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STRATUSWORKFORCE SCAN

Secondary School Teachers, Except Special and Career/Technical Education

In short: today's best AI models could do about 40% of this job's working time (projected from METR's April 2026 measurement and Epoch's November 2026 index) if the work were set up for them, and about 41% by the end of 2028 if progress keeps its long-run pace. The conversations, in-person and hands-on work, about 59% of the time, stays with people.

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Teach one or more subjects to students at the secondary school level.

1,065,210 people do this job in the US. $72,040 a year.

Reviewed on September 30, 2026: what each task is made of, and what handing it over would ask.

A typical 40-hour week

  • AI could take on3 h
  • A person checks AI's work13 h
  • Desk work AI can't do yet0 h
  • Stays with people24 h

Secondary School Teachers, Except Special and Career/Technical Education, now: of a 40-hour week, AI could take on 3 hours, 13 hours become checking its work, 0 hours are desk work it can't do yet, and 24 hours stay with people.

The largest pieces: Prepare course objectives and outlines (about 3 h, a person checks); Adapt methods and materials to students (about 2 h, a person checks); Assign and grade class work (about 1 h, a person checks).

Estimates for a typical week of this job, if progress keeps its long-run pace, counting work the best models finish four times in five. Every task is below.

now
40%

of the working time. Now is projected from METR's April 2026 measurement and Epoch's November 2026 index.

What the work is made of
  • 37%
  • 3%
  • 4%
  • 51%
  • 4%
29%

of the work: Anthropic's measure of what people already bring to Claude at work (2025). It counts help with part of a task, so it can be higher than the share within reach.

Half the desk work within reach
Already

On the chosen pace and reliability. Estimate.

Share of the working time within reach, now to 2030

0%25%50%75%100%2027202820292030NowDesk work: 41% of the time
Chosen to Ceiling: the share
DateNow
NowEnd of 2030
Change assumptionsLong-run pace, four in five

What each choice means: , , , , . Every pace starts from .

At this date and pace, models finish tasks up to 2.4 work days long four times in five.

What handing it over would take, now

The 40% within reach splits by what a model would need. The dates, pace and reliability follow the controls above. Estimates.

36%

of the working time. The material can be handed to a model and the result handed back.

3%

of the working time. The model has to be connected to the system the work lives in.

, not counted
4%

is conversation short enough by length. This site leaves conversation with people, so it is not in the total.

How far this has come

With GPT-4, measured in March 2023, 0% of this job's working time was within reach at . With Claude 3.7 Sonnet, measured in February 2025, 0%. With Claude Mythos Preview (early), measured in April 2026, 29%. Today's estimate: 40%.

0%10%20%30%40%50%2023202420252026GPT-4, March 2023: 0% within reachGPT-4 Turbo (Nov 2023), November 2023: 0% within reachGPT-4o, May 2024: 0% within reachClaude 3.5 Sonnet (June 2024), June 2024: 0% within reacho1-preview, September 2024: 0% within reachClaude 3.5 Sonnet (Oct 2024), October 2024: 0% within reacho1, December 2024: 0% within reachClaude 3.7 Sonnet, February 2025: 0% within reacho3, April 2025: 3% within reachGPT-5, August 2025: 6% within reachGemini 3 Pro, November 2025: 10% within reachClaude Opus 4.5, November 2025: 10% within reachGPT-5.2, December 2025: 13% within reachClaude Opus 4.6, February 2026: 14% within reachClaude Mythos Preview (early), April 2026: 29% within reachToday (estimate), November 2026: 40% within reach
Each step is a new best model measured by METR, four in five; the dashed end is today's estimate. Point at a dot for the model.

A backcast: today's task data with the best model METR had measured by each date. It shows how fast the models have moved, not what anyone forecast at the time.

Measured use over time

Of the Claude.ai conversations Anthropic sampled and tied to a work task, 0.0025% went to this job's tasks in May 2026, the 446th largest of the 447 jobs that showed up at all; 2 of its 32 tasks showed up. Within each of Anthropic's methods, never across a change: 0.071% to 0.054% (released February and March 2025); 0.21% to 0.11% (August 2025 to February 2026); 0.0026% to 0.0025% (April to May 2026).

0%0.25%0.5%20252026released February 2025: 0.071%released March 2025: 0.054%the week of Aug 4, 2025: 0.21%the week of Nov 13, 2025: 0.14%the week of Feb 5, 2026: 0.11%April 2026: 0.0026%May 2026: 0.0025%
Each dot is one release's sample. A line joins releases made by the same method; a change of method starts a new line. Point at a dot for its window.
Each release
ConversationsShareRankTasks seen
Released February 20250.071%220 of 70816 of 32
Released March 20250.054%260 of 70317 of 32
The week of Aug 4, 20250.21%92 of 65511 of 32
The week of Nov 13, 20250.14%118 of 67218 of 32
The week of Feb 5, 20260.11%151 of 67715 of 32
April 20260.0026%433 of 4342 of 32
May 20260.0025%446 of 4472 of 32

Measured, not estimated: Anthropic's samples of Claude.ai conversations, each tied by a model to an O*NET task, from the Anthropic Economic Index. It says where Claude's use goes, not how much of this job's working time it covers, so it is not on the same scale as the reach above. The releases differ in their sample, their classifier and the smallest share they report (the June 2026 file rounds each task to a hundredth of a percent, so a smaller task reads as none), which is why a change of method starts a new line. At least 96% of each older release's task-tied use matched this site's tasks, and all of the newest. Claude.ai only, so use through other tools and other companies' models is not in it. Every job ranked.

