS adoption in the late 1980s and 1990s reduced unplanned downtime in industrial settings by an estimated 10-20% by shifting reactive to preventive maintenance.

    Work toolChanging equipment
  • BACnet building automation standard (1995) + digital HVAC controls

    BACnet (Building Automation and Control Network) was issued as ANSI/ASHRAE Standard 135 in 1995, after eight years of development by a committee that had convened in Nashville in 1987 to solve a specific problem: over 400 proprietary protocols in the building automation field that prevented equipment from different manufacturers from communicating. BACnet created a common language for HVAC controls, lighting systems, fire detection, and access control. For maintenance workers, this transformed HVAC troubleshooting from analog gauge-reading to digital fault-code diagnosis — the same shift that happened to auto mechanics in the 1990s with OBD-II. A worker who had learned to diagnose a pneumatic thermostat now had to read a control-panel touchscreen and interpret fault codes from a building management system.

    Work toolChanging equipment
  • Predictive maintenance AI (Augury, 2011) + IoT sensor networks

    Augury was founded in 2011 by Saar Yoskovitz and Gal Shaul, after Shaul identified a failing machine at a medical device company by its sound alone — a fan that simply needed cleaning. Augury's technology digitizes that intuitive diagnostic: vibration and ultrasound sensors mounted on motors, compressors, and pumps feed data to cloud AI that models each machine's "health signature" and predicts failures days or weeks ahead. IBM Maximo, acquired by IBM in 2006, added AI-driven failure prediction on top of its CMMS work-order backbone. For maintenance workers, the practical effect is a shift in how they spend time: less reactive emergency response, more scheduled intervention triggered by sensor alerts. The work itself — the physical act of replacing a bearing or resealing a pump — does not change.

    Effect on the work

    Augury reported an internal target of making every plant persona 30% more productive — the augmentation model, not displacement. A 2019 Nanalyze survey of predictive maintenance deployments found 10-25% reductions in unplanned downtime, with maintenance headcounts largely stable.

    Work toolChanging equipment
  • AI-augmented diagnostics + smart building platforms

    The 2020s brought the integration layer: building management systems, IoT sensors, mobile work-order apps, and AI diagnostics unified into platforms that a technician operates from a tablet. Microsoft Smart Buildings, Siemens Desigo, and Johnson Controls Metasys combined BACnet-era sensor networks with cloud dashboards and, after 2023, LLM-powered troubleshooting assistants. A maintenance worker checking a fault code on a rooftop HVAC unit can now query an AI system for likely causes and recommended steps. What the AI cannot do: go up to the roof, remove the panel, identify whether the refrigerant lines are fouled or the compressor is mechanically failing, and execute the repair. The physical diagnostic under constraint — hands in the machine — remains the irreducible human contribution.

    Effect on the work

    BLS projects +3.8% employment growth 2024-2034 despite widespread AI tool adoption. The augmentation thesis holds empirically: smart-building AI has increased per-technician scope without reducing technician headcount in major commercial portfolios.

    Work toolChanging equipment
Projection cone · present → 2034

What credible sources project

Scrub the slider past now to anchor each scenario on the scrubber. The spread is the range of futures credible sources project for this role.

