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# Will parking enforcement workers be replaced by AI?

Updated October 2026

Parking enforcement workers score 30 out of 100 for AI exposure. 58% of their task time needs a person. AI can do 11% and helps with 31%.

-   **11%** AI can do it
-   **31%** AI helps
-   **58%** Needs a person

Moderate exposure

Lower than 63% of the 923 jobs we scored.

## Task by task

We graded 22 tasks, most exposed first. AI can do 2 of them, helps with 7 and leaves 13 to people.

| Task | AI exposure |
| --- | --- |
| Prepare and maintain required records, including logs of parking enforcement activities, and records of contested citations. Logs and records are structured data AI can generate and maintain. | 70% AI can do it |
| Enter and retrieve information pertaining to vehicle registration, identification, and status, using hand-held computers. Vehicle lookups and data entry are routine digital work. | 62% AI can do it |
| Write warnings and citations for illegally parked vehicles. AI can draft citations from entered details; officer verifies violation. | 55% AI helps |
| Investigate and answer complaints regarding contested parking citations, determining their validity and routing them appropriately. AI can review citation records and draft contest determinations. | 55% AI helps |
| Provide information to the public regarding parking regulations and facilities, and the location of streets, buildings and points of interest. Chatbots can answer regulation and location questions; on-site help remains. | 50% AI helps |

## How parking enforcement workers compare

All jobs (923)

Protective service (26)

The dark line is **parking enforcement workers, at 30**. Each dot is a score, and darker dots mean more jobs share it. The short marks are the averages, 37 for all jobs and 31 for protective service.

## Pay and outlook in the US

Median pay

$46,730 a year, May 2025

People employed

9,050 in the US, May 2025

Projected change in jobs

\-1.1% from 2024 to 2034

## Skills to build

-   Enter and retrieve vehicle records in Integrated Parking Solutions MApp
-   Issue citations on FastTrack handheld citation computers
-   Verify plates and vehicles visually before booting or towing
-   Answer contested citation appeals with documented determinations in Microsoft Word
-   Coordinate boot and tow decisions with dispatchers by radio

## Safer roles nearby

5 related jobs with lower scores.

-   [Parking attendants20 out of 100](https://www.aigentcy.com/ai-exposure/parking-attendants/)
-   [Security guards26 out of 100](https://www.aigentcy.com/ai-exposure/security-guards/)
-   [Transit police officers29 out of 100](https://www.aigentcy.com/ai-exposure/transit-police-officers/)
-   [Highway maintenance workers8 out of 100](https://www.aigentcy.com/ai-exposure/highway-maintenance-workers/)
-   [Crossing guards24 out of 100](https://www.aigentcy.com/ai-exposure/crossing-guards/)

## Questions about parking enforcement workers and AI

Will AI replace parking enforcement workers?

Partly. About 2 in 10 working hours go to tasks AI can already do, mostly keeping enforcement logs and records and entering vehicle registration data on handheld computers. Patrolling streets, confirming vehicles by sight, handling roadside problems and directing traffic stay with people, since those tasks need a person in the field.

Which parking enforcement tasks is AI taking over?

Record keeping is the most exposed task, with an exposure score of 70, because logs and records of enforcement activity are structured data that AI can generate and maintain. Vehicle lookups and data entry come next at 62, since plate and status checks are routine digital work that software handles well.

Which parking enforcement tasks stay with people?

Physical field work stays human, with exposure scores of 2 to 4. Collecting coins from meters, winding meter clocks, checking oil and gas, setting barricades and helping motorists with flat tires or locked keys all need hands in the field, and together they make up most of the job's task weight at 58 percent.

How can parking enforcement workers stay valuable as AI takes on records?

Focus on tasks that need a person on the street and a sign-off on the result. Confirm vehicles visually before any boot or tow, learn the contested citation review process in your agency's records system, and keep handheld citation work accurate in FastTrack and MApp so your records hold up on appeal.

## Related jobs

-   [Railroad conductors32 out of 100](https://www.aigentcy.com/ai-exposure/railroad-conductors/)
-   [Chauffeurs30 out of 100](https://www.aigentcy.com/ai-exposure/chauffeurs/)
-   [Dispatchers65 out of 100](https://www.aigentcy.com/ai-exposure/dispatchers/)
-   [Vehicle inspectors31 out of 100](https://www.aigentcy.com/ai-exposure/vehicle-inspectors/)

## Next steps for parking enforcement workers

-   ### Check your job
    
    Your job title is a rough guide. Your tasks decide your score. Paste your job description or CV to see which tasks AI can do.
    
    [Check your job](https://www.aigentcy.com/tools/ai-exposure-checker/) [Check your CV](https://www.aigentcy.com/tools/cv-checker/)
    
-   ### Estimate team savings
    
    The score is per person. Add headcount and salary to see the hours AI can take on in a team of parking enforcement workers, and what they cost.
    
    [Estimate what AI saves a team of parking enforcement workers](https://www.aigentcy.com/tools/team-ai-audit/?role=parking-enforcement-workers) [Work out the return on automation](https://www.aigentcy.com/tools/ai-savings-calculator/)
    

### Check which roles in your team AI can take on

We map your team's tasks, show what AI can do today and build the automations that pay back first.

[Book an AI audit](https://www.aigentcy.com/audit/)

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-   [**Jobs A to Z**Every job we score, by first letter.](https://www.aigentcy.com/ai-exposure/jobs/)
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-   [**How we score AI exposure**The grading, the weights and every source.](https://www.aigentcy.com/ai-exposure/methodology/)

Sources and licences

Occupation data from the O\*NET 30.3 Database by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA), used under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) and modified by Aigentcy. O\*NET® is a trademark of USDOL/ETA. Wage, employment and projection data from the U.S. Bureau of Labor Statistics. EU occupation names from ESCO, European Commission. AI usage signals from the Anthropic Economic Index (CC BY) and Microsoft Research (CC BY 4.0). [Methodology and sources](https://www.aigentcy.com/ai-exposure/methodology/). Scores © Aigentcy. Quote them with a link to the page.
