Parking Enforcement Workers
Parking Enforcement Workers — AI exposure, safer roles, and a pivot plan.
Also known as: Meter Maid · Parking Manager · Parking Officer · Parking Enforcer · Parking Control Officer · Parking Meter Attendant
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.
Most exposed tasks
Highest structured exposure values in this role’s task mix — the work AI systems can already do most of.
-
Enter and retrieve information pertaining to vehicle registration, identification, and status, using hand-held computers.90
-
Collect coins deposited in meters.77
-
Prepare and maintain required records, including logs of parking enforcement activities, and records of contested citations.76
Augmentable tasks
Work where AI assists rather than replaces — the productivity frontier of this role.
-
Patrol an assigned area by vehicle or on foot to ensure public compliance with existing parking ordinance.59
-
Make arrangements for illegally parked or abandoned vehicles to be towed, and direct tow-truck drivers to the correct vehicles.59
-
Respond to and make radio dispatch calls regarding parking violations and complaints.58
Most durable tasks
Lowest exposure — typically judgment, relationships, physical presence, or accountability. This is the human moat.
The current data release does not distinguish durable tasks for this role.
Task exposure values and classifications come from the versioned data release — they are structured data, not model output. Bars show exposure contribution relative to this role’s task mix.
What this means
A score of 62 puts Parking Enforcement Workers in the most-exposed quarter of analyzed occupations. In practice, exposure this high is about the mix: 11 of 20 analyzed tasks lean automatable, 9 augmentable, and 0 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.
One next move: audit how much of your week sits in the exposed tasks above — then shift time toward the durable set or investigate the adjacent roles below.
Lower-exposure adjacent roles
Shown only when the target is at least 10 points lower under the same score version and skill overlap is at least 50%. These are adjacent roles with lower task exposure — not guaranteed “safe careers”.
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.
Your week probably doesn’t match the average
This page scores the occupation. The $9 Personalized Risk & Action Report scores your task mix — paste what you actually do and get your own score, confidence level, task matrix, human moat, and a 7/30/90-day plan.
Personalize my result — $9Related roles
Adjacent by skills or family — no exposure claim implied.
FAQ — Parking Enforcement Workers
- What does a score of 62 mean for a Parking Enforcement Workers?
- It means that, weighted across the 20 tasks we analyzed for this role, the task mix sits at 62 on a 0–100 exposure scale — in the most-exposed quarter 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?
- The highest-exposure tasks are: Enter and retrieve information pertaining to vehicle registration, identification, and status, using hand-held computers; Collect coins deposited in meters; Prepare and maintain required records, including logs of parking enforcement activities, and records of contested citations. Exposure is scored per task from structured data, not generated by a language model.
- Which parts of this job are most durable?
- The current data release does not distinguish durable tasks for this role.
- 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 2026.07.11-r1 · updated 2026-07-11 · baseline mapping: 20 of 20 tasks carry source-level provenance · methodology