Occupation · SOC 25-2023.00
Teach occupational, vocational, career, or technical subjects to students at the middle, intermediate, or junior high school level.
Also called: Family and Consumer Sciences Teacher (FACS Teacher) · Teacher · Technology Education Teacher (Tech Ed Teacher) · Technology Teacher · Business Education Teacher · Business Teacher · Career and Technology Education Teacher (CTE Teacher) · Computer Teacher · Industrial Arts Teacher · Industrial Technology Teacher · Agriscience Technology Instructor (Agriculture Science Technology Instructor) · Automotive 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-25-2023-00/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.
54th-percentile task overlap — yet about 900 openings a year (-2% projected, BLS), and observed AI use leans 4753% 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 | 41st | 0.5 | |
| AI assistant applicability (Microsoft) Moderate | 62nd | 0.2 |
OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.2), with simple added tooling (β 0.3), and including AI-powered software (γ 0.5). 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 0.3 · 38th percentile among occupations · Moderate
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% | |
| Prepare, administer, and grade tests and assignments to evaluate students' progress. | 4.2% | |
| 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% | |
| Observe and evaluate students' performance, behavior, social development, and physical health. | 1.8% | |
| 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 | Declining · -2.0% by 2034 |
| Projected annual openings | 900 |
| Employment 2024 → 2034 | 14,000 → 13,800 |
“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 | 47.5% working with AI · 47.3% handed to AI |
| 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 |
| Used for work (vs. personal / coursework) | 34.0% |
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 |
|---|---|---|
| Prepare, administer, and grade tests and assignments to evaluate students' progress. | Directive | 7.7% |
| Use computers, audio-visual aids, and other equipment and materials to supplement presentations. | Learning | 5.7% |
| 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% |
| Prepare objectives and outlines for courses of study, following curriculum guidelines or requirements of states and schools. | Directive | 1.8% |
| Adapt teaching methods and instructional materials to meet students' varying needs and interests. | Iteration | 1.5% |
| Assign and grade class work and homework. | Directive | 1.0% |
| Prepare reports on students and activities as required by administration. | 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.
| Confer with other staff members to plan and schedule lessons promoting learning, following approved curricula. | 100.0% | |
| Assign and grade class work and homework. | 98.1% | |
| Prepare reports on students and activities as required by administration. | 97.8% | |
| Sponsor extracurricular activities such as clubs, student organizations, and academic contests. | 97.6% | |
| Prepare objectives and outlines for courses of study, following curriculum guidelines or requirements of states and schools. | 97.2% | |
| Meet with parents and guardians to discuss their children's progress and to determine priorities for their children and their resource needs. | 97.1% |
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 prepare, administer, and grade tests and assignments to evaluate students' progress. From: Prepare, administer, and grade tests and assignments to evaluate students' progress. · 7.7% of measured AI use · directive
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 prepare materials and classrooms for class activities. From: Prepare materials and classrooms for class activities. · 2.2% of measured AI use · directive
Help me plan and conduct activities for a balanced program of instruction, demonstration, and work time that provides students with opportunities to observe, question, and investigate. From: Plan and conduct activities for a balanced program of instruction, demonstration, and work time that provides students with opportunities to observe, question, and investigate. · 2.0% of measured AI use · directive
All 31 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).
| Speaking | 4.1 | |
| Reading Comprehension | 4.0 | |
| Active Listening | 4.0 | |
| Learning Strategies | 4.0 | |
| Critical Thinking | 3.9 | |
| Monitoring | 3.9 | |
| Writing | 3.6 | |
| Active Learning | 3.5 |
| Oral Expression | 4.1 | |
| Oral Comprehension | 4.0 | |
| Written Comprehension | 4.0 | |
| Speech Clarity | 4.0 | |
| Written Expression | 3.9 | |
| Deductive Reasoning | 3.9 | |
| Near Vision | 3.9 | |
| Speech Recognition | 3.9 | |
| Problem Sensitivity | 3.8 | |
| Inductive Reasoning | 3.8 | |
| Fluency of Ideas | 3.3 | |
| Originality | 3.3 | |
| Category Flexibility | 3.3 | |
| Information Ordering | 3.1 | |
| Selective Attention | 3.1 | |
| Far Vision | 3.1 |
| Instructing | 4.0 | |
| Social Perceptiveness | 3.9 | |
| Coordination | 3.4 | |
| Judgment and Decision Making | 3.4 | |
| Service Orientation | 3.3 | |
| Complex Problem Solving | 3.3 | |
| Systems Analysis | 3.0 |
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 68.
Showing the top 40 of 94.
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 . Fields of study crosswalked to this occupation (NCES CIP–SOC), not a requirement.
Share of people in this occupation at each level of education.
| Bachelor's Degree | 64.9% | |
| Master's Degree | 18.8% | |
| Post-Baccalaureate Certificate | 15.7% | |
| Post-Secondary Certificate | 0.6% |
The interests and personal qualities O*NET associates with people who do this work.
| Dependability | 8.0 | |
| Integrity | 7.0 | |
| Cooperation | 6.0 | |
| Social Orientation | 5.0 | |
| Self-Control | 4.0 | |
| Stress Tolerance | 3.0 |
| Social | 7.0 | |
| Conventional | 3.8 | |
| Artistic | 3.4 | |
| Investigative | 3.3 | |
| Realistic | 3.3 |
| Teaching/Education | 6.8 | |
| Social Service | 5.4 | |
| Professional Advising | 4.6 | |
| Public Speaking | 4.4 | |
| Social Science | 2.5 |
U.S. · annual wages (BLS OEWS)
| 10th percentile | $47,090 |
| 25th percentile | $55,920 |
| Median (50th) | $63,620 |
| 75th percentile | $78,270 |
| 90th percentile | $98,430 |
| People employed | 14,200 |
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 | 14,190 | $63,630 |
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 | 11.3× | 14,190 |
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, Middle School — 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, Middle School show 54th-percentile AI task overlap — and about 900 annual U.S. openings
Career/Technical Education Teachers, Middle School show 54th-percentile AI task overlap — and about 900 annual U.S. openings • Career/Technical Education Teachers, Middle School rank in the 54th 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 900 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 declining (-2%) from 2024 to 2034. (BLS Employment Projections 2024–34) • Median annual pay is $63,620, across about 14,200 U.S. workers. (BLS OEWS (May 2024)) • Of the AI use actually observed for this work, 48% 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, Middle School". https://singulariki.com/roles/role-25-2023-00 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, Middle School." 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-25-2023-00
Singulariki. (2026). Career/Technical Education Teachers, Middle School. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-25-2023-00
@misc{singulariki-role-25-2023-00,
title = {Career/Technical Education Teachers, Middle School},
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-25-2023-00}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.