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Time Machine

Parking Attendants

Scrub through 131years 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
1925195019752000now
2026
Known today as Parking Attendants (BLS SOC 53-6021)
Latest actual · 2024
135K
OEWS is a point-in-time survey snapshot, not a continuous time series; BLS advises against using it for year-over-year trend comparison.
Latest actual · 2024
$34,600
Source: BLS-OEWS
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.

  • Car lifts, turntables, and spiral ramps (valet-parked garage)

    The earliest tools of the trade were mechanical aids that let one attendant store many cars in a tight footprint: the elevator and turntable of the 1905 Rue de Ponthieu garage in Paris, the lifts and spiraling ramps of American hotel garages like Chicago's Hotel La Salle (1918). These did not replace the attendant; they extended his reach. The whole point of the system was that the driver never touched the storage process. The attendant received the car, drove or platformed it into a slot no customer could navigate, and retrieved it on demand. The job was defined by skilled, fast, repetitive vehicle handling in cramped space, and by the trust required to hand a stranger your car.

    Work toolChanging equipment
  • Parking meter (Park-O-Meter, Oklahoma City, July 16, 1935)

    Carl C. Magee's Park-O-Meter No. 1 went up on a downtown Oklahoma City corner on July 16, 1935, with 175 meters tested across fourteen blocks. The meter did not touch the garage attendant directly, but it reshaped the broader work of managing parked cars: it mechanized curbside time-enforcement, a task previously done by traffic police chalking tires, and it established the principle that parking was a metered, paid, automatically-policed resource. By the early 1940s more than 140,000 meters were installed across the United States. The meter is the first machine in this occupation's history to substitute for a human in the parking-management loop, and it set the template for every automated pay device that followed.

    Effect on the work

    The meter automated curbside enforcement rather than garage attending, so its direct headcount effect on 53-6021 was small, but it normalized paid, machine-enforced parking and seeded the automation of fee collection that later removed booth cashiers.

    Work toolChanging equipment
  • Self-park ramp garage (driver parks own car)

    The single largest change to the occupation came not from a device but from a building design: the self-park ramp garage, which spread widely in the 1940s and 1950s. Architects laid out continuous sloped floors a driver could navigate alone, and the premise of the whole trade, that the attendant parks the car, quietly fell away. Self-parking did not eliminate the attendant overnight; garages still needed people to collect fees, work the entry booth, direct drivers to open floors, and patrol for valid tickets. But it converted the core of the job from skilled vehicle-jockeying into booth-and-flow work, a shift that made the later automation of the booth itself far easier.

    Effect on the work

    Self-park layouts removed the per-car jockeying labor that had justified large attendant crews per garage, lowering the labor intensity of parking storage and reframing the role around fee collection and traffic direction.

    Work toolChanging equipment
  • Automated ticket dispenser + gate arm + pay station

    Through the 1970s the entry booth itself began to mechanize: a ticket spitter dispensed a timestamped stub when a car broke a sensor loop, a gate arm rose automatically, and on exit a cashier (or, increasingly, a pay-on-foot machine) computed the charge. A 1977 New York Times article captured the moment, declaring that "Self-park Garages Sound Death Knell of Car-Jockey" and profiling an attendant who drove a nine-story Detroit garage's ramps hundreds of times a shift, work the new layouts and gates were rendering optional. The attendant did not disappear, but the role narrowed to staffing an exit booth, handling exceptions, and managing the machines. Pay-on-foot and automated pay-on-exit stations through the 1990s and 2000s removed even the cashier from many facilities.

    Effect on the work

    Automated dispensers and gates let a single attendant, or none, oversee facilities that once needed a booth crew; pay-on-foot machines removed the cashier function from many garages, concentrating remaining staff at premium and high-exception sites.

    Work toolChanging equipment
  • Computer-vision license-plate recognition + checkout-free parking (Metropolis, SKIDATA AI)

    Metropolis Technologies, founded in 2017 by Alex Israel, built a parking platform around computer-vision license-plate recognition: cameras read a plate on entry and exit, the system bills the driver's account automatically, and no booth attendant, ticket, or payment interaction is required. The company scaled aggressively, acquiring SP Plus Corporation in 2024 to become one of the largest parking operators in North America and raising a $1.6 billion round in late 2025 for further expansion. Parallel systems from incumbents like SKIDATA add AI vehicle identification by plate, make, model, and color, camera-based occupancy counting without ground sensors, and automated billing at exit, plus early Automated Valet Parking that stores and retrieves cars with no driver and no attendant. This is the era that removes the last human from routine lots: the tasks that survived self-park and automated gates, namely sitting in a booth to take payment, are precisely what the camera-and-account model eliminates.

    Effect on the work

    License-plate recognition and account-based billing let operators run routine lots and garages with zero booth attendants across thousands of locations, hollowing out the entry/exit and payment tasks that had remained human; BLS projects a 12% occupational decline 2024-34, and one automation-risk index scores the role at 62%.

