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Skincare Specialists

Occupation · SOC 39-5094.00

Provide skincare treatments to face and body to enhance an individual's appearance. Includes electrologists and laser hair removal specialists.

Also called: Aesthetician · Esthetician · Medical Esthetician · Skincare Specialist · Clinical Esthetician · Electrologist · Facialist · Skin Therapist · Skincare Therapist · Spa Technician (Spa Tech) · Aesthetic RN Injector (Aesthetic Registered Nurse Injector) · Beautician

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-39-5094-00/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.

Often handed to AI

Task areas most often handled directively in observed AI conversations — candidates to delegate with light review.

  • Advise clients about colors and types of makeup and instruct them in makeup application techniques. · 0.5%
See how AI is used here →

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.

  • Determine which products or colors will improve clients' skin quality and appearance. · 93.9% need a human
  • Advise clients about colors and types of makeup and instruct them in makeup application techniques. · 87.5% need a human
See the boundary tasks →

31st-percentile task overlap — yet about 14,500 openings a year (+6.7% projected, BLS) . 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.) Moderate 41st -0.3
LLM task exposure, γ (OpenAI / Eloundou) Moderate 35th 0.3
AI assistant applicability (Microsoft) Low 24th 0.1

OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.1), with simple added tooling (β 0.2), and including AI-powered software (γ 0.3). 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 0.3 · 39th 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.

Stay abreast of latest industry trends, products, research, and treatments. 0.6%
Determine which products or colors will improve clients' skin quality and appearance. 0.2%

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 · +6.7% by 2034
Projected annual openings 14,500
Employment 2024 → 2034 97,400 → 103,900

“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.

Most common way people use AI here Directive · AI does it; you give the instruction
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
Advise clients about colors and types of makeup and instruct them in makeup application techniques. Directive 0.5%
Determine which products or colors will improve clients' skin quality and appearance. — 0.3%

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.

Determine which products or colors will improve clients' skin quality and appearance. 93.9%
Advise clients about colors and types of makeup and instruct them in makeup application techniques. 87.5%

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 advise clients about colors and types of makeup and instruct them in makeup application techniques.

    From: Advise clients about colors and types of makeup and instruct them in makeup application techniques. · 0.5% of measured AI use · directive

  • Help me determine which products or colors will improve clients' skin quality and appearance.

    From: Determine which products or colors will improve clients' skin quality and appearance. · 0.3% of measured AI use

Tasks

All 18 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.

Work activities

Knowledge, skills & abilities

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

Knowledge

Customer and Personal Service 4.3
Sales and Marketing 3.7
Administration and Management 3.6
Education and Training 3.6
English Language 3.5
Administrative 3.4
Communications and Media 3.1

Abilities

Oral Comprehension 3.9
Oral Expression 3.9
Near Vision 3.9
Deductive Reasoning 3.5
Speech Recognition 3.5
Speech Clarity 3.5
Written Comprehension 3.3
Problem Sensitivity 3.3
Arm-Hand Steadiness 3.3
Selective Attention 3.1
Finger Dexterity 3.1
Written Expression 3.0
Fluency of Ideas 3.0
Inductive Reasoning 3.0
Information Ordering 3.0
Category Flexibility 3.0
Manual Dexterity 3.0
Originality 2.9
Control Precision 2.9

Essential skills

Speaking 3.8
Active Listening 3.5
Monitoring 3.3
Reading Comprehension 3.1
Critical Thinking 3.1
Active Learning 3.0
Writing 2.9

Transferable skills

Service Orientation 3.6
Social Perceptiveness 3.1
Coordination 3.0
Complex Problem Solving 3.0
Time Management 3.0
Instructing 2.9
Judgment and Decision Making 2.9

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
Microsoft Excel Spreadsheet software Hot technology
Microsoft Office software Office suite software Hot technology
Microsoft PowerPoint Presentation software Hot technology
Microsoft Word Word processing software Hot technology
Spa management software Data base user interface and query 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.

Face-to-Face Discussions with Individuals and Within Teams 5.0
Contact With Others 5.0
Indoors, Environmentally Controlled 5.0
Frequency of Decision Making 4.7
Physical Proximity 4.7
Deal With External Customers or the Public in General 4.6
Freedom to Make Decisions 4.3
Spend Time Using Your Hands to Handle, Control, or Feel Objects, Tools, or Controls 4.2
Telephone Conversations 4.1
Impact of Decisions on Co-workers or Company Results 4.0
Determine Tasks, Priorities and Goals 4.0
Work With or Contribute to a Work Group or Team 3.9
Wear Common Protective or Safety Equipment such as Safety Shoes, Glasses, Gloves, Hearing Protection, Hard Hats, or Life Jackets 3.9
Importance of Being Exact or Accurate 3.9
Exposed to Disease or Infections 3.6
Level of Competition 3.6
Spend Time Making Repetitive Motions 3.5
Coordinate or Lead Others in Accomplishing Work Activities 3.3
E-Mail 3.3
Health and Safety of Other Workers 3.3
Spend Time Standing 3.2
Importance of Repeating Same Tasks 3.1
Spend Time Sitting 2.8
Work Outcomes and Results of Other Workers 2.6
Spend Time Bending or Twisting Your Body 2.6
Written Letters and Memos 2.6
Time Pressure 2.6
Exposed to Contaminants 2.5
Consequence of Error 2.5
Conflict Situations 2.5
Dealing With Unpleasant, Angry, or Discourteous People 2.4
Exposed to Cramped Work Space, Awkward Positions 2.2
Pace Determined by Speed of Equipment 2.2
Exposed to Minor Burns, Cuts, Bites, or Stings 2.1
Exposed to Hazardous Conditions 2.1
Spend Time Walking or Running 1.9
Spend Time Kneeling, Crouching, Stooping, or Crawling 1.9
Wear Specialized Protective or Safety Equipment such as Breathing Apparatus, Safety Harness, Full Protection Suits, or Radiation Protection 1.8
Public Speaking 1.7
Exposed to Extremely Bright or Inadequate Lighting Conditions 1.7