Employment outlook
Projected change in the number of people doing this work.
Skilled trades shortage counter-scenario (Facilities Dive, 2026)
2034
+8%
Industry counter-narrative: the facilities management industry consistently projects a shortage of skilled maintenance technicians driven by (a) retirement of the Baby Boomer generation of maintenance workers, (b) declining vocational enrollment in trade schools, and (c) growing complexity of modern building systems (BACnet, smart building IoT, EV charging infrastructure) requiring higher-skill workers. If the shortage projection materializes, net employment could grow 6-10% even without underlying demand growth, as replacement need exceeds supply from new entrants.
BLS Occupational Outlook 2024-34
2034
+4%
BLS Employment Projections — industry-occupation matrix + labor productivity assumptions. The 2024-34 cycle projects 49-9071 at +3.8% employment growth (published as "about as fast as average"). Baseline: 1,629,700 (2024); projected: 1,692,100 (2034). ~159,800 annual openings projected over the decade, driven largely by replacement need (retirements + occupational transfers) rather than net new positions. BLS projections do not model speculative automation scenarios; they model productivity-adjusted demand given current technology trajectories.
BLS Occupational Outlook Handbook 2024-34 (openings)
2034
+4%
BLS OOH supplementary projection: ~159,800 average annual openings per year 2024-2034. The occupation is designated "Bright Outlook" by O*NET, indicating expected faster-than-average growth or large numbers of openings. The high annual-openings figure relative to net employment growth reflects the age structure of the current workforce: a significant share of incumbents are near retirement age, creating large replacement demand even if the occupation grows only modestly.
AI task exposure
Share of the role’s tasks that researchers estimate AI can do. This is a measure of task exposure, not a forecast of jobs lost.
Frey & Osborne (2013)
2033
22%
of tasks
Gaussian-process classifier on O*NET task features across 702 occupations. F&O assigned General Maintenance and Repair Workers a probability of computerization of approximately 0.22 — significantly lower than the all-occupation mean of 0.47. This places the occupation in the lower-risk tertile of the F&O distribution. The reason cited in the F&O methodology: the role scores high on "manual dexterity" and "work in cramped or awkward positions" — bottleneck task categories that make computer substitution difficult. The -22% figure here represents the implied employment effect if the F&O probability were fully realized, which F&O did not claim. Treat as a ceiling on the pessimistic tail, and note that F&O's lower-risk prediction has been empirically validated: employment has grown, not shrunk, since 2013.
Eloundou et al. — "GPTs are GPTs" (2023)
2028
2%
of tasks
GPT-4 task-by-task LLM exposure labeling on O*NET tasks. Maintenance and Repair Workers score very low on LLM exposure because the core tasks — physically diagnosing and repairing mechanical and structural systems — are not text-based tasks an LLM can perform. The -2% estimate represents the conservative lower-bound on near-term displacement from AI-augmented software tools (work-order management, diagnostic apps, CMMS optimization) rather than from robotics. This is the "AI tells you what to fix; you still fix it" regime.
Today, in this role

What's shifting in the work right now

The historical view above shows how this role has moved. This is the present-day detail: which AI tools are picking up which tasks, where the edge still is, and the natural directions this work can grow.

What's changing in your day

Three parts of your work where AI is already doing real lifting, and what stays yours.

AI is sitting alongside you hereCreate, accept, update, and close CMMS work orders via mobile app — capturing asset ID, fault description, parts used, labor time, and any follow-up actions required

Create, accept, update, and close CMMS work orders via mobile app — capturing asset ID, fault description, parts used, labor time, and any follow-up actions required; attaching photos of the fault condition and completed repair; and adding notes that will help the next technician or the AI scheduling engine understand the repair history for that asset.[10],[4]

Where your edge is

CMMS documentation quality is what separates a maintenance operation that has institutional memory from one that rediscovers the same failures every cycle. The technician who writes precise fault descriptions and photos assets becomes the invisible author of the building's repair history — a dataset that feeds AI scheduling, parts inventory, and eventually vendor performance reviews. In a competitive maintenance job market, demonstrable CMMS proficiency (UpKeep, MaintainX, IBM Maximo) is the most frequently cited differentiator in job postings per BOMA 2025.

AI is sitting alongside you hereSource and procure repair parts — identifying the correct part number from OEM documentation or equipment nameplates, comparing pricing and lead times across suppliers (Grainger, Fastenal, local HVAC supply houses), managing the maintenance storeroom inventory, and flagging AI-generated low-stock alerts in the CMMS inventory module to prevent stockouts on high-frequency consumables (belts, filters, light bulbs, ballasts).

Source and procure repair parts — identifying the correct part number from OEM documentation or equipment nameplates, comparing pricing and lead times across suppliers (Grainger, Fastenal, local HVAC supply houses), managing the maintenance storeroom inventory, and flagging AI-generated low-stock alerts in the CMMS inventory module to prevent stockouts on high-frequency consumables (belts, filters, light bulbs, ballasts).[11],[1]

Tools picking this up
Where your edge is

AI inventory modules (Fiix, UpKeep) now auto-generate purchase orders when stock drops below reorder point — but the technician who maintains accurate part numbers, tracks substitutes for discontinued components, and builds supplier relationships that get a critical part delivered same-day is performing work the software cannot. Learn your equipment's OEM part-number documentation systems (Carrier, Trane, York, Weil-McLain) and maintain a parallel mental model of which local supply houses stock which parts for emergency situations.

