Occupation · SOC 25-2022.00
Teach one or more subjects to students at the middle, intermediate, or junior high school level.
Also called: Language Arts Teacher (LA Teacher) · Math Teacher (Mathematics Teacher) · Science Teacher · Teacher · Art Teacher · English Teacher · Middle School Teacher · Music Teacher · PE Teacher (Physical Education Teacher) · Social Studies Teacher · Algebra Teacher · American History 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-25-2022-00/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.
66th-percentile task overlap — yet about 40,500 openings a year (-2% projected, BLS), and observed AI use leans 6276% 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.) High | 86th | 1.3 | |
| LLM task exposure, γ (OpenAI / Eloundou) Moderate | 51st | 0.6 | |
| AI assistant applicability (Microsoft) Moderate | 61st | 0.2 |
OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.1), with simple added tooling (β 0.3), 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 0.2 · 32nd 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% | |
| Prepare, administer, and grade tests and assignments to evaluate students' progress. | 4.2% | |
| Instruct through lectures, discussions, and demonstrations in one or more subjects, such as English, mathematics, or social studies. | 3.7% | |
| Use computers, audio-visual aids, and other equipment and materials to supplement presentations. | 3.1% | |
| Observe and evaluate students' performance, behavior, social development, and physical health. | 1.8% | |
| Organize and label materials and display students' work. | 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 | 40,500 |
| Employment 2024 → 2034 | 633,700 → 621,300 |
“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 |
|---|---|---|
| Primary School Teachers · 2341 | 26% | 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 | 62.8% working with AI · 34.4% 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) | 18.5% |
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 |
|---|---|---|
| Instruct through lectures, discussions, and demonstrations in one or more subjects, such as English, mathematics, or social studies. | Learning | 38.7% |
| 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% |
| Guide and counsel students with adjustment or academic problems, or special academic interests. | Iteration | 3.9% |
| 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% |
Tasks where the model most often judged that a person remained necessary — a useful read on the current boundary, not a guarantee.
| Assist students who need extra help, such as by tutoring and preparing and implementing remedial programs. | 100.0% | |
| Confer with other staff members to plan and schedule lessons promoting learning, following approved curricula. | 100.0% | |
| Prepare reports on students and activities as required by administration. | 97.8% | |
| Organize and label materials and display students' work. | 97.6% | |
| Guide and counsel students with adjustment or academic problems, or special academic interests. | 97.5% | |
| Prepare objectives and outlines for courses of study, following curriculum guidelines or requirements of states and schools. | 97.2% |
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 instruct through lectures, discussions, and demonstrations in one or more subjects, such as English, mathematics, or social studies. From: Instruct through lectures, discussions, and demonstrations in one or more subjects, such as English, mathematics, or social studies. · 38.7% of measured AI use · learning
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 guide and counsel students with adjustment or academic problems, or special academic interests. From: Guide and counsel students with adjustment or academic problems, or special academic interests. · 3.9% of measured AI use · task iteration
All 35 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).
| Learning Strategies | 4.3 | |
| Speaking | 4.1 | |
| Active Listening | 4.0 | |
| Reading Comprehension | 3.9 | |
| Writing | 3.9 | |
| Active Learning | 3.9 | |
| Monitoring | 3.9 | |
| Critical Thinking | 3.8 |
| Instructing | 4.3 | |
| Social Perceptiveness | 3.9 | |
| Coordination | 3.8 | |
| Time Management | 3.8 | |
| Complex Problem Solving | 3.6 | |
| Judgment and Decision Making | 3.6 | |
| Service Orientation | 3.3 | |
| Persuasion | 3.1 |
| Oral Expression | 4.3 | |
| Oral Comprehension | 3.9 | |
| Written Comprehension | 3.9 | |
| Written Expression | 3.9 | |
| Problem Sensitivity | 3.9 | |
| Information Ordering | 3.9 | |
| Speech Clarity | 3.9 | |
| Deductive Reasoning | 3.8 | |
| Near Vision | 3.8 | |
| Speech Recognition | 3.8 | |
| Fluency of Ideas | 3.4 | |
| Inductive Reasoning | 3.3 | |
| Originality | 3.1 |
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 47.
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 , Social Sciences . 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 | 66.9% | |
| Post-Baccalaureate Certificate | 21.3% | |
| Less than a High School Diploma | 9.6% | |
| Master's Degree | 2.2% |
The interests and personal qualities O*NET associates with people who do this work.
| Integrity | 10.0 | |
| Cooperation | 9.0 | |
| Social Orientation | 8.0 | |
| Self-Control | 7.0 | |
| Stress Tolerance | 6.0 | |
| Empathy | 5.0 | |
| Adaptability | 4.0 |
| Social | 7.0 | |
| Artistic | 4.1 | |
| Conventional | 3.6 |
| Teaching/Education | 7.0 | |
| Social Service | 5.8 | |
| Professional Advising | 4.8 | |
| Public Speaking | 4.7 | |
| Humanities | 3.9 | |
| Mathematics/Statistics | 3.3 |
U.S. · annual wages (BLS OEWS)
| 10th percentile | $47,050 |
| 25th percentile | $53,540 |
| Median (50th) | $62,970 |
| 75th percentile | $79,380 |
| 90th percentile | $100,980 |
| People employed | 620,370 |
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 | 619,200 | $62,980 |
| Other Services (except Public Administration) · Sector | 720 | $57,150 |
| Administrative and Support and Waste Management and Remediation Services · Sector | 70 | — |
| Temporary Help Services · National industry | 60 | — |
| Health Care and Social Assistance · Sector | — | $60,850 |
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 | 11.28× | 619,200 |
| Other Services (except Public Administration) · Sector | 0.04× | 720 |
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 Middle School Teachers, Except Special and Career/Technical Education — 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 48th percentile of 427 international occupations.
Middle School Teachers, Except Special and Career/Technical Education show 66th-percentile AI task overlap — and about 40,500 annual U.S. openings
Middle School Teachers, Except Special and Career/Technical Education show 66th-percentile AI task overlap — and about 40,500 annual U.S. openings • Middle School Teachers, Except Special and Career/Technical Education rank in the 66th 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 40,500 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 declining (-2%) from 2024 to 2034. (BLS Employment Projections 2024–34) • Median annual pay is $62,970, across about 620,370 U.S. workers. (BLS OEWS (May 2024)) • Of the AI use actually observed for this work, 63% 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 — "Middle School Teachers, Except Special and Career/Technical Education". https://singulariki.com/roles/role-25-2022-00 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. "Middle School Teachers, Except Special and Career/Technical Education." 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-25-2022-00
Singulariki. (2026). Middle School Teachers, Except Special and Career/Technical Education. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-25-2022-00
@misc{singulariki-role-25-2022-00,
title = {Middle School Teachers, Except Special and Career/Technical Education},
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-25-2022-00}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.