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Shampooers

Occupation · SOC 39-5093.00

Shampoo and rinse customers' hair.

Also called: Shampoo Assistant · Shampoo Technician · Shampooer · Stylist Assistant · Hair Assistant · Shampoo Person · Hair Shampoo Assistant · Salon Shampoo Assistant · Scalp Treatment Operator · Scalp Treatment Specialist · Shampoo Specialist · Shampooist

Job family: Personal Care and Service Occupations

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Download .md

A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch /roles/role-39-5093-00/context.md directly.

AI work map

A fast read on where AI already shows up in this occupation, where it stays a copilot, where humans remain in the loop, and what the labor market is doing. Built from observed Claude.ai conversations mapped to O*NET tasks and from published research — measures of usage and exposure, not advice or predictions that the job is going away.

Use as a copilot

Task areas where people work with AI — iterating, learning, or checking — staying in the loop rather than handing the task off.

  • Treat scalp conditions and hair loss, using specialized lotions, shampoos, or equipment such as infrared lamps or vibrating equipment. · 0.7%
See collaboration patterns →

Keep a human in the loop

Task areas where a human was still judged necessary in a large share of observed conversations — not a safety ruling, an observed-need signal.

  • Treat scalp conditions and hair loss, using specialized lotions, shampoos, or equipment such as infrared lamps or vibrating equipment. · 95.9% need a human
See the boundary tasks →

20th-percentile task overlap — yet about 2,700 openings a year (+5.5% projected, BLS), and observed AI use leans 5890% copilot, not hand-off (AEI) . What exposure means →

AI & job outlook

What today's research says about this occupation's exposure to AI, how AI is actually being used in it, and where employment is headed. These are positions within published studies — measures of exposure and usage, not predictions that this job will disappear.

Exposure to current AI

Each study uses its own scale, so the raw scores are not comparable across rows — the percentile (this job's rank among all U.S. occupations with data) is the comparable figure, and sizes the bars.

Measure Rank vs all occupations Percentile Score
Overall AI exposure (Felten et al.) Low 21st -0.9
LLM task exposure, γ (OpenAI / Eloundou) Low 19th 0.1
AI assistant applicability (Microsoft) Low 27th 0.1

OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.1), with simple added tooling (β 0.1), and including AI-powered software (γ 0.1). Higher means more of the job's tasks could be done at least twice as fast — not that they will be automated away.

This job mostly cannot be done remotely (Dingel–Neiman) — its hands-on tasks sit outside what software-based AI reaches.

Historical automation estimate (2013)

A pre-LLM (2013) estimate of how automatable this job is by computerization and robotics. Shown for historical context only — it is not part of any current AI ranking.

Frey–Osborne probability 0.8 · 64th percentile among occupations · Moderate

How AI is actually used in this job

Among measured AI assistant conversations mapped to this occupation (Anthropic Economic Index, 2026-01-15), these task types came up most. These are shares of observed AI conversations — not shares of the job, of worker time, or of what could be automated.

Treat scalp conditions and hair loss, using specialized lotions, shampoos, or equipment such as infrared lamps or vibrating equipment. 0.6%

Job outlook

Independent U.S. Bureau of Labor Statistics employment projection for 2024–2034 — a labor-market forecast, not an AI-impact forecast.

Outlook About average · +5.5% by 2034
Projected annual openings 2,700
Employment 2024 → 2034 18,500 → 19,600

“Annual openings” counts new jobs plus replacements for workers who leave the occupation, so it can be large even when growth is modest.

Where this work sits on the global GenAI gradient

The ILO's 2025 global study scores generative-AI exposure on the international ISCO-08 occupation system, not US SOC. Bridged through the published (and approximate, many-to-many) IBS O*NET-SOC ↔ ISCO-08 crosswalk, this US occupation corresponds to the international occupation below. Exposure here means how much of the work's tasks today's AI can attempt — task overlap, not automation, adoption, or jobs lost.

18% mean task exposure (2025)
29th percentile of 427 placed occupations
−4 pts shift 2023 → 2025
International occupation (ISCO-08) Task exposure (2025) Most tasks fall in
Beauticians and Related Workers · 5142 18% Not exposed

Read the whole six-band gradient on the GenAI exposure gradient page. The crosswalk is approximate: a US occupation can map to several international ones, and the ILO scores describe the international occupation, not this exact US role.