Robots and the physical work

Anthropic rates 11% of this job's working time as physical work. For 7% of the working time, a robot has been shown doing most of the task somewhere: 7% in a purpose-built cell. 0.07 of 3, the 551st highest of the 923 jobs.

  • Not physical 89%
  • No robot shown 4%
  • In a purpose-built cell 7%

Anthropic's rating, not this site's estimate: Claude Opus 5, searching the web, rated each physical O*NET task by the kind of setting in which a robot it could cite (deployed, sold or demonstrated) does most of the task, weighted by its own estimate of each task's share of the time (What work can robots do?, September 30, 2026, data CC BY 4.0; every job ranked). A robot shown somewhere is not a robot in your building: cost, setup and safety decide that. The share within reach on this page still counts no body work. The robot behind each rated task is under the task below.

What changes for the people in this job

From the task-by-task review, by the end of 2028 on the long-run pace at four in five. It says which parts of the work stay with people and which change, not whether anyone keeps a job: that depends on decisions no data set can see.

What stays with people

59% of the working time: the conversation, in-person and hands-on parts of the tasks.

  • Instruct through lectures and discussions, the in-person work, 9%
  • Plan and supervise projects and field trips, the in-person work, 5%
  • Set and enforce classroom rules, the in-person work, 4%
  • Plan and conduct a balanced program, the in-person work, 4%
  • Encourage students to explore and persevere, the in-person work, 4%
  • Use computers and audio-visual aids in class, the in-person work, 4%

What becomes checking the machine

33% of the working time: desk work a model could do by then, in tasks where a mistake costs something or a licensed person signs. A person checks it. Another 7% is desk work that is small if wrong, which can be handed over with lighter checks.

  • Prepare course objectives and outlines, costly if wrong, 8%
  • Adapt methods and materials to students, costly if wrong, 5%
  • Assign and grade class work, a licensed person signs, 3%
  • Prepare, give and grade tests, a licensed person signs, 3%
  • Keep student records, costly if wrong, 2%
  • Prepare reports on students, costly if wrong, 2%

What to learn

  • The conversations. About 55% of the time is conversation and in-person work, which this site leaves with people: listening, explaining, persuading, calming.
  • Signing off under your license. Some tasks need a licensed, certified or sworn person to do or sign them. The license, and the judgment it stands for, stays with the person.
  • Reviewing work you did not do yourself. The tasks under What becomes checking the machine, where a mistake costs something, stay a person's to check or sign: spotting what a draft gets wrong is a skill of its own.
  • Briefing a model and checking its drafts. About 37% of the time is documents and data, the part models reach first: writing a clear brief, giving the right material, and checking what comes back.
  • Dealing with people outside the organization. Customers, patients, suppliers or the public: trust with them is built by a person.

Your own version of this job: read it against your job description. The headline is free; the full personal report, every task with its timeline and what to learn, is $19 (a sample).

The tasks

Sorted by . 32 tasks from .

Task
Instruct through lectures, discussions, and demonstrations in one or more subjects, such as English, mathematics, or social studies.Teaching a room of students.Done daily by most who do it. AI observed on this task.9%50 min38 min to 1.3 hIn person 100%Stays with people
Prepare objectives and outlines for courses of study, following curriculum guidelines or requirements of states and schools.Curriculum planning on paper.Done daily by most who do it. AI observed on this task.8%2.5 h50 min to 6.7 hDocuments 100%96%Half by now
Plan and supervise class projects, field trips, visits by guest speakers, or other experiential activities, and guide students in learning from those activities.Leading students in person, with the planning behind it.Done more than yearly by most who do it. 7%5 h1.7 h to 2.1 work daysIn person 70%, documents 30%22%Desk part half by now
Adapt teaching methods and instructional materials to meet students' varying needs and interests.Reworking materials, and trying them with the class.Done daily by most who do it. AI observed on this task.7%1.1 h25 min to 2.1 hDocuments 70%, in person 30%70%Desk part half by now
Plan and conduct activities for a balanced program of instruction, demonstration, and work time that provides students with opportunities to observe, question, and investigate.Teaching a room, with the planning behind it.Done daily by most who do it. AI observed on this task.6%1.3 h38 min to 2.5 hIn person 70%, documents 30%30%Desk part half by now
Prepare materials and classrooms for class activities.Writing and gathering lesson materials, and setting up the room.Done daily by most who do it. Robots: in a purpose-built cell, Xerox / Plockmatic PowerSquare 160 inline booklet finishing system (sold). Anthropic's rating.5%33 min17 min to 1.1 hDocuments 60%, hands-on 40%60%Desk part half by now
Prepare, administer, and grade tests and assignments to evaluate students' progress.Writing and marking tests, and giving them in class.Done more than weekly by most who do it. AI observed on this task.5%1.3 h38 min to 2.5 hDocuments 70%, in person 30%70%Desk part half by now
Establish and enforce rules for behavior and procedures for maintaining order among students.Keeping order in a room of students.Done hourly or more by most who do it. 4%21 min8 min to 50 minIn person 100%Stays with people
Assign and grade class work and homework.Marking papers, and handing the work out and back.Done daily by most who do it. 4%50 min25 min to 1.7 hDocuments 80%, in person 20%80%Desk part half by now
Prepare students for later grades by encouraging them to explore learning opportunities and to persevere with challenging tasks.Teaching a room of students.Done daily by most who do it. 4%25 min13 min to 50 minIn person 100%Stays with people
Use computers, audio-visual aids, and other equipment and materials to supplement presentations.Teaching a room, with the equipment in hand.Done daily by most who do it. AI observed on this task.4%25 min13 min to 50 minIn person 70%, hands-on 30%Stays with people
Administer standardized ability and achievement tests, and interpret results to determine students' strengths and needs.Proctoring in the room, then reading the results.Done more than yearly by most who do it. 3%2.5 h1.3 h to 6.7 hDocuments 50%, in person 50%50%Desk part half by now