    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.
BLS National Employment Matrix 2024-34
2034
-12%
BLS Employment Projections: industry-occupation matrix plus labor-productivity assumptions. The 2024-34 cycle projects a 12% decline for parking attendants (53-6021), among the steeper occupational declines in the projection set and well below the all-occupations average. The model reflects the spread of automated and cashierless parking technology (license-plate recognition, app-based payment, pay-on-exit machines) that removes the booth and payment functions, partially offset by continued demand for valet service in hospitality and for staffing at high-traffic venues. The projection does not separately model the pace of Metropolis-style platform rollout, which could deepen the decline if adoption accelerates.
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.
AI Changing Work automation-risk index (2026)
2034
62%
of tasks
Composite automation-risk score for parking attendants, reported as 62% exposed, citing the BLS -12% projection alongside the rapid deployment of computer-vision parking platforms. This is a task-exposure estimate, not a headcount forecast: it expresses how much of the role's routine task content (ticketing, payment, occupancy counting, entry/exit control) is technically automatable with current systems, which is high, while leaving the physically present tasks (premium valet, event management, emergency response) outside the exposed share. Rendered as a neutral exposure strip, not as projected jobs lost.
Eloundou et al., "GPTs are GPTs" (2023)
2030
10%
of tasks
GPT-4 task-by-task LLM-exposure labeling on O*NET tasks. Parking attendants score low for language-model exposure specifically, because the dominant tasks (driving and parking vehicles, greeting guests, directing traffic, patrolling, physical motorist assistance) require physical presence that large language models cannot supply. This is the key contrast with the other projections: the real displacement vector for this role is computer vision and IoT sensors, not text AI. Eloundou measures only the LLM channel, so its low exposure number is correct and also incomplete; it is included to show that the threat here is non-LLM automation, which Eloundou by design does not capture.
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 taking this onIssue physical or digital claim tickets, scan license plates, and log vehicles into a parking management platform so customers can retrieve their car without searching.

Issue physical or digital claim tickets, scan license plates, and log vehicles into a parking management platform so customers can retrieve their car without searching.[6],[7]

Where your edge is

Focus on customer-facing exception handling when the system produces an error (duplicate plate, unreadable tag). Platform operators who can troubleshoot camera or sensor failures are valued by multi-facility managers.

AI is taking this onCollect parking fees, process credit/debit payments, make change, and balance a shift cash drawer or reconcile a digital payment summary at the end of a shift.

Collect parking fees, process credit/debit payments, make change, and balance a shift cash drawer or reconcile a digital payment summary at the end of a shift.[8],[1]

Where your edge is

In facilities that retain a cashier booth, accuracy and fraud prevention (counterfeit detection, till reconciliation) remain human responsibilities. Pursue cross-training on the facility's POS and parking management dashboards so you can audit automated transaction logs.

AI is sitting alongside you hereMonitor parking facility occupancy in real time using a management dashboard, adjusting signage and directing staff to reopen overflow areas or close full sections during peak demand.

Monitor parking facility occupancy in real time using a management dashboard, adjusting signage and directing staff to reopen overflow areas or close full sections during peak demand.[9],[8]

Where your edge is

Learn the facility's parking management software (SKIDATA, ParkHub, T2) well enough to interpret occupancy dashboards and run end-of-day reports. Workers who can operate the analytics layer are more likely to move into a shift supervisor or parking manager role.

Where this role is heading

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

A direction you could grow

Security Guards

Parking attendants who already patrol facilities, respond to incidents, and coordinate with emergency services carry a directly transferable skill set into security guard work. The jump requires a state Guard Card in most states and customer de-escalation training but no additional education.

What you'd add
  • · State Guard Card certification (most states: 8-hour pre-assignment training)
  • · Incident report writing and documentation
  • · Radio communication and dispatch protocols
  • · First aid / CPR certification
What it takesMost of your skills carry over
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The data behind this timeline

On record since1905
Latest tracked employment134,650 (US, 2024)
Latest median pay$34,600 (2024)
Outlook-12% by 2034 (BLS National Employment Matrix 2024-34)
View all 24 cited data points
YearUS employmentMedian annual paySource
196060,000n/aESTIMATE
2000121,000n/aBLS-OEWS
2003113,490$16,630BLS-OEWS
2004120,080$16,800BLS-OEWS
2005124,250$16,930BLS-OEWS
2006131,870$17,320BLS-OEWS
2007131,860$18,020BLS-OEWS
2008136,470$18,790BLS-OEWS
2009129,990$19,200BLS-OEWS
2010124,590$19,530BLS-OEWS
2011126,160$19,820BLS-OEWS
2012126,520$19,540BLS-OEWS
2013130,190$19,500BLS-OEWS
2014136,440$19,800BLS-OEWS
2015144,150$20,630BLS-OEWS
2016146,350$21,730BLS-OEWS
2017145,400$22,810BLS-OEWS
2018145,900$23,870BLS-OEWS
2019147,390$25,140BLS-OEWS
2020123,790$27,080BLS-OEWS
202191,160$29,240BLS-OEWS
2022105,290$30,570BLS-OEWS
2023118,130$32,840BLS-OEWS
2024134,650$34,600BLS-OEWS
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