Working with AI in this job

How people actually apply AI to this occupation's tasks, from Claude.ai (Free and Pro) conversations in the Anthropic Economic Index, 2026-01-15. This is one AI assistant's consumer sample — not all AI, not the whole workforce. Autonomy and the collaboration mix are model-rated estimates; figures below the sample floor are hidden.

Augmentation vs. automation 58.9% working with AI · — handed to AI
Most common way people use AI here Learning · you ask AI to explain or teach
Typical AI autonomy 4.0 / 5 · higher = AI acts more independently

What people delegate to AI

The role's most common tasks in AI conversations, each tagged with how people work with the AI on it. “Usage” is the share of observed conversations, not of the job.

Task How Usage
Treat scalp conditions and hair loss, using specialized lotions, shampoos, or equipment such as infrared lamps or vibrating equipment. Learning 0.7%

Where a human is still needed

Tasks where the model most often judged that a person remained necessary — a useful read on the current boundary, not a guarantee.

Treat scalp conditions and hair loss, using specialized lotions, shampoos, or equipment such as infrared lamps or vibrating equipment. 95.9%

What people most often hand AI here

Example prompts phrased from the tasks people most often delegate to AI in this occupation (Anthropic Economic Index). Each shows the underlying measured task and its share of observed AI use. They are suggested phrasings of real tasks — 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.

    From: 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

Tasks

All 4 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.

Emerging tasks

Newer responsibilities O*NET has flagged as growing for this occupation.

  • 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.

Work activities

Knowledge, skills & abilities

O*NET importance rating, from 1 (not important) to 5 (extremely important).

Knowledge

Customer and Personal Service 4.2
English Language 4.1
Sales and Marketing 3.2
Public Safety and Security 2.7
Chemistry 2.7
Education and Training 2.7
Psychology 2.6

Abilities

Oral Comprehension 3.6
Oral Expression 3.4
Speech Clarity 3.3
Arm-Hand Steadiness 3.1
Near Vision 3.1
Manual Dexterity 3.0
Finger Dexterity 2.9
Speech Recognition 2.9
Problem Sensitivity 2.8
Deductive Reasoning 2.8
Selective Attention 2.8
Trunk Strength 2.8
Written Comprehension 2.6
Inductive Reasoning 2.6
Information Ordering 2.6
Written Expression 2.5
Category Flexibility 2.5
Time Sharing 2.5
Control Precision 2.4
Dynamic Strength 2.4
Extent Flexibility 2.4

Essential skills

Speaking 3.3
Active Listening 3.1
Monitoring 2.8
Reading Comprehension 2.5
Critical Thinking 2.5
Writing 2.4

Transferable skills

Service Orientation 3.0
Social Perceptiveness 2.8
Coordination 2.8
Judgment and Decision Making 2.5
Time Management 2.5
Persuasion 2.4

Skills in demand

Skills employers ask for in job postings for this occupation (Lightcast), with whether each is a common or specialized skill.

Tools & technology

Example Category
Facebook Web page creation and editing software Hot technology
Appointment scheduling software Calendar and scheduling software
Email software Electronic mail software
Inventory tracking software Inventory management software
Web browser software Internet browser software

Work context

How characteristic each condition is of the job, on O*NET's 1–5 context scale (higher = more present in day-to-day work). Each condition links to how it varies across all occupations.