Within reach, per task: the share of the task's time whose instances are short enough for a model to finish at the chosen date, pace and reliability. Half by: the date half of that time comes within reach. Made of: how the task's time splits among five kinds of doing. Only the documents and systems parts can count as within reach, so a task that is 30% documents can be at most 30% within reach.

Jobs that share skills with this one

From O*NET's related occupations. Within reach now and by the end of 2028, long-run pace, four in five.

Where this job works

The industry groups that employ the most of it (BLS, May 2025).

Where the most of these jobs are

The metro areas with the most people in it (BLS, May 2025).

Questions about this job

How much of the work of Secondary School Teachers, Except Special and Career/Technical Education is within reach of AI now?
An estimated 40% of the working time is within reach of AI models now and 41% by the end of 2028, on METR's long-run pace at four in five. Within reach means a model could finish work that long at that reliability. It is not a forecast of jobs lost or of savings.
Which tasks of Secondary School Teachers, Except Special and Career/Technical Education come within reach first?
Weighted by the time each takes, the tasks with the most within reach now (projected from METR's April 2026 measurement and Epoch's November 2026 index) are: Prepare course objectives and outlines (96% of the task's time now); Adapt methods and materials to students (70% of the task's time now); and Assign and grade class work (80% of the task's time now).
Which tasks of Secondary School Teachers, Except Special and Career/Technical Education stay with people?
Tasks that are people work or body work are not counted as within reach at any date. The largest: Instruct through lectures and discussions; Set and enforce classroom rules; and Encourage students to explore and persevere. Together such tasks are about 34% of the working time, and the people and body parts of the other tasks stay with people too.
What should Secondary School Teachers, Except Special and Career/Technical Education learn as AI takes on more of the work?
By the job's own task-by-task review, the first things to learn are the conversations; signing off under your license; and reviewing work you did not do yourself. By the end of 2028 on the long-run pace at four in five, about 59% of the working time stays with people, 33% becomes checking a model's work and 7% could be handed over with lighter checks. It says which parts of the work change, never whether anyone keeps a job.
Do people already use AI for the work of Secondary School Teachers, Except Special and Career/Technical Education?
In the Claude.ai conversations Anthropic sampled for May 2026 and tied to a work task, 0.0025% went to this job's tasks, the 446th largest share of the 447 jobs that showed up; 2 of its 32 tasks appeared. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 29%. These are measures of use, not of how much of the work AI could finish, and they cover Claude only.
Can robots do the physical work of Secondary School Teachers, Except Special and Career/Technical Education?
Anthropic's robot exposure rating (September 2026) finds 11% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 7% of the working time. Its index is 0.07 of 3. One example: Xerox / Plockmatic PowerSquare 160 inline booklet finishing system for "prepare materials and classrooms". A robot shown somewhere is not one in every workplace; this site's own estimates still count no physical work as within reach.
How is this estimated?
From the 32 tasks O*NET lists for the occupation, each with an estimated length checked against GDPval and a share of the working time, reviewed one task at a time on September 30, 2026 for what each is made of (documents, business systems, conversation, in person, hands-on), and METR's measurements of how long a task the best AI models can finish, carried forward to the date from the latest, Claude Mythos Preview (early) in April 2026. Data checked November 10, 2026.

How the estimates are made

This job in your state or metro area
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A small card with the share of working time within reach now and at the end of 2027, 2028 and 2030, the date and a link back. Free under CC BY 4.0; the card carries the credit.

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Your own version of this job

The page above is the occupation. Your job is your title and what you actually do: give both, and they are read against these tasks in your browser, nothing sent anywhere. The headline is free: how much of your working time is within reach now and by the end of 2028, and how many of the tasks your description names.

The full personal report is $19, to print or save as a PDF: every task with when it comes within reach, which ones your description names, the parts of your description the task list does not cover, what stays with you, what becomes checking the machine and what to learn.