# Parking Attendants

> 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.

- **SOC code:** 53-6021.00
- **Canonical URL:** https://singulariki.com/roles/role-53-6021-00
- **Also known as:** Parking Attendant, Parking Lot Attendant, Valet Attendant, Valet Parker, Hiker, Parking Cashier, Parking Ramp Attendant, Valet Parking Attendant
- **Frame:** "AI exposure" means task overlap (how codifiable the work is), not jobs lost or a forecast. Every figure below is traced to a named public dataset.

## What this work is

**Core tasks** (O*NET):
- Take numbered tags from customers, locate vehicles, and deliver vehicles, or provide customers with instructions for locating vehicles.
- Inspect vehicles to detect any damage.
- Greet customers and open their car doors.
- 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.
- Perform cash handling tasks, such as making change, balancing and recording cash drawer, or distributing tips.
- Patrol parking areas to prevent vehicle damage and vehicle or property thefts.
- Explain and calculate parking charges, collect fees from customers, and respond to customer complaints.
- Park and retrieve automobiles for customers in parking lots, storage garages, or new car lots.
- Provide customer assistance and information, such as giving directions or handling wheelchairs.
- Keep parking areas clean and orderly to ensure that space usage is maximized.
- Direct motorists to parking areas or parking spaces, using hand signals or flashlights as necessary.
- Escort customers to their vehicles to ensure their safety.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Speaking _(essential_skill)_
- Far Vision _(ability)_
- Customer and Personal Service _(knowledge)_
- Service Orientation _(transferable_skill)_
- Oral Comprehension _(ability)_
- Oral Expression _(ability)_
- Near Vision _(ability)_
- Speech Recognition _(ability)_
- Active Listening _(essential_skill)_
- Problem Sensitivity _(ability)_
- Speech Clarity _(ability)_
- Spatial Orientation _(ability)_

**Skills in demand:**
- Speech Recognition _(Specialized Skill)_
- Active Listening _(Common Skill)_
- English Language _(Common Skill)_
- Social Perceptiveness _(Common Skill)_
- Microsoft Word _(Common Skill)_
- Microsoft Outlook _(Common Skill)_
- Microsoft Excel _(Common Skill)_
- Information Ordering _(Specialized Skill)_
- Inductive Reasoning _(Common Skill)_
- Depth Perception _(Common Skill)_
- Deductive Reasoning _(Common Skill)_
- Visualization _(Specialized Skill)_

**Tools & technology:**
- Microsoft Excel _(hot technology)_
- Microsoft Office software _(hot technology)_
- Microsoft Outlook _(hot technology)_
- Microsoft Word _(hot technology)_
- CorePark Valet
- Email software
- Payment processing software
- SMS Valet

## AI exposure & outlook

- **AI task-overlap index:** 29th percentile (Low) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 24th percentile (Low) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 23rd percentile (Low) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 45th percentile (Moderate) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 74th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** no — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** 3.0% growth (About average); 18.5k annual openings; 135.7k → 139.8k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $34,600; 134,650 employed.

## How people actually use AI here

Anthropic Economic Index — measured AI conversations mapped to this occupation's tasks:

- **Automation vs augmentation:** 42% automation, 41% augmentation (usage-weighted).
- **Autonomy median:** 4.0 (higher = AI acts more independently).
- **Dominant collaboration mode:** directive.

**Tasks most handed to AI here:**
- Provide customer assistance and information, such as giving directions or handling wheelchairs. _(0.9% of measured AI use; directive)_

**Example prompts (honest phrasings of the tasks above — starting points, not endorsed instructions):**
- Help me provide customer assistance and information, such as giving directions or handling wheelchairs.

## Sources

- **O*NET** (30.3) — U.S. Department of Labor / National Center for O*NET Development. https://www.onetcenter.org/database.html
- **BLS Occupational Employment and Wage Statistics (OEWS)** (May 2024) — U.S. Bureau of Labor Statistics. https://www.bls.gov/oes/
- **BLS Employment Projections** (2024–2034) — U.S. Bureau of Labor Statistics. https://www.bls.gov/emp/
- **Anthropic Economic Index** (v4 (2026-01-15) + v2 (2025-03-27)) — Anthropic. https://www.anthropic.com/economic-index
- **Microsoft “Working with AI”** (working-with-ai) — Microsoft Research. https://www.microsoft.com/en-us/research/
- **“GPTs are GPTs” (Eloundou et al.)** (arXiv 2303.10130) — OpenAI / academic. https://arxiv.org/abs/2303.10130
- **AI Occupational Exposure (AIOE)** (Felten, Raj & Seamans) — academic. https://github.com/AIOE-Data/AIOE
- **Frey & Osborne (2013)** (frey-osborne-automation) — academic. https://www.oxfordmartin.ox.ac.uk/publications/the-future-of-employment/
- **Dingel & Neiman (2020)** (dingel-neiman-workathome) — academic. https://github.com/jdingel/DingelNeiman-workathome

---
_Generated from Singulariki's joined dataset; data snapshot 2026-06-02T21:00:32.945303+00:00. https://singulariki.com/roles/role-53-6021-00_