Teaching Assistants, Special Education
In short: today's best AI models could do about 5% 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 95% of the time, stays with people.
Assist a preschool, elementary, middle, or secondary school teacher to provide academic, social, or life skills to students who have learning, emotional, or physical disabilities. Serve in a position for which a teacher has primary responsibility for the design and implementation of educational programs and services.
$36,780 a year (for the broader BLS group this job sits in).
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 on1 h
- A person checks AI's work1 h
- Desk work AI can't do yet0 h
- Stays with people38 h
Teaching Assistants, Special Education, now: of a 40-hour week, AI could take on 1 hours, 1 hours become checking its work, 0 hours are desk work it can't do yet, and 38 hours stay with people.
The largest pieces: Prepare lesson outlines and plans (under an hour); Observe students and record progress (under an hour, a person checks); Grade homework and record results (under an hour, 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.
of the working time. Now is projected from METR's April 2026 measurement and Epoch's November 2026 index.
- 3%
- 2%
- 2%
- 65%
- 28%
Anthropic's data does not cover this job.
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 5% 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, 5%. Today's estimate: 5%.
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, 0.0053% went to this job's tasks in May 2026, the 445th largest of the 447 jobs that showed up at all; 1 of its 30 tasks showed up. Within each of Anthropic's methods, never across a change: 0.053% to 0.022% (released February and March 2025); 0.062% to 0.047% (August 2025 to February 2026); 0.0057% to 0.0053% (April to May 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.053% | 271 of 708 | 7 of 30 |
| Released March 2025 | 0.022% | 402 of 703 | 3 of 30 |
| The week of Aug 4, 2025 (released September 2025) | 0.062% | 211 of 655 | 5 of 30 |
| The week of Nov 13, 2025 (released January 2026) | 0.071% | 195 of 672 | 8 of 30 |
| The week of Feb 5, 2026 (released March 2026) | 0.047% | 257 of 677 | 8 of 30 |
| April 2026 (released June 2026) | 0.0057% | 423 of 434 | 1 of 30 |
| May 2026 (released June 2026) | 0.0053% | 445 of 447 | 1 of 30 |
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 54% of this job's working time as physical work. For 10% of the working time, a robot has been shown doing most of the task somewhere: 10% in a purpose-built cell. 0.10 of 3, the 516th highest of the 923 jobs.
- Not physical 46%
- No robot shown 44%
- In a purpose-built cell 10%
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
94% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Assist students with special needs, the in-person work, 16%
- Supervise students around the school, the in-person work, 11%
- Teach acceptable behavior, the in-person work, 10%
- Carry out therapeutic regimens, the in-person work, 7%
- Use special teaching strategies, the in-person work, 6%
- Teach daily living skills, the in-person work, 5%
What becomes checking the machine
2% 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 3% is desk work that is small if wrong, which can be handed over with lighter checks.
- Observe students and record progress, costly if wrong, 0.9%
- Grade homework and record results, costly if wrong, 0.8%
What to learn
- The conversations. About 67% 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.
- The hands-on craft. About 28% of the time is hands-on work, which no model here does; robots are rated separately on this page.
- 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.
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 . 30 tasks from .
