US dataswitch to UK
Parking Enforcement Workers
entering and retrieving information pertaining to vehicle registration, performing simple vehicle maintenance procedures and identifying vehicles in violation of parking codes. If that's your week, this page is about your job.
The honest answer
AI changes the edges of this job, not the middle: patrolling an assigned area by vehicle or on foot to ensure public compliance with existing parking ordinance is work software can't reach.
What shifts is preparing and maintaining required records: the paper around the work, not the work.
Your week, as this page understands it
Patrol assigned area, such as public parking lot or city streets to issue tickets to overtime parking violators and illegally parked vehicles. The job title says “parking enforcement workers”. The real job is the part underneath: patrolling an assigned area by vehicle or on foot to ensure public compliance with existing parking ordinance. That is the thing someone has to be right about.
The exposed part of this job is specific, and we won’t pretend it is coming back. But parking enforcement workers is not one task. It is 22 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is patrolling an assigned area by vehicle or on foot to ensure public compliance with existing parking ordinance, and the ledger below shows exactly why.
Where the work sits, by task weight
- shifting to AI
- 4%
- changing shape
- 10%
- staying human
- 86%
These bars are tasks changing hands, not people being counted out. The ledger below shows which.
Whole-job exposure score 19 out of 100 (14–24 allowing for uncertainty): minimal exposure, across 22 scored tasks. The number is the support for the sentence above it, not a headline about anyone’s future.
How we know this
What is measured: Every published task statement for parking enforcement workers is rated on five dimensions: can a model produce the output, does the work need a body in a room, does it need a legally accountable person, does it depend on a person being trusted in the moment, and how much data exists. A published formula turns those five ratings into the score; the model never writes the number.
How the bar is built: Each task’s share of the bar is its published importance weight, so a task you do all day counts for more than one you do twice a year.
Release: 2026-q4.1, scores computed 2026-08-05. Read the full method.
Your job, task by task
These are the official task statements for this occupation, in plain English, sorted by what the evidence says is happening to each one. The official wording sits under every line so you can check the rewrite against it.
- One row is marked low confidence, so treat it as a ballpark rather than a fine measurement.
- 3 of this occupation's scored task statements carry a score that was measured under a different occupation's context, because the statement is shared between jobs and has only been scored once so far. Each one names the occupation it was measured under in the free routes below; none is presented as a measurement for this job.
- Task clusters are not derived in this release, so the task-cluster field is empty and no Collab365 Space routing is attached to this occupation yet.
Shifting to AI
1 taskTasks today’s tools can already do most of. This is the part we will not soften: where these rows are the bulk of your week, the week changes.
Preparing and maintaining required records
This is reading one thing and writing another: required records in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Prepare and maintain required records, including logs of parking enforcement activities, and records of contested citations.” (O*NET task statement)
How this row was scored
Exposure score: 88 out of 100 (84–92 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Keeping logs of enforcement activity and contested tickets is routine record-keeping software does end to end.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.
Changing shape
2 tasksTasks where the machine takes the producing and a person keeps the checking, the deciding, or the answering-for-it. For most jobs this is the biggest group, and it is where "transformation, not termination" is literally visible.
Entering and retrieving information pertaining to vehicle registration
The software now makes the first pass at information, but part of it still happens in the physical world. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Enter and retrieve information pertaining to vehicle registration, identification, and status, using hand-held computers.” (O*NET task statement)
How this row was scored
Exposure score: 50 out of 100 (43–57 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: The look-up itself is instant for software, but the officer is there because someone has to stand by the vehicle.
The five ratings: output a model can produce 4/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.
Investigating and answering complaints regarding contested parking citations
The software now makes the first pass at complaints regarding contested parking citations, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Investigate and answer complaints regarding contested parking citations, determining their validity and routing them appropriately.” (O*NET task statement)
How this row was scored
Exposure score: 56 out of 100 (52–60 allowing for uncertainty): partial exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Reviewing a challenged ticket against the evidence and the rules is desk work software handles well.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Staying human
19 tasksTasks that stay with a person, because they happen in the physical world, because the rules need someone accountable, or because the value is that a specific person does them.
