Preschool Teachers, Except Special Education
In short: today's best AI models could do about 24% 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 conversations, in-person and hands-on work, about 76% of the time, stays with people.
Instruct preschool-aged students, following curricula or lesson plans, in activities designed to promote social, physical, and intellectual growth.
478,780 people do this job in the US. $38,140 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 on2 h
- A person checks AI's work8 h
- Desk work AI can't do yet0 h
- Stays with people30 h
Preschool Teachers, Except Special Education, now: of a 40-hour week, AI could take on 2 hours, 8 hours become checking its work, 0 hours are desk work it can't do yet, and 30 hours stay with people.
The largest pieces: Adapt methods and materials to students (about 3 h, a person checks); Keep student records (under an hour, a person checks); Prepare materials and classrooms (under an hour).
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.
- 20%
- 4%
- 4%
- 51%
- 22%
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.
What handing it over would take, now
The 24% within reach splits by what a model would need. The dates, pace and reliability follow the controls above. Estimates.
of the working time. The material can be handed to a model and the result handed back.
of the working time. The model has to be connected to the system the work lives in.
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, 20%. Today's estimate: 24%.
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, 0.00096% went to this job's tasks in May 2026, the 447th largest of the 447 jobs that showed up at all; 1 of its 34 tasks showed up. Within each of Anthropic's methods, never across a change: 0.04% to 0.038% (released February and March 2025); 0.014% to 0.017% (August 2025 to February 2026); 0.001% to 0.00096% (April to May 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.04% | 307 of 708 | 11 of 34 |
| Released March 2025 | 0.038% | 316 of 703 | 11 of 34 |
| The week of Aug 4, 2025 (released September 2025) | 0.014% | 417 of 655 | 8 of 34 |
| The week of Nov 13, 2025 (released January 2026) | 0.028% | 336 of 672 | 13 of 34 |
| The week of Feb 5, 2026 (released March 2026) | 0.017% | 418 of 677 | 10 of 34 |
| April 2026 (released June 2026) | 0.001% | 434 of 434 | 1 of 34 |
| May 2026 (released June 2026) | 0.00096% | 447 of 447 | 1 of 34 |
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 62% of this job's working time as physical work. For 18% of the working time, a robot has been shown doing most of the task somewhere: 18% in a purpose-built cell. 0.18 of 3, the 458th highest of the 923 jobs.
- Not physical 38%
- No robot shown 44%
- In a purpose-built cell 18%
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
75% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Teach basic skills, the in-person work, 8%
- Lead games, crafts, music and storytelling, the in-person work, 7%
- Provide materials for children to explore, the hands-on work, 6%
- Set and enforce classroom rules, the in-person work, 5%
- Feed, dress and change children, the hands-on work, 5%
- Plan and supervise projects and field trips, the in-person work, 4%
What becomes checking the machine
19% 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 4% is desk work that is small if wrong, which can be handed over with lighter checks.
- Adapt methods and materials to students, costly if wrong, 7%
- Keep student records, costly if wrong, 2%
- Prepare reports on students, costly if wrong, 2%
- Plan and supervise projects and field trips, costly if wrong, 2%
- Plan and conduct a balanced program, costly if wrong, 2%
- Set lesson objectives and share them, costly if wrong, 1%
What to learn
- The conversations. About 54% of the time is conversation and in-person work, which this site leaves with people: listening, explaining, persuading, calming.
- Dealing with people outside the organization. Customers, patients, suppliers or the public: trust with them is built by a 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: spotting what a draft gets wrong is a skill of its own.
- The hands-on craft. About 22% of the time is hands-on work, which no model here does; robots are rated separately on this page.
- Briefing a model and checking its drafts. About 20% 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.
