Headline risk
4%
Very Low RiskParking attendants
United States AI Work Index tracks this occupation on the shared structural baseline and then layers on local demand resilience, wages, and confidence.
Why This Score
Share of job tasks that overlap with current AI capabilities
Median annual wage
Projected employment change over 10 years
Typical preparation needed for this occupation
Occupation profile
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.
Task evidence
100% weighted task match · 0% effective coverage
Scores combine AI task overlap, human advantages, and local demand. How it works
United States Now
Median Wage
USD 34,600
Employment 2024
135.7K
Projected Change (2024–34)
3.0%
Openings (2024–34)
18.5K
Wage distribution
Demand outlook
Projections published, but no prose outlook available.
Role Profile
Tasks
- 1. Explain and calculate parking charges, collect fees from customers, and respond to customer complaints. AI use: 0%
- 2. Take numbered tags from customers, locate vehicles, and deliver vehicles, or provide customers with instructions for locating vehicles. AI use: 0%
- 3. Inspect vehicles to detect any damage. AI use: 0%
- 4. Provide customer assistance and information, such as giving directions or handling wheelchairs. AI use: 0%
- 5. Keep parking areas clean and orderly to ensure that space usage is maximized. AI use: 0%
- 6. 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. AI use: 0%
Technologies
Requirements
Work context
Worker profile
Median age 33.0 · 76K employed
Under 25: 30% · 25–54: 55% · 55+: 13%
Related
No direct US role match is available yet for this occupation.
Source coverage
11/11 source families · O*NET 30.2 / OEWS 2024 / ORS 2025 / OOH 2025-08-28 / Projections 2024-34 / CPS 2025 / Anthropic task penetration
Mapping quality
major_group_fallback · employment series present
Narrative & sources
Published limitations
This page shows the local country layer, not realised individual job outcomes. The global structural baseline is shared across countries; only the local demand and wage layer changes here.
Built from O*NET occupation descriptions, task statements, technology skills, work context, Job Zones, Anthropic task penetration, BLS OEWS wages, BLS projection tables, BLS ORS requirements, BLS OOH narrative content, BLS skills data, and BLS CPS occupation age tables.