# Shampooers

> Shampoo and rinse customers' hair.

- **SOC code:** 39-5093.00
- **Canonical URL:** https://singulariki.com/roles/role-39-5093-00
- **Also known as:** Shampoo Assistant, Shampoo Technician, Shampooer, Stylist Assistant, Hair Assistant, Shampoo Person, Hair Shampoo Assistant, Salon Shampoo Assistant
- **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):
- Massage, shampoo, and condition patron's hair and scalp to clean them and remove excess oil.
- Advise patrons with chronic or potentially contagious scalp conditions to seek medical treatment.
- Maintain treatment records.
- Treat scalp conditions and hair loss, using specialized lotions, shampoos, or equipment such as infrared lamps or vibrating equipment.

**Emerging tasks** (O*NET):
- Assist hair stylists with chemical services, such as neutralizing perms and applying hair color.
- Launder and fold the towels that are used for drying customers' hair.
- Refill and stock work stations with supplies, such as shampoos and conditioners.
- Rinse out hair color or permanent solutions from customers' hair.
- Sweep hair from the salon floor.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Customer and Personal Service _(knowledge)_
- English Language _(knowledge)_
- Oral Comprehension _(ability)_
- Oral Expression _(ability)_
- Speaking _(essential_skill)_
- Speech Clarity _(ability)_
- Sales and Marketing _(knowledge)_
- Active Listening _(essential_skill)_
- Arm-Hand Steadiness _(ability)_
- Near Vision _(ability)_
- Service Orientation _(transferable_skill)_
- Manual Dexterity _(ability)_

**Skills in demand:**
- English Language _(Common Skill)_
- Active Listening _(Common Skill)_
- Facebook _(Specialized Skill)_
- Speech Recognition _(Specialized Skill)_
- Finger Dexterity _(Common Skill)_
- Social Perceptiveness _(Common Skill)_
- Deductive Reasoning _(Common Skill)_
- Chemistry _(Specialized Skill)_
- Information Ordering _(Specialized Skill)_
- Inductive Reasoning _(Common Skill)_
- Psychology _(Specialized Skill)_
- Time Management _(Common Skill)_

**Tools & technology:**
- Facebook _(hot technology)_
- Appointment scheduling software
- Email software
- Inventory tracking software
- Web browser software

## AI exposure & outlook

- **AI task-overlap index:** 20th percentile (Low) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 21st percentile (Low) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 19th percentile (Low) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 27th percentile (Low) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 64th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** no — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** 5.5% growth (About average); 2.7k annual openings; 18.5k → 19.6k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $31,470; 8,890 employed.

## How people actually use AI here

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

- **Automation vs augmentation:** — automation, 59% augmentation (usage-weighted).
- **Autonomy median:** 4.0 (higher = AI acts more independently).
- **Dominant collaboration mode:** learning.

**Tasks most handed to AI here:**
- Treat scalp conditions and hair loss, using specialized lotions, shampoos, or equipment such as infrared lamps or vibrating equipment. _(0.7% of measured AI use; learning)_

**Example prompts (honest phrasings of the tasks above — starting points, not endorsed instructions):**
- Help me treat scalp conditions and hair loss, using specialized lotions, shampoos, or equipment such as infrared lamps or vibrating equipment.

## 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

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_Generated from Singulariki's joined dataset; data snapshot 2026-06-02T21:00:32.945303+00:00. https://singulariki.com/roles/role-39-5093-00_