Occupation · SOC 25-3021.00
Teach or instruct individuals or groups for the primary purpose of self-enrichment or recreation, rather than for an occupational objective, educational attainment, competition, or fitness.
Also called: Dance Instructor · Instructor · Martial Arts Instructor · Teacher · Art Teacher · Dance Teacher · Driving Instructor · Flight Instructor · Music Instructor · Piano Teacher · Acting Teacher · Adventure Education Teacher
Job family: Educational Instruction and Library Occupations
A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch
/roles/role-25-3021-00/context.md directly.
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.
Task areas most often handled directively in observed AI conversations — candidates to delegate with light review.
Task areas where people work with AI — iterating, learning, or checking — staying in the loop rather than handing the task off.
Task areas where a human was still judged necessary in a large share of observed conversations — not a safety ruling, an observed-need signal.
The capabilities O*NET rates most important for this occupation — the human ground the work is built on.
See all skills →Independent published positions, read together — not a forecast.
58th-percentile task overlap — yet about 51,400 openings a year (+3.7% projected, BLS), and observed AI use leans 6835% copilot, not hand-off (AEI) . What exposure means →
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.
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 | 61st | 0.5 | |
| LLM task exposure, γ (OpenAI / Eloundou) Moderate | 47th | 0.6 | |
| AI assistant applicability (Microsoft) High | 69th | 0.2 |
OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.2), with simple added tooling (β 0.4), and including AI-powered software (γ 0.6). Higher means more of the job's tasks could be done at least twice as fast — not that they will be automated away.
Most of this job's tasks can be done remotely (Dingel–Neiman), which tends to track with higher digital and AI exposure.
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 0.1 · 30th percentile among occupations · Low
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.
| Adapt teaching methods and instructional materials to meet students' varying needs and interests. | 12.9% | |
| Write instructional articles on designated subjects. | 8.7% | |
| Review instructional content, methods, and student evaluations to assess strengths and weaknesses, and to develop recommendations for course revision, development, or elimination. | 8.4% | |
| Use computers, audio-visual aids, and other equipment and materials to supplement presentations. | 3.1% | |
| Prepare and implement remedial programs for students requiring extra help. | 1.9% | |
| Instruct students individually and in groups, using various teaching methods, such as lectures, discussions, and demonstrations. | 1.6% |
Independent U.S. Bureau of Labor Statistics employment projection for 2024–2034 — a labor-market forecast, not an AI-impact forecast.
| Outlook | About average · +3.7% by 2034 |
| Projected annual openings | 51,400 |
| Employment 2024 → 2034 | 417,500 → 433,000 |
“Annual openings” counts new jobs plus replacements for workers who leave the occupation, so it can be large even when growth is modest.
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 6 occupations below. Exposure here means how much of the work's tasks today's AI can attempt — task overlap, not automation, adoption, or jobs lost.
| International occupation (ISCO-08) | Task exposure (2025) | Most tasks fall in |
|---|---|---|
| Sports Coaches, Instructors and Officials · 3422 | 37% | Minimal |
| Other Music Teachers · 2354 | 35% | Minimal |
| Other Arts Teachers · 2355 | 35% | Minimal |
| Other Language Teachers · 2353 | 34% | Minimal |
| Fitness and Recreation Instructors and Programme Leaders · 3423 | 25% | Not exposed |
| Driving Instructors · 5165 | 21% | 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.
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 | 68.3% working with AI · 28.6% 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 |
| Used for work (vs. personal / coursework) | 26.3% |
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 |
|---|---|---|
| Conduct classes, workshops, and demonstrations, and provide individual instruction to teach topics and skills such as cooking, dancing, writing, physical fitness, photography, personal finance, and flying. | Learning | 23.9% |
| Review instructional content, methods, and student evaluations to assess strengths and weaknesses, and to develop recommendations for course revision, development, or elimination. | Iteration | 7.8% |
| Use computers, audio-visual aids, and other equipment and materials to supplement presentations. | Learning | 5.7% |
| Write instructional articles on designated subjects. | Directive | 2.6% |
| Prepare materials and classrooms for class activities. | Directive | 2.2% |
| Plan and conduct activities for a balanced program of instruction, demonstration, and work time that provides students with opportunities to observe, question, and investigate. | Directive | 2.0% |
| Adapt teaching methods and instructional materials to meet students' varying needs and interests. | Iteration | 1.5% |
| Prepare instructional program objectives, outlines, and lesson plans. | Directive | 1.0% |
Tasks where the model most often judged that a person remained necessary — a useful read on the current boundary, not a guarantee.
