As of November 2026,
Parking Enforcement Workers has an AI-exposure score of 64/100
(High exposure) on the AI-Safe Careers index. This is an estimate of task
exposure, not a prediction of job loss.
Score inputs for this role:
This role starts from O*NET 31.0 occupational descriptors and is empirically grounded by Penn/OpenAI GPTs are GPTs study, Felten, Raj and Seamans AIOE index. BLS labor-market figures are separate context, not score inputs.
Parking Enforcement Workers
More exposed than 78% of the roles we track. Median pay ~US$46,730. About 700 projected openings a year (BLS 2024–34 - growth plus replacement).
Pay & demand figures are US medians (BLS, in USD) - your local figures will differ. Your exposure score applies broadly.
Will AI replace Parking Enforcement Workers?
No exposure score can predict whether AI will replace this role. The 64/100 score means our current model estimates high task exposure from the sources listed on this page. It does not predict an employer decision, headcount, or an individual outcome. The task map below shows the work assessed and where human judgment remains important.
Early-career context (study ages 22-25)
This role's High score and automation-heavy task mix point in the same direction as the study's highest-exposure automation cohort. The measures are not identical, so the study result is context rather than a direct forecast for this role.
The November 2025 revision reports a 16% relative employment decline for workers ages 22-25 in the most AI-exposed U.S. occupations, after firm-level controls, relative to workers in less-exposed fields and more experienced workers in the same occupations.
Use the task map to identify durable work and the skills worth building early.
Stanford Digital Economy Lab, Canaries in the Coal Mine - November 2025 revision
This is group-level U.S. payroll evidence, not a personal forecast. The authors do not claim that AI alone caused the change, and this context does not alter the exposure score.
How this role compares to similar Protective Service roles
What this role usually involves
Patrol assigned area, such as public parking lot or city streets to issue tickets to overtime parking violators and illegally parked vehicles.
Broad guidance for this preparation level; exact requirements vary by role and employer.
Source: O*NET 31.0 exact occupation - Parking Enforcement Workers, SOC 33-3041.00. Context describes the role; the AI-exposure score remains a separate task-exposure estimate.
Parking Enforcement Workers tasks, by AI exposure
- Enter and retrieve information pertaining to vehicle registration, identification, and status, using hand-held computers.
- Mark tires of parked vehicles with chalk and record time of marking, and return at regular intervals to ensure that parking time limits are not exceeded.
- Locate lost, stolen, and counterfeit parking permits, and take necessary enforcement action.
No augmentable tasks identified for this role - all 20 of its individually-assessed tasks read as automatable.
No durable tasks identified for this role - all 20 of its individually-assessed tasks read as automatable.
We analyzed all 20 Parking Enforcement Workers tasks - 20 automatable. The full task map - every task with exactly what to do about each - is in your Career Report.
Your report unlocks three concrete artifacts
Every task scored with what to automate, augment, or protect.
Related roles with exposure deltas, salary, demand, and reachability. Lower-exposure options appear only when the data supports them.
A keepable roadmap plus resume and LinkedIn repositioning.
Grounded in O*NET-linked or curated role data, with Penn, Anthropic Economic Index, and AIOE signals where matched. BLS labor-market context is separate - not generic advice.
Adjacent career paths
Relatedness shows how reachable a move may be. A path is labeled lower exposure only when its score is at least 6 points lower; every row shows the measured difference.
Enter and retrieve information pertaining to vehicle registration, identification, and status, using hand-held computers.
Your AI-Safe Career Report
Every task scored with what to do about it; adjacent paths with honest exposure deltas, salary, demand, and reachability; a skill-gap map; a 30/60/90-day roadmap; Agent Reality Check; plus a résumé and LinkedIn rewrite and professional PDF.
Grounded in O*NET-linked or curated role data, with Penn, Anthropic Economic Index, and AIOE signals where matched. BLS labor-market context is separate.
AI was the most-cited reason for announced U.S. job cuts in 2026 through September (21% of all cuts) - the workers who adapt earliest fare best. - Challenger, Gray & Christmas, 2026The upside: AI now appears in 7.3% of U.S. job postings on Indeed, up from 1.7% in January 2019 - the skills employers ask for are shifting, and adapting early pays. - Indeed Hiring Lab AI Tracker, 2026
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Parking Enforcement Workers - median pay by US state (BLS OEWS, USD)
Median annual wage, in USD. US national: US$46,730. More states are being added.