Indoors, Environmentally Controlled 5.0
Contact With Others 4.9
Spend Time Standing 4.8
Importance of Being Exact or Accurate 4.7
Physical Proximity 4.6
Spend Time Using Your Hands to Handle, Control, or Feel Objects, Tools, or Controls 4.6
Face-to-Face Discussions with Individuals and Within Teams 4.5
Work With or Contribute to a Work Group or Team 4.5
Spend Time Making Repetitive Motions 4.4
Impact of Decisions on Co-workers or Company Results 4.4
Frequency of Decision Making 4.1
Deal With External Customers or the Public in General 4.0
Telephone Conversations 3.9
Freedom to Make Decisions 3.6
Determine Tasks, Priorities and Goals 3.4
Coordinate or Lead Others in Accomplishing Work Activities 3.4
Time Pressure 3.3
Spend Time Walking or Running 3.2
Wear Common Protective or Safety Equipment such as Safety Shoes, Glasses, Gloves, Hearing Protection, Hard Hats, or Life Jackets 3.0
Health and Safety of Other Workers 3.0
Dealing With Unpleasant, Angry, or Discourteous People 2.9
Work Outcomes and Results of Other Workers 2.8
Level of Competition 2.7
Spend Time Bending or Twisting Your Body 2.7
Importance of Repeating Same Tasks 2.5
Exposed to Contaminants 2.5
Written Letters and Memos 2.3
Conflict Situations 1.9
Consequence of Error 1.8
Degree of Automation 1.8
Pace Determined by Speed of Equipment 1.8
Exposed to Cramped Work Space, Awkward Positions 1.8
Spend Time Keeping or Regaining Balance 1.6
Exposed to Sounds, Noise Levels that are Distracting or Uncomfortable 1.5
Indoors, Not Environmentally Controlled 1.5
Spend Time Sitting 1.5
Exposed to Minor Burns, Cuts, Bites, or Stings 1.4
Spend Time Kneeling, Crouching, Stooping, or Crawling 1.4
Exposed to Hazardous Conditions 1.4
Exposed to Disease or Infections 1.4

How to get in

Job zone
Zone 2 — Job Zone 1-2: Very Little to Some Preparation Needed
Education
Usually requires a high school diploma or GED, though some occupations may not.
Typical entry-level education
No formal educational credential · BLS, the typical path — not a requirement
Related experience
Some occupations may need little or no previous experience; others require several months to a year of experience. For example, landscaping and groundskeeping workers might require very little training or previous experience, while agricultural equipment operators can benefit from on-the job training.
Preparation level
SVP (Below 6.0) — total schooling plus on-the-job experience.

What to study: Culinary, Entertainment, and Personal Services . Fields of study crosswalked to this occupation (NCES CIP–SOC), not a requirement.

Education of current workers

Share of people in this occupation at each level of education.

Post-Secondary Certificate 67.5%
High School Diploma 18.4%
Less than a High School Diploma 13.1%
Some College Courses 1.1%

Interests & work styles

The interests and personal qualities O*NET associates with people who do this work.

Career interests (Holland / RIASEC)

Realistic 5.5
Social 3.8
Conventional 3.4
Enterprising 2.5
Artistic 1.6

Interest areas

Personal Service 5.1
Physical/Manual Labor 2.5
Health Care Service 2.2
Social Service 1.8
Sales 1.6
Teaching/Education 1.5

Work styles

Cooperation 1.8
Empathy 1.8
Social Orientation 1.8
Dependability 1.8
Optimism 1.5

Wages & employment

U.S. · annual wages (BLS OEWS)

$23k10th$27k25th$31kMedian$36k75th$36k90th
Annual wages by percentile — U.S. (BLS OEWS). The light band spans the 10th–90th percentile; the darker band is the middle half (25th–75th); the line is the median.
19k202420k2034 (proj.)+5.5% · About average
Projected U.S. employment, 2024–2034 (BLS Employment Projections). A labor-market forecast for the occupation, not an AI-impact forecast.
10th percentile $22,880
25th percentile $27,390
Median (50th) $31,470
75th percentile $35,610
90th percentile $35,970
People employed 8,890

Industries that employ this occupation

Where these workers are employed, by number of jobs (national, BLS OEWS). Pay shown is the occupation's national median, not industry-specific.

Industry Workers National median pay
Other Services (except Public Administration) · Sector 8,740 $31,470
Administrative and Support and Waste Management and Remediation Services · Sector $33,340

Where this work is most concentrated

Industries where this occupation is far more common than in the economy as a whole. The location quotient is how many times more concentrated it is here (a value of 5 means five times its economy-wide share).

Industry Concentration Workers
Other Services (except Public Administration) · Sector 34.25× 8,740

Part of the Healthcare & Human Services career cluster.