| Task | ||||
|---|---|---|---|---|
| Provide assistance to students with special needs.Hands-on help and patient attention to the child.Done hourly or more by most who do it. Robots: no robot shown. Anthropic's rating. | 16% | 38 min17 min to 1.7 h | In person 50%, hands-on 50% | Stays with people |
| Supervise students in classrooms, halls, cafeterias, school yards, and gymnasiums, or on field trips.Being present with children.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 11% | 38 min17 min to 2.5 h | In person 60%, hands-on 40% | Stays with people |
| Teach socially acceptable behavior, employing techniques such as behavior modification or positive reinforcement.Working with a child in person, moment by moment.Done daily by most who do it. | 10% | 38 min13 min to 1.3 h | In person 100% | Stays with people |
| Carry out therapeutic regimens, such as behavior modification and personal development programs, under the supervision of special education instructors, psychologists, or speech-language pathologists.Working with the child in person, under a specialist's supervision.Done daily by most who do it. | 7% | 50 min25 min to 1.7 h | In person 80%, hands-on 20% | Stays with people |
| Employ special educational strategies or techniques during instruction to improve the development of sensory- and perceptual-motor skills, language, cognition, or memory.Teaching a child in person, adapting as it goes.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 6% | 50 min17 min to 2.1 h | In person 100% | Stays with people |
| Instruct students in daily living skills required for independent maintenance and self-sufficiency, such as hygiene, safety, or food preparation.Showing and practicing with the student in person.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 5% | 50 min25 min to 1.7 h | In person 80%, hands-on 20% | Stays with people |
| Organize and supervise games and other recreational activities to promote physical, mental, and social development.Leading children's activities in person.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 5% | 50 min25 min to 1.7 h | In person 100% | Stays with people |
| Provide students with disabilities with assistive devices, supportive technology, and assistance accessing facilities, such as restrooms.Hands-on help and a steadying presence.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 5% | 33 min17 min to 1.3 h | Hands-on 60%, in person 40% | Stays with people |
| Enforce administration policies and rules governing students.Dealing with children in person.Done daily by most who do it. | 4% | 17 min8 min to 38 min | In person 100% | Stays with people |
| Tutor and assist children individually or in small groups to help them master assignments and to reinforce learning concepts presented by teachers.Teaching children in person.Done daily by most who do it. AI observed on this task. | 3% | 25 min13 min to 50 min | In person 100% | Stays with people |
| Prepare classrooms with a variety of materials or resources for children to explore, manipulate, or use in learning activities or imaginative play.Setting out materials by hand, to a plan.Done daily by most who do it. Robots: in a purpose-built cell, RightHand Robotics RightPick (deployed). Anthropic's rating. | 3% | 38 min17 min to 1.7 h | Hands-on 80%, documents 20% | 20%Desk part half by now |
| Present subject matter to students under the direction and guidance of teachers, using lectures, discussions, supervised role-playing methods, or by reading aloud.Teaching a room of children.Done daily by most who do it. | 3% | 25 min13 min to 50 min | In person 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.
- Special Education Teachers, Kindergarten34% now, 34% by 2028
- Special Education Teachers, Secondary School36% now, 36% by 2028
- Special Education Teachers, Elementary School40% now, 40% by 2028
- Teaching Assistants, Preschool, Elementary, Middle, and Secondary School, Except Special Education8% now, 8% by 2028
- Special Education Teachers, Middle School40% now, 40% by 2028
- Instructional Coordinators39% now, 68% by 2028
Where this job works
The industry groups that employ the most of it (BLS, May 2025). Counts are for the broader BLS group this job sits in.
Where the most of these jobs are
The metro areas with the most people in it (BLS, May 2025). Counts are for the broader BLS group this job sits in.
Questions about this job
- How much of the work of Teaching Assistants, Special Education is within reach of AI now?
- An estimated 5% of the working time is within reach of AI models now and 5% 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 Teaching Assistants, 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: Prepare lesson outlines and plans (100% of the task's time now); Observe students and record progress (40% of the task's time now); and Grade homework and record results (100% of the task's time now).
- Which tasks of Teaching Assistants, Special Education stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Assist students with special needs; Supervise students around the school; and Teach acceptable behavior. Together such tasks are about 89% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Teaching Assistants, 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 the hands-on craft. By the end of 2028 on the long-run pace at four in five, about 94% of the working time stays with people, 2% becomes checking a model's work and 3% 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 Teaching Assistants, Special Education?
- In the Claude.ai conversations Anthropic sampled for May 2026 and tied to a work task, 0.0053% went to this job's tasks, the 445th largest share of the 447 jobs that showed up; 1 of its 30 tasks appeared. 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 Teaching Assistants, Special Education?
- Anthropic's robot exposure rating (September 2026) finds 54% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 10% of the working time. Its index is 0.10 of 3. One example: RightHand Robotics RightPick for "set up the classroom with materials". 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 30 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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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.