Patrolling an assigned area by vehicle or on foot to ensure public compliance with existing parking ordinance
This work happens in the physical world: an assigned area, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Patrol an assigned area by vehicle or on foot to ensure public compliance with existing parking ordinance.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Patrolling streets on foot or by vehicle is physical presence from start to finish.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Writing warnings and citations for illegally parked vehicles
This work happens in the physical world: warnings, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Write warnings and citations for illegally parked vehicles.” (O*NET task statement)
How this row was scored
Exposure score: 14 out of 100 (7–21 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; work that happens in the physical world; someone qualified has to answer for it.
The rating behind it: Deciding a car is illegally parked and issuing the ticket happens at the curb beside the vehicle.
The five ratings: output a model can produce 3/4 · needs a body in a room 3/4 · needs an accountable person 2/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Responding to and making radio dispatch calls regarding parking violations and complaints
This work happens in the physical world: and making radio dispatch calls regarding parking violations, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Respond to and make radio dispatch calls regarding parking violations and complaints.” (O*NET task statement)
How this row was scored
Exposure score: 24 out of 100 (17–31 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Dispatch messages can be handled by software, but responding to a call means going to the location.
The five ratings: output a model can produce 2/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Maintaining close communications with dispatching personnel
This work happens in the physical world: close communications, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Maintain close communications with dispatching personnel, using two-way radios or cell phones.” (O*NET task statement)
How this row was scored
Exposure score: 24 out of 100 (17–31 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Staying in radio contact while out on patrol is tied to being out on patrol.
The five ratings: output a model can produce 2/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Identifying vehicles in violation of parking codes
This work happens in the physical world: vehicles, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Identify vehicles in violation of parking codes, checking with dispatchers when necessary to confirm identities or to determine whether vehicles need to be booted or towed.” (O*NET task statement)
How this row was scored
Exposure score: 16 out of 100 (9–23 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Plate reading and rule checking are automated, but someone still has to be at the vehicle.
The five ratings: output a model can produce 3/4 · needs a body in a room 3/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Observing and reporting hazardous conditions
This work happens in the physical world: hazardous conditions, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Observe and report hazardous conditions, such as missing traffic signals or signs, and street markings that need to be repainted.” (O*NET task statement)
How this row was scored
Exposure score: 14 out of 100 (7–21 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Spotting a missing sign or faded road marking requires being on that street to see it.
The five ratings: output a model can produce 2/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Maintaining assigned equipment and supplies
This work happens in the physical world: assigned equipment, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Maintain assigned equipment and supplies, such as hand-held citation computers, citation books, rain gear, tire-marking chalk, and street cones.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Looking after chalk, cones, rain gear and handheld devices is hands-on.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Show the other 12 tasks
Providing information to the public regarding parking regulations and facilities
staying humanThis work happens in the physical world: information, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Provide information to the public regarding parking regulations and facilities, and the location of streets, buildings and points of interest.” (O*NET task statement)
How this row was scored
Exposure score: 35 out of 100 (28–42 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Parking rules and directions are well documented, but the questions arrive from people on the sidewalk.
The five ratings: output a model can produce 3/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 4/4.
Assigning and reviewing the work of subordinates
staying humanThe value here is that a specific person handles the work of subordinates and stands behind it. That is earned, not computed.
importance 3 · SupplementalSource: “Assign and review the work of subordinates.” (O*NET task statement)
How this row was scored
Exposure score: 26 out of 100 (19–33 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the value is that a specific person does it.
The rating behind it: Handing out work and checking it is about managing colleagues, which needs someone they answer to.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.
Locating lost, stolen and counterfeit parking permits and taking necessary enforcement action
staying humanThis work happens in the physical world: lost, stolen and counterfeit parking permits, in a real place. Software cannot follow it there.
importance 4 · SupplementalSource: “Locate lost, stolen, and counterfeit parking permits, and take necessary enforcement action.” (O*NET task statement)
How this row was scored
Exposure score: 25 out of 100 (18–32 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Permit records can be cross-checked automatically, but seizing a fake permit happens at the vehicle.