| Prepare instructional program objectives, outlines, and lesson plans. | 99.0% | |
| Assign and grade class work and homework. | 98.1% | |
| Write instructional articles on designated subjects. | 97.3% | |
| Use computers, audio-visual aids, and other equipment and materials to supplement presentations. | 97.0% | |
| Prepare materials and classrooms for class activities. | 93.2% | |
| Review instructional content, methods, and student evaluations to assess strengths and weaknesses, and to develop recommendations for course revision, development, or elimination. | 92.8% |
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 conduct classes, workshops, and demonstrations, and provide individual instruction to teach topics and skills such as cooking, dancing, writing, physical fitness, photography, personal finance, and flying. From: Conduct classes, workshops, and demonstrations, and provide individual instruction to teach topics and skills such as cooking, dancing, writing, physical fitness, photography, personal finance, and flying. · 23.9% of measured AI use · learning
Help me review instructional content, methods, and student evaluations to assess strengths and weaknesses, and to develop recommendations for course revision, development, or elimination. From: Review instructional content, methods, and student evaluations to assess strengths and weaknesses, and to develop recommendations for course revision, development, or elimination. · 7.8% of measured AI use · task iteration
Help me use computers, audio-visual aids, and other equipment and materials to supplement presentations. From: Use computers, audio-visual aids, and other equipment and materials to supplement presentations. · 5.7% of measured AI use · learning
Help me write instructional articles on designated subjects. From: Write instructional articles on designated subjects. · 2.6% of measured AI use · directive
All 30 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.
O*NET importance rating, from 1 (not important) to 5 (extremely important).
| Education and Training | 4.3 | |
| Customer and Personal Service | 3.5 | |
| English Language | 3.3 | |
| Sociology and Anthropology | 2.5 |
| Oral Expression | 4.0 | |
| Oral Comprehension | 3.9 | |
| Speech Clarity | 3.6 | |
| Speech Recognition | 3.3 | |
| Written Comprehension | 3.1 | |
| Written Expression | 3.1 | |
| Deductive Reasoning | 3.1 | |
| Information Ordering | 3.1 | |
| Near Vision | 3.1 | |
| Fluency of Ideas | 3.0 | |
| Originality | 3.0 | |
| Problem Sensitivity | 3.0 | |
| Inductive Reasoning | 3.0 | |
| Category Flexibility | 3.0 | |
| Flexibility of Closure | 2.6 | |
| Selective Attention | 2.6 | |
| Memorization | 2.5 | |
| Visualization | 2.5 | |
| Far Vision | 2.5 |
| Speaking | 3.6 | |
| Active Listening | 3.4 | |
| Learning Strategies | 3.4 | |
| Reading Comprehension | 3.1 | |
| Critical Thinking | 3.1 | |
| Active Learning | 3.1 | |
| Monitoring | 3.1 | |
| Writing | 3.0 |
| Instructing | 3.4 | |
| Social Perceptiveness | 3.1 | |
| Coordination | 3.0 | |
| Service Orientation | 3.0 | |
| Judgment and Decision Making | 3.0 | |
| Complex Problem Solving | 2.9 | |
| Time Management | 2.9 | |
| Persuasion | 2.6 | |
| Management of Personnel Resources | 2.5 |
Skills employers ask for in job postings for this occupation (Lightcast), with whether each is a common or specialized skill.
Showing the top 40 of 45.
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.
What to study: Education , Multi/Interdisciplinary Studies . Fields of study crosswalked to this occupation (NCES CIP–SOC), not a requirement.
