Will AI replace Parking Attendants?
AI reaches little of this job’s work.
8/100
Low exposure
More exposed to AI than 18% of US workers.
- AI already used in
- 0% of the work
- As AI tools mature: up to
- 16% of the work
What the job involves
Park vehicles or issue tickets for customers in a parking lot or garage. May park or tend vehicles in environments such as a car dealership or rental car facility. May collect fee.
Where AI reaches the work
The job’s main tasks, heaviest first, by how far AI reaches them.
Within reach(2)
- Provide customer assistance and information, such as giving directions or handling wheelchairs.
- Issue ticket stubs or place numbered tags on windshields, log tags or attach tag to customers' keys, and give customers matching tags for locating parked vehicles.
Out of reach(13)
- Explain and calculate parking charges, collect fees from customers, and respond to customer complaints.
- Take numbered tags from customers, locate vehicles, and deliver vehicles, or provide customers with instructions for locating vehicles.
- Inspect vehicles to detect any damage.
- Keep parking areas clean and orderly to ensure that space usage is maximized.
- Greet customers and open their car doors.
and 8 more
Also called
Parking Lot Attendant · Hiker · Parking Attendant · Valet Parker · Parking Ramp Attendant · Valet Attendant · Auto Hiker · Auto Parker
Related jobs
What these numbers mean
The score is the share of this job’s work, weighted by how important and frequent each task is, that AI could do in half the time: tasks an AI model could do alone count in full, tasks that need software built on AI count half.
“AI already used” is the share of the work in tasks where people are recorded using AI today. “As AI tools mature” counts every task AI could halve, with or without extra software.
The percentile compares the score with every job’s, weighted by how many people in the US do each one. Exposure means AI could change how the work is done, not that the job goes away. These are estimates for the typical job, not predictions.
Sources
- O*NET 31.0 Database, U.S. Department of Labor, Employment and Training Administration
- GPTs are GPTs: Labor market impact potential of LLMs (task labels), Eloundou, Manning, Mishkin & Rock (2023), OpenAI and University of Pennsylvania
- Anthropic Economic Index: labor market impacts (task penetration), Anthropic
- Occupational Employment and Wage Statistics, May 2025 (national and metropolitan areas), U.S. Bureau of Labor Statistics