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Parking Enforcement Workers

Patrol assigned area, such as public parking lot or city streets to issue tickets to overtime parking violators and illegally parked vehicles.

Also known as: Meter Maid · Parking Manager · Parking Officer · Parking Enforcer · Parking Control Officer · Parking Meter Attendant

AI Task Exposure Score

Moderate exposure

More exposed than 32% of 968 occupations · Rank #644 (1 = most exposed)

This score estimates how exposed the tasks in a role are to current and near-term AI capabilities. It does not predict whether a specific person will lose a job.

Your free role snapshot

Start with the work, not the headline

This occupation baseline already contains different kinds of work. These are the two ends of its current task range and one useful action you can take now.

Most exposed task

Prepare and maintain required records, including logs of parking enforcement activities, and records of contested citations.

Augmentable 55/100 exposure

Most durable task

Wind parking meter clocks.

Durable 10/100 exposure

Useful next step

Make one change to the task mix

Pilot AI on one augmentable task, then document the judgment, relationships, and accountability you still own.

Want this mapped to your actual week? Know what to strengthen, what to delegate to AI with review, and what to do over the next 7, 30, and 90 days.

Build my 7/30/90-day action plan — $9

Most exposed tasks

No task is classified fully automatable in this release. The highest-exposure task relative to this role is shown in the free snapshot above; the assistive work is detailed next.

Augmentable tasks

Work where AI assists rather than replaces — the productivity frontier of this role.

  • Prepare and maintain required records, including logs of parking enforcement activities, and records of contested citations.55
  • Enter and retrieve information pertaining to vehicle registration, identification, and status, using hand-held computers.45
  • Investigate and answer complaints regarding contested parking citations, determining their validity and routing them appropriately.45

Most durable tasks

Lowest exposure — typically judgment, relationships, physical presence, or accountability. This is the human moat.

  • Collect coins deposited in meters.10
  • Wind parking meter clocks.10
  • Patrol an assigned area by vehicle or on foot to ensure public compliance with existing parking ordinance.15

Task exposure values and classifications are published, versioned estimates audited against the anchored rubric. This page reads them from the data release rather than generating them at request time. Bars show exposure contribution relative to this role’s task mix.

What this means

A score of 27 puts Parking Enforcement Workers in the second quartile of analyzed occupations. In practice, exposure this level is about the mix: 0 of 20 analyzed tasks lean automatable, 3 augmentable, and 17 durable. The useful question isn’t “will AI take this job” — it’s which tasks go first, which get faster, and where to reposition time. That’s what the personalized report maps against your actual week.

Lower-exposure adjacent roles

No adjacent role in the current data release is at least 10 points lower with ≥50% skill overlap — we don’t label anything “safer” unless the data supports it.

Labor-market context

  • $46,730median wage
  • 9,050employed
  • 700annual openings
  • -2.4%projected growth

Context only — labor statistics are not inputs to the exposure score. See methodology.

Turn your actual week into a plan

Know which work to strengthen, what to delegate to AI with review, and what to do over the next 7, 30, and 90 days. Your $9 plan includes a confidence-rated personal score, task matrix, human moat, and only genuinely lower-exposure adjacent roles.

Build my 7/30/90-day action plan — $9

Related roles

Adjacent by skills or family — no exposure claim implied.

How this score was calculated

The score is the plain average of the AI-exposure values of this role’s 20 analyzed tasks (equal task weights in this release — no hidden factors):

  • Augmentable 3 tasks, averaging 48/100 exposure
  • Durable 17 tasks, averaging 23/100 exposure

score = (3×48 + 17×23) ÷ 20 ≈ 27

Every task’s exposure value was scored against a published anchored rubric that scores tasks as actually performed — physical, in-person, and accountability requirements included (data release 2026.07.12-r2). The band (Moderate) is a corpus quartile; the percentile is tie-aware across all 968 occupations.

FAQ — Parking Enforcement Workers

Will AI replace Parking Enforcement Workers?
This score cannot predict whether this occupation or any individual job will be replaced. It shows which tasks current and near-term AI can perform or accelerate, which tasks remain more durable, and where a worker can adapt. Employer decisions, demand, regulation, and how the role changes are outside the score.
What does a score of 27 mean for a Parking Enforcement Workers?
It means that, weighted across the 20 tasks we analyzed for this role, the task mix sits at 27 on a 0–100 exposure scale — in the second quartile of analyzed occupations. It measures task exposure to current and near-term AI capabilities, not the probability of losing a job.
Which tasks in this role are most exposed to AI?
This role has no strongly automatable task in the current data release.
Which parts of this job are most durable?
The most durable responsibilities are: Collect coins deposited in meters; Wind parking meter clocks; Patrol an assigned area by vehicle or on foot to ensure public compliance with existing parking ordinance. Durable tasks typically depend on judgment, relationships, physical presence, or accountability.
Is this score personalized to me?
No — this page shows the occupation-level baseline. Two people with the same title often do different work. The $9 personalized report recalculates the score from the tasks you actually do and builds a concrete 7/30/90-day plan around them.

Score version jr-v1 · data release 2026.07.12-r2 · updated 2026-07-13 · baseline mapping: 20 of 20 tasks carry source-level provenance · methodology