Occupation · SOC 25-1194.00
Teach vocational courses intended to provide occupational training below the baccalaureate level in subjects such as construction, mechanics/repair, manufacturing, transportation, or cosmetology, primarily to students who have graduated from or left high school. Teaching takes place in public or private schools whose primary business is academic or vocational education.
Also called: Cosmetology Instructor · HVAC-R Instructor (Heating, Ventilation, Air Conditioning, And Refrigeration Instructor) · Instructor · Professor · Automotive Instructor · Automotive Technology Instructor · Flight Instructor · Teacher · Welding Instructor · Accounting Teacher · Adjunct Instructor · Adult Education Instructor
Job family: Educational Instruction and Library Occupations
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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.
61st-percentile task overlap — yet about 8,800 openings a year (+0.7% projected, BLS), and observed AI use leans 6441% 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 | 52nd | 0.2 | |
| LLM task exposure, γ (OpenAI / Eloundou) High | 71st | 0.8 | |
| AI assistant applicability (Microsoft) Moderate | 64th | 0.2 |
OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.1), with simple added tooling (β 0.5), and including AI-powered software (γ 0.8). 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.
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.
| Observe and evaluate students' work to determine progress, provide feedback, and make suggestions for improvement. | 27.8% | |
| Develop curricula and plan course content and methods of instruction. | 4.0% | |
| Present lectures and conduct discussions to increase students' knowledge and competence using visual aids, such as graphs, charts, videotapes, and slides. | 0.7% | |
| Select and assemble books, materials, supplies, and equipment for training, courses, or projects. | 0.7% | |
| Prepare outlines of instructional programs and training schedules and establish course goals. | 0.2% |
Independent U.S. Bureau of Labor Statistics employment projection for 2024–2034 — a labor-market forecast, not an AI-impact forecast.
| Outlook | About average · +0.7% by 2034 |
| Projected annual openings | 8,800 |
| Employment 2024 → 2034 | 122,200 → 123,000 |
“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 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.
| International occupation (ISCO-08) | Task exposure (2025) | Most tasks fall in |
|---|---|---|
| Vocational Education Teachers · 2320 | 35% | Minimal |
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 | 64.4% working with AI · 33.1% handed to AI |
| Most common way people use AI here | Iteration · you and AI go back and forth |
| Typical AI autonomy | 4.0 / 5 · higher = AI acts more independently |
| Used for work (vs. personal / coursework) | 30.4% |
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 |
|---|---|---|
| Observe and evaluate students' work to determine progress, provide feedback, and make suggestions for improvement. | Validation | 21.7% |
| Develop teaching aids such as instructional software, multimedia visual aids, or study materials. | Directive | 18.8% |
| Develop curricula and plan course content and methods of instruction. | Directive | 5.4% |
| Select and assemble books, materials, supplies, and equipment for training, courses, or projects. | Directive | 1.1% |
| Conduct on-the-job training classes or training sessions to teach and demonstrate principles, techniques, procedures, or methods of designated subjects. | Learning | 1.0% |
| Supervise independent or group projects, field placements, laboratory work, or other training. | Iteration | 0.9% |
| Advise students on course selection, career decisions, and other academic and vocational concerns. | Iteration | 0.6% |
| Provide individualized instruction and tutorial or remedial instruction. | Directive | 0.5% |
Tasks where the model most often judged that a person remained necessary — a useful read on the current boundary, not a guarantee.
| Advise students on course selection, career decisions, and other academic and vocational concerns. | 100.0% | |
| Provide individualized instruction and tutorial or remedial instruction. | 100.0% | |
| Select and assemble books, materials, supplies, and equipment for training, courses, or projects. | 98.2% | |
| Observe and evaluate students' work to determine progress, provide feedback, and make suggestions for improvement. | 95.6% | |
| Develop curricula and plan course content and methods of instruction. | 93.7% | |
| Develop teaching aids such as instructional software, multimedia visual aids, or study materials. | 92.5% |
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 observe and evaluate students' work to determine progress, provide feedback, and make suggestions for improvement. From: Observe and evaluate students' work to determine progress, provide feedback, and make suggestions for improvement. · 21.7% of measured AI use · validation
Help me develop teaching aids such as instructional software, multimedia visual aids, or study materials. From: Develop teaching aids such as instructional software, multimedia visual aids, or study materials. · 18.8% of measured AI use · directive
Help me develop curricula and plan course content and methods of instruction. From: Develop curricula and plan course content and methods of instruction. · 5.4% of measured AI use · directive
Help me select and assemble books, materials, supplies, and equipment for training, courses, or projects. From: Select and assemble books, materials, supplies, and equipment for training, courses, or projects. · 1.1% of measured AI use · directive
All 20 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 | 4.5 | |
| English Language | 3.8 | |
| Mechanical | 3.7 | |
| Customer and Personal Service | 3.7 | |
| Mathematics | 3.7 | |
| Administrative | 3.5 | |
| Engineering and Technology | 3.5 | |
| Computers and Electronics | 3.4 | |
| Administration and Management | 3.4 | |
| Public Safety and Security | 3.3 | |
| Design | 3.2 | |
| Chemistry | 3.1 | |
| Personnel and Human Resources | 3.0 |
| Active Listening | 4.0 | |
| Learning Strategies | 4.0 | |
| Reading Comprehension | 3.9 | |
| Speaking | 3.9 | |
| Active Learning | 3.9 | |
| Critical Thinking | 3.8 | |
| Writing | 3.6 | |
| Monitoring | 3.6 |
| Instructing | 4.0 | |
| Social Perceptiveness | 3.3 | |
| Complex Problem Solving | 3.3 | |
| Judgment and Decision Making | 3.3 | |
| Coordination | 3.1 | |
| Persuasion | 3.0 | |
| Negotiation | 3.0 | |
| Service Orientation | 3.0 |
| Oral Comprehension | 4.0 | |
| Oral Expression | 4.0 | |
| Written Comprehension | 3.9 | |
| Written Expression | 3.9 | |
| Problem Sensitivity | 3.8 | |
| Speech Clarity | 3.8 | |
| Deductive Reasoning | 3.6 | |
| Speech Recognition | 3.6 | |
| Inductive Reasoning | 3.3 | |
| Information Ordering | 3.3 | |
| Near Vision | 3.3 |
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 42.