Share of people in this occupation at each level of education.
| Post-Secondary Certificate | 18.5% | |
| Bachelor's Degree | 18.1% | |
| High School Diploma | 13.5% | |
| Associate's Degree (or other 2-year degree) | 13.5% | |
| Post-Doctoral Training | 0.8% | |
| Post-Baccalaureate Certificate | 0.7% | |
| Some College Courses | 0.3% |
The interests and personal qualities O*NET associates with people who do this work.
| Social | 7.0 | |
| Artistic | 4.2 | |
| Enterprising | 3.2 | |
| Conventional | 3.1 | |
| Investigative | 3.0 |
| Teaching/Education | 6.5 | |
| Public Speaking | 4.6 | |
| Social Service | 4.0 | |
| Personal Service | 3.9 | |
| Performing Arts | 3.6 | |
| Professional Advising | 3.6 | |
| Humanities | 2.7 | |
| Athletics | 2.6 |
| Dependability | 5.0 | |
| Cooperation | 4.0 | |
| Social Orientation | 3.0 |
U.S. · annual wages (BLS OEWS)
| 10th percentile | $28,980 |
| 25th percentile | $35,410 |
| Median (50th) | $45,590 |
| 75th percentile | $62,180 |
| 90th percentile | $90,780 |
| People employed | 308,520 |
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 |
|---|---|---|
| Educational Services · Sector | 199,990 | $46,240 |
| Arts, Entertainment, and Recreation · Sector | 44,390 | $43,140 |
| Other Services (except Public Administration) · Sector | 22,030 | $45,000 |
| Fitness and Recreational Sports Centers · National industry | 15,260 | $37,340 |
| Health Care and Social Assistance · Sector | 15,050 | $45,940 |
| Retail Trade · Sector | 10,200 | $44,590 |
| Theater Companies and Dinner Theaters · National industry | 3,100 | $75,980 |
| Services for the Elderly and Persons with Disabilities · National industry | 2,210 | $43,650 |
| Sporting Goods Retailers · National industry | 1,890 | $37,820 |
| Accommodation and Food Services · Sector | 1,560 | $40,010 |
| Administrative and Support and Waste Management and Remediation Services · Sector | 1,100 | $52,000 |
| Professional, Scientific, and Technical Services · Sector | 730 | $46,620 |
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 |
|---|---|---|
| Theater Companies and Dinner Theaters · National industry | 21.4× | 3,100 |
| Fitness and Recreational Sports Centers · National industry | 12.1× | 15,260 |
| Arts, Entertainment, and Recreation · Sector | 8.4× | 44,390 |
| Educational Services · Sector | 7.33× | 199,990 |
| Sporting Goods Retailers · National industry | 3.17× | 1,890 |
| Other Services (except Public Administration) · Sector | 2.49× | 22,030 |
| Agriculture, Forestry, Fishing and Hunting · Sector | 0.46× | 390 |
| Services for the Elderly and Persons with Disabilities · National industry | 0.46× | 2,210 |
Part of the Education career cluster.
Side-by-side comparisons place two occupations’ pay, preparation, skills, and AI exposure on the same page — same data, same scale, no forecast.
Options the data surfaces for Self-Enrichment Teachers — not advice or a forecast. Each is a real cross-link you can follow into the evidence.
Capabilities this work builds that are used across many other occupations.
Occupations O*NET rates as related — the nearby moves on the map.
How people typically prepare for this work.
On the global GenAI exposure gradient this work sits around the 61st percentile of 427 international occupations.
Self-Enrichment Teachers show 58th-percentile AI task overlap — and about 51,400 annual U.S. openings
Self-Enrichment Teachers show 58th-percentile AI task overlap — and about 51,400 annual U.S. openings • Self-Enrichment Teachers rank in the 58th percentile (Moderate 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 51,400 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 (+3.7%) from 2024 to 2034. (BLS Employment Projections 2024–34) • Median annual pay is $45,590, across about 308,520 U.S. workers. (BLS OEWS (May 2024)) • Of the AI use actually observed for this work, 68% 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 — "Self-Enrichment Teachers". https://singulariki.com/roles/role-25-3021-00 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.
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.
Singulariki. "Self-Enrichment Teachers." 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-25-3021-00
Singulariki. (2026). Self-Enrichment Teachers. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-25-3021-00
@misc{singulariki-role-25-3021-00,
title = {Self-Enrichment Teachers},
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-25-3021-00}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.