How to get in

Job zone
Zone 3 — Job Zone Three: Medium Preparation Needed
Education
Most occupations in this zone require training in vocational schools, related on-the-job experience, or an associate's degree.
Typical entry-level education
Postsecondary nondegree award · BLS, the typical path — not a requirement
Related experience
Previous work-related skill, knowledge, or experience is required for these occupations. For example, an electrician must have completed three or four years of apprenticeship or several years of vocational training, and often must have passed a licensing exam, in order to perform the job.
Preparation level
SVP (6.0 to < 7.0) — 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.

High School Diploma 39.1%
Post-Secondary Certificate 30.2%
Some College Courses 8.8%
Post-Doctoral Training 2.6%

Interests & work styles

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

Interest areas

Personal Service 5.8
Health Care Service 3.6
Teaching/Education 2.9
Sales 2.6
Physical/Manual Labor 2.5
Professional Advising 2.3
Marketing/Advertising 2.2

Career interests (Holland / RIASEC)

Realistic 5.5
Social 4.2
Conventional 3.4
Enterprising 3.1
Artistic 3.0

Work styles

Dependability 4.0
Attention to Detail 3.0
Social Orientation 2.2
Empathy 2.2

Wages & employment

U.S. · annual wages (BLS OEWS)

$27k10th$34k25th$42kMedian$56k75th$77k90th
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.
97k2024104k2034 (proj.)+6.7% · 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 $27,160
25th percentile $34,130
Median (50th) $41,560
75th percentile $55,860
90th percentile $77,330
People employed 70,240

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 51,870 $38,570
Health Care and Social Assistance · Sector 11,410 $47,300
Retail Trade · Sector 3,190 $38,830
Accommodation and Food Services · Sector 2,130 $39,040
Arts, Entertainment, and Recreation · Sector 740 $36,260
Fitness and Recreational Sports Centers · National industry 550 $37,390
Wholesale Trade · Sector 470 $54,500
Administrative and Support and Waste Management and Remediation Services · Sector 330 $62,400
Casino Hotels · National industry 240 $29,850
Offices of Optometrists · National industry 60 $42,010
Educational Services · Sector 50 $53,360
Management of Companies and Enterprises · Sector — $63,440

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 25.72× 51,870
Fitness and Recreational Sports Centers · National industry 1.92× 550
Casino Hotels · National industry 1.56× 240
Health Care and Social Assistance · Sector 1.08× 11,410
Arts, Entertainment, and Recreation · Sector 0.61× 740
Retail Trade · Sector 0.45× 3,190
Accommodation and Food Services · Sector 0.33× 2,130
Wholesale Trade · Sector 0.17× 470

Part of the Healthcare & Human Services career cluster.

Exposure quadrant: AI task-overlap percentile vs Median pay Skincare Specialists sits at the 31st percentile of AI task-overlap and the 16th 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 Skincare Specialists Massage Therapists Surgical Assistants Surgical Technologists Hairdressers, Hairstylists, and Cosmetologists Barbers Dental Assistants 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 Skincare Specialists — 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.

Adjacent roles

Occupations O*NET rates as related — the nearby moves on the map.

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

Skincare Specialists show 31st-percentile AI task overlap — and about 14,500 annual U.S. openings

  • Skincare Specialists rank in the 31st 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 14,500 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 (+6.7%) from 2024 to 2034.BLS Employment Projections 2024–34
  • Median annual pay is $41,560, across about 70,240 U.S. workers.BLS OEWS (May 2024)
Copy the whole kit
Skincare Specialists show 31st-percentile AI task overlap — and about 14,500 annual U.S. openings

• Skincare Specialists rank in the 31st 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 14,500 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 (+6.7%) from 2024 to 2034. (BLS Employment Projections 2024–34)
• Median annual pay is $41,560, across about 70,240 U.S. workers. (BLS OEWS (May 2024))

Source: Singulariki — "Skincare Specialists". https://singulariki.com/roles/role-39-5094-00
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. "Skincare Specialists." 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-39-5094-00

APA

Singulariki. (2026). Skincare Specialists. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-39-5094-00

BibTeX 
@misc{singulariki-role-39-5094-00,
  title  = {Skincare Specialists},
  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-39-5094-00}
}

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

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