The five ratings: output a model can produce 2/4 · needs a body in a room 2/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Training new or temporary staff
staying humanThis work happens in the physical world: new or temporary staff, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Train new or temporary staff.” (O*NET task statement)
How this row was scored
Exposure score: 18 out of 100 (6–30 allowing for uncertainty): minimal exposure, low confidence.
Why it sits in this group: work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Training material is easy to write, but showing new staff the route means walking it with them.
The five ratings: output a model can produce 2/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.
Making arrangements for illegally parked or abandoned vehicles
staying humanThis work happens in the physical world: arrangements, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Make arrangements for illegally parked or abandoned vehicles to be towed, and direct tow-truck drivers to the correct vehicles.” (O*NET task statement)
How this row was scored
Exposure score: 12 out of 100 (5–19 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Arranging a tow can be done by message, but pointing the driver at the right vehicle happens on the street.
The five ratings: output a model can produce 2/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Appearing in court at hearings regarding contested traffic citations
staying humanThis work happens in the physical world: court, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Appear in court at hearings regarding contested traffic citations.” (O*NET task statement)
How this row was scored
Exposure score: 2 out of 100 (0–6 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world; someone qualified has to answer for it; the value is that a specific person does it.
The rating behind it: Attending a hearing to defend a citation means appearing in person before an adjudicator.
The five ratings: output a model can produce 0/4 · needs a body in a room 3/4 · needs an accountable person 2/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.
Marking tires of parked vehicles with chalk and recording time of marking
staying humanThis work happens in the physical world: tires of parked vehicles, in a real place. Software cannot follow it there.
importance 4 · SupplementalSource: “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.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: the same decision, made over and over; work that happens in the physical world.
The rating behind it: Chalking tires and returning later to check them is done on foot.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Performing simple vehicle maintenance procedures
staying humanThis work happens in the physical world: simple vehicle maintenance procedures, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Perform simple vehicle maintenance procedures, such as checking oil and gas, and report mechanical problems to supervisors.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Checking oil and fuel on a vehicle is done with your hands.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Performing traffic control duties, setting up barricades and temporary signs
staying humanThis work happens in the physical world: traffic control duties, in a real place. Software cannot follow it there.
importance 3 · CoreSource: “Perform traffic control duties such as setting up barricades and temporary signs, placing bags on parking meters to limit their use, or directing traffic.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Setting out barricades and signs and directing traffic is physical work in the road.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 2/4.
Providing assistance to motorists needing help with problems
staying humanThis work happens in the physical world: assistance, in a real place. Software cannot follow it there.
importance 3 · SupplementalSource: “Provide assistance to motorists needing help with problems, such as flat tires, keys locked in cars, or dead batteries.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Helping a driver with a flat tire or a dead battery is practical help given in person.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.
Collecting coins deposited in meters
staying humanThis work happens in the physical world: coins, in a real place. Software cannot follow it there.
importance 4 · SupplementalSource: “Collect coins deposited in meters.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Emptying coins from meters is hands-on collection work.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Winding parking meter clocks
staying humanThis work happens in the physical world: meter clocks, in a real place. Software cannot follow it there.
importance 4 · SupplementalSource: “Wind parking meter clocks.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Winding a meter clock is a hands-on job at the meter.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
What this job pays, and how many people do it
- Median pay
- $46,730a year, the middle of the range, so half earn more and half earn less.bls-oews, 2025 · May 2025 estimates (national_M2025_dl.xlsx)
How we know this
Source: bls-oews
Reference period: May 2025 estimates (national_M2025_dl.xlsx)
Rounding: Shown as published.
- People doing this job
- 9,050in the US, 2025.bls-oews · May 2025 estimates (national_M2025_dl.xlsx)
What is deliberately not here: a forecast of how many of these jobs exist in ten years. Where an official projection exists for a market we publish it with its vintage; where it does not, we leave the space empty rather than borrow the other country’s number.