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 . 34 tasks from .
| Task | ||||
|---|---|---|---|---|
| Adapt teaching methods and instructional materials to meet students' varying needs and interests.Reworking materials, and trying them with the children.Done daily by most who do it. AI observed on this task. | 10% | 1.1 h25 min to 2.1 h | Documents 70%, in person 30% | 70%Desk part half by now |
| Teach basic skills, such as color, shape, number and letter recognition, personal hygiene, and social skills.Teaching a room of children.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 8% | 38 min17 min to 1.3 h | In person 100% | Stays with people |
| Organize and lead activities designed to promote physical, mental, and social development, such as games, arts and crafts, music, storytelling, and field trips.Leading a room of children.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 7% | 50 min25 min to 2.1 h | In person 100% | Stays with people |
| Provide a variety of materials and resources for children to explore, manipulate, and use, both in learning activities and in imaginative play.Setting out materials and helping children use them.Done daily by most who do it. Robots: in a purpose-built cell, RightPick (RightHand Robotics) (sold). Anthropic's rating. | 6% | 38 min17 min to 1.7 h | Hands-on 70%, in person 30% | Stays with people |
| Plan and supervise class projects, field trips, visits by guests, or other experiential activities and guide students in learning from those activities.Leading children in person, with the planning behind it.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 6% | 2.5 h50 min to 5 h | In person 70%, documents 30% | 30%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.Robots: no robot shown. Anthropic's rating. | 5% | 1.3 h38 min to 2.5 h | In person 70%, documents 30% | 30%Desk part half by now |
| Establish and enforce rules for behavior and procedures for maintaining order.Keeping order in a room of children.Done daily by most who do it. | 5% | 25 min13 min to 50 min | In person 100% | Stays with people |
| Attend to children's basic needs by feeding them, dressing them, and changing their diapers.Hands-on care.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 5% | 33 min13 min to 50 min | Hands-on 100% | Stays with people |
| Arrange indoor and outdoor space to facilitate creative play, motor-skill activities, and safety.Moving furniture and equipment, to a plan.Done daily by most who do it. Robots: in a purpose-built cell, RightPick (RightHand Robotics) (sold). Anthropic's rating. | 4% | 38 min17 min to 1.3 h | Hands-on 80%, documents 20% | 20%Desk part half by now |
| Select, store, order, issue, and inventory classroom equipment, materials, and supplies.Handling and counting supplies, with the order.Done more than monthly by most who do it. Robots: in a purpose-built cell, Amazon Vulcan (deployed). Anthropic's rating. | 4% | 1.3 h25 min to 3.3 h | Hands-on 50%, systems 30%, documents 20% | 50%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, RightPick (RightHand Robotics) (deployed). Anthropic's rating. | 3% | 33 min17 min to 1.1 h | Documents 60%, hands-on 40% | 60%Desk part half by now |
| Organize and label materials and display students' work in a manner appropriate for their ages and perceptual skills.Arranging the room by hand.Done daily by most who do it. AI observed on this task.Robots: in a purpose-built cell, Amazon Sparrow (deployed). Anthropic's rating. | 3% | 38 min17 min to 1.3 h | Hands-on 100% | Stays with people |
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.
- Kindergarten Teachers, Except Special Education23% now, 23% by 2028
- Special Education Teachers, Kindergarten34% now, 34% by 2028
- Elementary School Teachers, Except Special Education35% now, 35% by 2028
- Special Education Teachers, Preschool25% now, 26% by 2028
- Special Education Teachers, Secondary School36% now, 36% 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 Preschool Teachers, Except Special Education is within reach of AI now?
- An estimated 24% of the working time is within reach of AI models now and 24% 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 Preschool Teachers, Except Special 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: Adapt methods and materials to students (70% of the task's time now); Keep student records (100% of the task's time now); and Prepare materials and classrooms (60% of the task's time now).
- Which tasks of Preschool Teachers, Except Special Education stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Teach basic skills; Lead games, crafts, music and storytelling; and Provide materials for children to explore. Together such tasks are about 51% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Preschool Teachers, Except Special 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; dealing with people outside the organization; and reviewing work you did not do yourself. By the end of 2028 on the long-run pace at four in five, about 75% of the working time stays with people, 19% becomes checking a model's work and 4% 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 Preschool Teachers, Except Special Education?
- In the Claude.ai conversations Anthropic sampled for May 2026 and tied to a work task, 0.00096% went to this job's tasks, the 447th largest share of the 447 jobs that showed up; 1 of its 34 tasks appeared. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 0%. 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 Preschool Teachers, Except Special Education?
- Anthropic's robot exposure rating (September 2026) finds 62% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 18% of the working time. Its index is 0.18 of 3. One example: RightPick (RightHand Robotics) for "provide materials for children to explore". 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 34 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.
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