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: Agriculture, Agriculture Operations, and Related Sciences , Computer and Information Sciences and Support Services , Education , Homeland Security, Law Enforcement, Firefighting and Related Protective Services , Transportation and Materials Moving . Fields of study crosswalked to this occupation (NCES CIP–SOC), not a requirement.
Share of people in this occupation at each level of education.
| Associate's Degree (or other 2-year degree) | 42.3% | |
| Bachelor's Degree | 20.2% | |
| Post-Secondary Certificate | 16.2% | |
| Master's Degree | 7.6% | |
| Some College Courses | 6.9% | |
| Doctoral Degree | 4.7% | |
| High School Diploma | 2.2% |
The interests and personal qualities O*NET associates with people who do this work.
| Teaching/Education | 6.6 | |
| Public Speaking | 4.9 | |
| Professional Advising | 4.4 | |
| Social Service | 3.6 | |
| Mechanics/Electronics | 3.4 | |
| Engineering | 2.9 | |
| Construction/Woodwork | 2.6 | |
| Human Resources | 2.6 |
| Social | 6.6 | |
| Investigative | 4.2 | |
| Realistic | 3.8 | |
| Conventional | 3.3 | |
| Artistic | 3.1 |
| Dependability | 5.0 | |
| Cooperation | 4.0 | |
| Achievement Orientation | 3.0 |
U.S. · annual wages (BLS OEWS)
| 10th percentile | $38,680 |
| 25th percentile | $48,030 |
| Median (50th) | $61,490 |
| 75th percentile | $80,070 |
| 90th percentile | $106,580 |
| People employed | 111,150 |
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 | 103,420 | $61,540 |
| Health Care and Social Assistance · Sector | 1,590 | $56,300 |
| Other Services (except Public Administration) · Sector | 430 | $96,860 |
| Labor Unions and Similar Labor Organizations · National industry | 200 | $101,190 |
| Finance and Insurance · Sector | 80 | $121,910 |
| Ambulance Services · National industry | 80 | $56,170 |
| Transportation and Warehousing · Sector | — | $55,710 |
| Professional, Scientific, and Technical Services · Sector | — | $54,140 |
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 |
|---|---|---|
| Educational Services · Sector | 10.52× | 103,420 |
| Labor Unions and Similar Labor Organizations · National industry | 2.62× | 200 |
| Other Services (except Public Administration) · Sector | 0.13× | 430 |
| Health Care and Social Assistance · Sector | 0.1× | 1,590 |
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 Career/Technical Education Teachers, Postsecondary — 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 64th percentile of 427 international occupations.
Career/Technical Education Teachers, Postsecondary show 61st-percentile AI task overlap — and about 8,800 annual U.S. openings
Career/Technical Education Teachers, Postsecondary show 61st-percentile AI task overlap — and about 8,800 annual U.S. openings • Career/Technical Education Teachers, Postsecondary rank in the 61st 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 8,800 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 (+0.7%) from 2024 to 2034. (BLS Employment Projections 2024–34) • Median annual pay is $61,490, across about 111,150 U.S. workers. (BLS OEWS (May 2024)) • Of the AI use actually observed for this work, 64% 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 — "Career/Technical Education Teachers, Postsecondary". https://singulariki.com/roles/role-25-1194-00 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. "Career/Technical Education Teachers, Postsecondary." 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; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026. https://singulariki.com/roles/role-25-1194-00
Singulariki. (2026). Career/Technical Education Teachers, Postsecondary. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-25-1194-00
@misc{singulariki-role-25-1194-00,
title = {Career/Technical Education Teachers, Postsecondary},
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; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026},
url = {https://singulariki.com/roles/role-25-1194-00}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.