Why this is shifting
The reason is boringly specific. Most of what is shifting here is reading one thing and writing another: required records in, a record out. The rows above are exactly that shape: preparing and maintaining required records and entering and retrieving information pertaining to vehicle registration. What it cannot do is be there in the room, and that is still where an assigned area gets done. Which is why this page talks about your tasks changing, not your job ending.
Your move
Over a pint: what I’d tell you if you were my friend
Start with what does not change: patrolling an assigned area by vehicle or on foot to ensure public compliance with existing parking ordinance is the middle of this job, and the evidence on this page says it stays with a person.
So, given all that: 4% of this job's task weight sits in rows the software is already learning, 10% in rows that change shape rather than disappear, and 86% in rows it is nowhere near. That is the position, measured across 22 scored tasks. It is not a forecast about you.
So the thing worth your attention is not the job going away. It is the layer around it. Preparing and maintaining required records is the part turning into software, and being the person who understands that layer is worth money.
This week: one thing
Ask the one question. Find whoever is bringing new software into your workplace (the manager, the office, whoever runs the system) and ask them what it is meant to do to required records, and what it is not meant to touch. Ten minutes, this week, before anyone decides it for you.
- What you end up holding
- a straight answer about what is actually being rolled out, and when
- How long it takes
- ten minutes
If there’s nobody obvious to ask, or you’d rather not ask your manager: Put the same question to your union rep, your shift lead or the person who has been there longest, in person, over a break. Same ten minutes, same answer, and you will usually get a straighter one. Write down what they say. The note is the artifact, and it tells you whether an assigned area is in scope or not. Nothing to log into, no license needed.
Over the next 90 days
Get inside the tool rollout rather than waiting for it. Over the next ninety days, ask to be in the group that tests, checks or signs off whatever new system arrives near entering and retrieving information pertaining to vehicle registration. It is usually an unglamorous seat that nobody fights for, and it is the one that decides how the software is used on your job rather than to it.
Over the next 12 months
On this evidence I would not retrain out of this job, and I will say that plainly rather than hedge it. The task list here is dominated by work that stays with a person. What I would do with a year is get formally recognised for the layer around it (the systems, the compliance, the planning), so you are the one who understands the software instead of the one it is done to. Before you pay for anything, use CareerOneStop - Find local training. It is free, it is the Labor Department's own service, and it is listed below with the rest of the free routes.
The roads out of here, and why I am not sending you down them
I looked at the obvious moves out of this job, and here is what I found.
I checked the 12 nearest US occupations to parking enforcement workers (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was parking attendants: only about 4% of its durable work is work you already do and it pays 24.8% less. And on the numbers you do not need one. This job scores 19/100 here, with only 4% of the task list in the top band, and “patrol an assigned area by vehicle or on foot to ensure public…” is not work that hands over cleanly. None of them beats deepening what you already have.
How that was checked: this job was compared against all 830 US occupations in this release on their official task statements, and the 12 nearest were examined one by one. A move that turns on an industry, an employer or a qualification rather than on the work itself will not show up in a check like that. And this release carries no licence register, so anything you are weighing needs that looked up separately.
3 moves I checked and rejected
These are the obvious-looking jumps. They are here with their reasons rather than quietly dropped, because the ones that fail are worth knowing about. It is one less thing to turn over at night.
Parking Attendants
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already patrol an assigned area by vehicle or on foot to ensure public compliance…, and their equivalent is to patrol parking areas to prevent vehicle damage and vehicle or property thefts. Across both published task lists that is about 4% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 4% of the durable side of that job. That is a different job, not a next step. It is a pay cut, in those words: $35,150 against your $46,730, 24.8% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice.
Conservation Scientists
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already train new or temporary staff, and their equivalent is to train staff on park programs. Across both published task lists that is about 1% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 1% of the durable side of that job. That is a different job, not a next step.
Crossing Guards and Flaggers
Why it looked obvious: It came up as a near neighbour on the overall shape of the two task lists, but nothing in your day matched a specific piece of theirs closely enough to name.
