Adult Basic Education, Adult Secondary Education, and English as a Second Language Instructors
In short: today's best AI models could do about 66% 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 the same by the end of 2028 if progress keeps its long-run pace. The people and hands-on work, about 34% of the time, stays with people.
Teach or instruct out-of-school youths and adults in basic education, literacy, or English as a Second Language classes, or in classes for earning a high school equivalency credential.
37,310 people do this job in the US. $61,540 a year.
A typical 40-hour week
Not yet reviewed task by task- AI could take on26 h
- A person checks AI's work0 h
- Desk work AI can't do yet0 h
- Stays with people14 h
Adult Basic Education, Adult Secondary Education, and English as a Second Language Instructors, now: of a 40-hour week, AI could take on 26 hours, 0 hours become checking its work, 0 hours are desk work it can't do yet, and 14 hours stay with people.
The largest pieces: Conduct classes, workshops, and demonstrations to teach principles, techniques, or methods in subjects, such as basic English language skills, life skills, and workforce entry skills (about 4 h); Adapt teaching methods and instructional materials to meet students' varying needs, abilities, and interests (about 4 h); Observe students to determine qualifications, limitations, abilities, interests, and other individual characteristics (about 2 h).
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.
of the working time. Now is projected from METR's April 2026 measurement and Epoch's November 2026 index.
- 66%
- 3%
- 31%
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.
On the chosen pace and reliability. Estimate.
Share of the working time within reach, now to 2030
Change assumptionsHide 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.
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, 51%. Today's estimate: 66%.
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, 0.059% went to this job's tasks in May 2026, the 218th largest of the 447 jobs that showed up at all; 6 of its 37 tasks showed up. Within each of Anthropic's methods, never across a change: 0.36% to 0.22% (released February and March 2025); 0.73% to 0.59% (August 2025 to February 2026); 0.041% to 0.059% (April to May 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.36% | 57 of 708 | 17 of 37 |
| Released March 2025 | 0.22% | 86 of 703 | 18 of 37 |
| The week of Aug 4, 2025 (released September 2025) | 0.73% | 26 of 655 | 16 of 37 |
| The week of Nov 13, 2025 (released January 2026) | 0.66% | 29 of 672 | 19 of 37 |
| The week of Feb 5, 2026 (released March 2026) | 0.59% | 33 of 677 | 15 of 37 |
| April 2026 (released June 2026) | 0.041% | 243 of 434 | 5 of 37 |
| May 2026 (released June 2026) | 0.059% | 218 of 447 | 6 of 37 |
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 6% of this job's working time as physical work. For 6% of the working time, a robot has been shown doing most of the task somewhere: 6% in a purpose-built cell. 0.06 of 3, the 563rd highest of the 923 jobs.
- Not physical 94%
- In a purpose-built cell 6%
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.
The tasks
Sorted by . 37 tasks from .
| Task | Kind | |||
|---|---|---|---|---|
| Conduct classes, workshops, and demonstrations to teach principles, techniques, or methods in subjects, such as basic English language skills, life skills, and workforce entry skills.Done daily by most who do it. | 11% | 1.7 h50 min to 2.5 h | 100%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.Done daily by most who do it. AI observed on this task. | 9% | 1.3 h38 min to 2.5 h | Stays with people | |
| Instruct students individually and in groups, using various teaching methods, such as lectures, discussions, and demonstrations.Done daily by most who do it. | 9% | 50 min25 min to 1.7 h | Stays with people | |
| Adapt teaching methods and instructional materials to meet students' varying needs, abilities, and interests.Done daily by most who do it. AI observed on this task. | 9% | 1.3 h25 min to 2.5 h | 100%Half by now | |
| Observe students to determine qualifications, limitations, abilities, interests, and other individual characteristics.Done daily by most who do it. | 6% | 38 min17 min to 1.3 h | 100%Half by now | |
| Review instructional content, methods, and student evaluations to assess strengths and weaknesses, and to develop recommendations for course revision, development, or elimination.Done more than monthly by most who do it. AI observed on this task. | 5% | 2.1 h50 min to 4.2 h | 100%Half by now | |
| Attend professional meetings, conferences, and workshops to maintain and improve professional competence.Done more than yearly by most who do it. | 5% | 3.3 h50 min to 6.7 h | 91%Half by now | |
| Assign and grade class work and homework.Done daily by most who do it. | 4% | 50 min25 min to 1.7 h | 100%Half by now | |
| Observe and evaluate students' work to determine progress and make suggestions for improvement.Done daily by most who do it. AI observed on this task. | 3% | 25 min13 min to 50 min | 100%Half by now | |
| Prepare objectives and outlines for courses of study, following curriculum guidelines or requirements of states and schools.Done more than yearly by most who do it. AI observed on this task. | 3% | 2.5 h50 min to 6.7 h | 96%Half by now | |
| Establish clear objectives for all lessons, units, and projects and communicate those objectives to students.Done daily by most who do it. | 3% | 25 min13 min to 50 min | 100%Half by now | |
| Prepare for assigned classes and show written evidence of preparation upon request of immediate supervisors.Done daily by most who do it. | 3% | 50 min25 min to 1.7 h | 100%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.
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.
- Elementary School Teachers, Except Special Education35% now, 35% by 2028
- Secondary School Teachers, Except Special and Career/Technical Education40% now, 41% by 2028
- Tutors23% now, 23% by 2028
- Special Education Teachers, Kindergarten34% now, 34% by 2028
- Middle School Teachers, Except Special and Career/Technical Education43% now, 44% by 2028
- Special Education Teachers, Elementary School40% now, 40% by 2028
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 Adult Basic Education, Adult Secondary Education, and English as a Second Language Instructors is within reach of AI now?
- An estimated 66% of the working time is within reach of AI models now and 66% 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 Adult Basic Education, Adult Secondary Education, and English as a Second Language Instructors 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: Conduct classes, workshops, and demonstrations to teach principles, techniques, or methods in subjects, such as basic English language skills, life skills, and workforce entry skills (100% of the task's time now); Adapt teaching methods and instructional materials to meet students' varying needs, abilities, and interests (100% of the task's time now); and Observe students to determine qualifications, limitations, abilities, interests, and other individual characteristics (100% of the task's time now).
- Which tasks of Adult Basic Education, Adult Secondary Education, and English as a Second Language Instructors stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Plan and conduct activities for a balanced program of instruction, demonstration, and work time that provides students with opportunities to observe, question, and investigate; Instruct students individually and in groups, using various teaching methods, such as lectures, discussions, and demonstrations; and Plan and supervise class projects, field trips, visits by guest speakers, contests, or other experiential activities, and guide students in learning from those activities. Together such tasks are about 34% of the working time.
- Do people already use AI for the work of Adult Basic Education, Adult Secondary Education, and English as a Second Language Instructors?
- In the Claude.ai conversations Anthropic sampled for May 2026 and tied to a work task, 0.059% went to this job's tasks, the 218th largest share of the 447 jobs that showed up; 6 of its 37 tasks appeared. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 6%. 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 Adult Basic Education, Adult Secondary Education, and English as a Second Language Instructors?
- Anthropic's robot exposure rating (September 2026) finds 6% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 6% of the working time. Its index is 0.06 of 3. One example: Moxi for "provide students with disabilities with assistive devices, supportive technology, and assistance accessing facilities, such as restrooms". 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 37 tasks O*NET lists for the occupation, each with an estimated length checked against GDPval and a share of the working time, each classed as desk, people or body work, 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.
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