Exposure quadrant: AI task-overlap percentile vs Median pay Shampooers sits at the 20th percentile of AI task-overlap and the 1st percentile of median pay, placed here against 10 adjacent occupations on the same two axes. Lower overlap · higher pay Higher overlap · higher pay Higher overlap · lower pay Lower overlap · lower pay Shampooers Massage Therapists Surgical Assistants Nursing Assistants Skincare Specialists Makeup Artists, Theatrical and Performance AI task-overlap percentile → ↑ Median pay
AI task-overlap percentile (horizontal) vs. median-pay percentile (vertical), across all scored occupations. This occupation is highlighted; related occupations are plotted alongside it. Overlap measures shared tasks with AI, not automation.

Side-by-side comparisons place two occupations’ pay, preparation, skills, and AI exposure on the same page — same data, same scale, no forecast.

What you can do with this

Options the data surfaces for Shampooers — not advice or a forecast. Each is a real cross-link you can follow into the evidence.

Skills that travel

Capabilities this work builds that are used across many other occupations.

Paths in

How people typically prepare for this work.

Zoom out

On the global GenAI exposure gradient this work sits around the 29th percentile of 427 international occupations.

Write a report on thisheadline · factoids · citation

Shampooers show 20th-percentile AI task overlap — and about 2,700 annual U.S. openings

  • Shampooers rank in the 20th percentile (Low band) for AI task overlap across U.S. occupations — a measure of how much of the work today's AI can attempt, not how much is automated.Eloundou et al. (GPTs are GPTs) + Felten AIOE
  • The occupation is projected to see about 2,700 U.S. job openings per year (2024–34), counting growth and replacement — a labor-demand projection made independently of AI.BLS Employment Projections 2024–34
  • BLS projects employment to be about average (+5.5%) from 2024 to 2034.BLS Employment Projections 2024–34
  • Median annual pay is $31,470, across about 8,890 U.S. workers.BLS OEWS (May 2024)
  • Of the AI use actually observed for this work, 59% looks like augmentation (drafting, iterating, checking) rather than hands-off automation — from a Claude.ai usage sample, not a census.2026-01-15-v4-plus-2025-03-27-v2
Copy the whole kit
Shampooers show 20th-percentile AI task overlap — and about 2,700 annual U.S. openings

• Shampooers rank in the 20th percentile (Low band) for AI task overlap across U.S. occupations — a measure of how much of the work today's AI can attempt, not how much is automated. (Eloundou et al. (GPTs are GPTs) + Felten AIOE)
• The occupation is projected to see about 2,700 U.S. job openings per year (2024–34), counting growth and replacement — a labor-demand projection made independently of AI. (BLS Employment Projections 2024–34)
• BLS projects employment to be about average (+5.5%) from 2024 to 2034. (BLS Employment Projections 2024–34)
• Median annual pay is $31,470, across about 8,890 U.S. workers. (BLS OEWS (May 2024))
• Of the AI use actually observed for this work, 59% looks like augmentation (drafting, iterating, checking) rather than hands-off automation — from a Claude.ai usage sample, not a census. (2026-01-15-v4-plus-2025-03-27-v2)

Source: Singulariki — "Shampooers". https://singulariki.com/roles/role-39-5093-00
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.

AssetsShare imageMethodology & sourcesPress & newsroomThe newsroom

Every line is built only from figures this page already shows and cites. AI task overlap means what today's AI can attempt — not automation, job loss, or a forecast.

Sources for this page

Every figure above traces to a named public dataset and the exact release below — not hand-written opinion. See the full methodology for what each measure does and does not mean.

Data compiled June 2, 2026. Figures are estimates, not advice.

Cite this page
Plain

Singulariki. "Shampooers." Singulariki: a source-backed encyclopedia of work. Built from O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026. https://singulariki.com/roles/role-39-5093-00

APA

Singulariki. (2026). Shampooers. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-39-5093-00

BibTeX
@misc{singulariki-role-39-5093-00,
  title  = {Shampooers},
  author = {{Singulariki}},
  year   = {2026},
  note   = {O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026},
  url    = {https://singulariki.com/roles/role-39-5093-00}
}

Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.

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