Why I am not recommending it: The two task lists look alike from a distance and share almost nothing close up: no single piece of their work matched a piece of yours. That is a resemblance, not a route. It is a pay cut, in those words: $38,100 against your $46,730, 18.5% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice.
What I’d stop worrying about
A friend tells you what not to spend fear on. This is that list.
The headline number you read somewhere
The big “X% of jobs” figures are about the whole economy, not about you. The number that describes your job is on this page: 4% of its task weight, across 22 scored tasks. Every row behind it is printed above with the source. Check ours; ignore theirs.
The headlines about your trade disappearing
They are usually about the technology, not the timetable. Changes to work like patrolling an assigned area by vehicle or on foot to ensure public compliance with existing parking ordinance arrive through rules, insurance and money, slowly and visibly. This page tracks the task evidence and will move when it moves.
Retraining out of a job that is holding up
On this evidence I would not spend money leaving. Spend it on the layer around the job instead: the tools, the paperwork, the planning. That is where the change actually is.
The “obvious” next job everyone suggests
I checked the obvious moves and most of them did not survive. The reasons are printed with the routes above, including the pay and the gate. A move that fails on the numbers is worth knowing about so you can stop turning it over at night.
You are reading the United States figures
The United Kingdom splits this work across more than one official group, of which Police community support officers is the closest. The pay and employment figures are not directly comparable, and we do not average them together.
Switch to the United Kingdom page →partial match
In UK official statistics this job is counted as Police community support officers. Pay and employment stay on this page’s own group; the task list and the scores do not cross over.
Your route through this
Where to go next, and what it costs
Free, and complete
The moves above cost nothing. These are the real services that go with them: public, government-funded, and free at the point of use. Nothing on this page is behind an email address or a payment.
Anywhere in the US:
CareerOneStop - Find local training
Search what's running near you, from the Labor Department's own database, before anyone sells you a course.
Free to search; individual programs vary, and some are funded
Anywhere in the US:
An American Job Center will sit down with you for free. Find yours by ZIP code.
Free
Anywhere in the US:
CareerOneStop - Licensed occupations finder
Check what your state actually requires before you pay for anything.
Free
Anywhere in the US:
Free
Why there is no community here
Collab365, who build this site, run paid Spaces for a small number of subjects, and none of them is built for this job. We are not going to point you at the nearest one and call it a fit.
So the free services listed on this page are the whole answer, and it is the same answer we would give a friend.
Noted, and thank you. We’ll email you if a Space for parking enforcement workers launches. Nothing else.
That did not look like an email address, so nothing was saved. Have another go below.
We could not save that. The fault is ours, not yours, and your address was not stored. Please try again later.
No deadline on any of this. The page will still be here, and the data is refreshed on a published schedule rather than when someone wants a headline.
Questions people ask about this job
- Will AI replace Parking Enforcement Workers?
- Not as a job, but it is already doing parts of the work. Across the 22 official task statements scored for Parking Enforcement Workers (United States, SOC 33-3041), 4% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 19 out of 100 (range 14–24, band: minimal). That is a statement about tasks, not about headcount: this measures what AI could do, not whether any employer adopts it, whether the law allows it, or whether doing the routine parts faster creates more demand for the human parts. Figures are from release 2026-q4.1.
- Which tasks in “Parking Enforcement Workers” can AI already do?
- The highest-scoring tasks in release 2026-q4.1 are: “Prepare and maintain required records, including logs of parking enforcement activities, and records of contested citations” (88/100, very high); “Investigate and answer complaints regarding contested parking citations, determining their validity and routing them appropriately” (56/100, partial); “Enter and retrieve information pertaining to vehicle registration, identification, and status, using hand-held computers” (50/100, partial). Each score comes from five published 0–4 ratings turned into a number by a published formula, and each carries the model's one-sentence reason on the page.
- Which tasks in “Parking Enforcement Workers” stay human?