AI is sitting alongside you hereEstimate repair costs for damage assessments, capital planning, and insurance claims — walking a property with a property manager or insurance adjuster, identifying scope of damage from water intrusion, storm damage, or equipment failure, and producing a written estimate that reflects current labor and materials costs in the local market.

Estimate repair costs for damage assessments, capital planning, and insurance claims — walking a property with a property manager or insurance adjuster, identifying scope of damage from water intrusion, storm damage, or equipment failure, and producing a written estimate that reflects current labor and materials costs in the local market.[1],[4]

Tools picking this up
Where your edge is

Cost estimation is increasingly AI-assisted — CMMS platforms pull historical parts costs and labor times for similar repairs — but the technician's local market knowledge (which contractors are available, what current trade labor costs, which materials are backordered) is what makes the estimate credible. Building the ability to produce a written repair scope rapidly and defend it in a conversation with a property owner is one of the most transferable skills for a transition toward property management or construction management.

Where this role is heading

Natural next steps for someone with your foundation: not exits, evolutions.

A direction you could grow

Property, Real Estate, and Community Association Managers

Experienced maintenance technicians are among the most credible candidates for property management roles because they understand what tenants actually experience, what repairs cost, and how building systems interact in ways that no classroom training replicates. Property managers who came up through maintenance command genuine respect from maintenance staff, vendors, and contractors — they cannot be easily misled about scope or cost. The technical-to-management pivot typically occurs after 5-10 years in maintenance and requires adding leasing fundamentals, resident relations skills, and property management software proficiency (Yardi, Buildium, AppFolio). Median property manager wage is $62,850 (BLS 2023) with significant upside for portfolio management roles. The -12 CRI delta reflects that property management has more administrative exposure to AI than physical maintenance — but the career ceiling and total compensation are substantially higher.

What you'd add
· Property management software: Yardi Voyager, Buildium, or AppFolio — tenant portal management, work-order routing, lease tracking, and financial reporting
· Fair Housing Act compliance: protected classes, reasonable accommodation procedures, advertising standards — required knowledge for residential property management and tested on licensing exams
· Leasing fundamentals: tenant screening criteria, lease document review, move-in/move-out condition documentation, security deposit accounting
· Property management licensing: most US states require a real estate license or property management license; prep courses available through state-approved real estate schools
· CAM (Certified Apartment Manager) or CPM (Certified Property Manager) designation — NAA and IREM credentials that signal professional commitment to property management career track
What it takesSome new skills to pick up
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The data behind this timeline

On record since1870
Latest tracked employment1,529,700 (US, 2025)
Latest median pay$49,590 (2025)
Outlook+4% by 2034 (BLS Occupational Outlook 2024-34)
View all 21 cited data points
YearUS employmentMedian annual paySource
1900300,000n/aESTIMATE
1921400,000n/aESTIMATE
1950700,000n/aESTIMATE
19801,100,000$14,500ESTIMATE
20001,300,000$27,700BLS-OEWS
20101,217,820$34,730BLS-OEWS
20111,225,450$35,030BLS-OEWS
20121,230,270$35,210BLS-OEWS
20131,249,080$35,640BLS-OEWS
20141,282,920$36,170BLS-OEWS
20151,314,560$36,630BLS-OEWS
20161,332,480$36,940BLS-OEWS
20171,351,210$37,670BLS-OEWS
20181,384,240$38,300BLS-OEWS
20191,418,990$39,080BLS-OEWS
20201,357,630$40,850BLS-OEWS
20211,416,740$43,180BLS-OEWS
20221,607,200$46,960BLS-OEWS
20231,503,150$46,700BLS-OEWS
20241,629,700$48,620BLS-OEWS
20251,529,700$49,590BLS-OEWS
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