- About 86% of this job's task weight sits in work that scores low for AI exposure. The lowest-scoring tasks in release 2026-q4.1 are: “Wind parking meter clocks” (0/100, minimal); “Collect coins deposited in meters” (0/100, minimal); “Provide assistance to motorists needing help with problems, such as flat tires, keys locked in cars, or dead batteries” (0/100, minimal). Low scores usually mean the task needs a body in a room, a legally accountable human, or trust built in real time. Those are the three things the scoring rubric treats as gates rather than obstacles.
- What should someone working in “Parking Enforcement Workers” do about AI?
- Start from the ledger rather than the headline: 4% of this job's weighted core work is exposed, and roughly 86% is not. The practical move is to spend more of your week on the tasks that score low, the ones above, and to get fluent at directing AI through the tasks that score high, because those are the parts that change whether or not you are ready for them. This page does not predict your job, and nothing here is career advice tailored to you: the score describes the occupation, not the person.
- How is the AI exposure score for Parking Enforcement Workers calculated?
- Each official task statement for the occupation is rated on five published 0–4 dimensions (output replicability, physical embodiment, licensed accountability, real-time human trust, and data availability) by claude-opus-5 using scoring prompt task_scoring_v1.0. The model never writes the score; a published formula turns the five ratings into a 0–100 number, so every score can be recomputed by hand. The occupation figure is the importance-weighted mean across 22 scored tasks. The prompt, the rubric, the formula and the full dataset are published at https://futureproof.collab365.com/method and https://futureproof.collab365.com/data/2026-q4.1 under CC BY 4.0.
Where these numbers come from
About the data on this page
- One row is marked low confidence, so treat it as a ballpark rather than a fine measurement.
- The match between this job and its counterpart in the other country is partial, so the two pages count slightly different groups of people.
- 3 of this occupation's scored task statements carry a score that was measured under a different occupation's context, because the statement is shared between jobs and has only been scored once so far. Each one names the occupation it was measured under in the free routes below; none is presented as a measurement for this job.
- Task clusters are not derived in this release, so the task-cluster field is empty and no Collab365 Space routing is attached to this occupation yet.
- Task statements
- onet-dbProcessing: catalogue-bridge → onet-im-rt-weighting → task-scoring → score-aggregation
- Task weights
- onet-db (im-rt)
- Scores
- Rubric task_scoring_v1.0, model claude-opus-5, computed 2026-08-05.
- Pay and employment
- bls-oews (May 2025 estimates (national_M2025_dl.xlsx))bls-oews (May 2025 estimates (national_M2025_dl.xlsx))
Figures on this page come from release 2026-q4.1, published 2026-08-05. Every release keeps its own permanent address, so a figure you cite in March is still there, unchanged, in November.
The plain-English wording on this page is assembled directly from the task statements and the published ratings, not written by hand for this occupation. That is why it is specific, and it is also why we say so.
The routes and free resources further up are today’s, not the release’s (last reviewed 2026-08-05). A route is an offer, not a historical fact, so it moves on its own clock.
Using these figures?
Cite this
Everything on this site is published under CC BY 4.0. Quote it, chart it, sell something built on it. Just say where it came from, and cite the dated release rather than the site, so the figure you quote stays checkable.
Plain text
Collab365 (2026). Collab365 Futureproof: task-level AI exposure for US and UK occupations, release 2026-q4.1 (methodVersion 2.0.0, promptVersion task_scoring_v1.0). https://futureproof.collab365.com/data/2026-q4.1. Licensed CC BY 4.0. Built with O*NET data (USDOL/ETA, CC BY 4.0); ONS data (Open Government Licence v3.0); GAISI task framework (arXiv:2507.22748, MIT); BLS data (public domain).
BibTeX
@misc{collab365futureproof2026q41,
title = {Collab365 Futureproof: task-level AI exposure for US and UK occupations, release 2026-q4.1},
author = {{Collab365}},
year = {2026},
url = {https://futureproof.collab365.com/data/2026-q4.1},
note = {Release 2026-q4.1, methodVersion 2.0.0, promptVersion task_scoring_v1.0, CC BY 4.0}
}Data as of release 2026-q4.1, published . Releases never change after publication; when the figures move, a new dated release is published beside this one and this one stays exactly where it is.