As of August 2026,
Teaching Assistants, Preschool, Elementary, Middle, and Secondary School, Except Special Education has an AI-exposure score of 49/100
(Elevated exposure) on the AI-Safe Careers index. This is an estimate of task
exposure, not a prediction of job loss.
Score inputs for this role:
This role starts from O*NET 29.1 occupational descriptors and is empirically grounded by Penn/OpenAI GPTs are GPTs study, Anthropic Economic Index (June 26, 2026). BLS labor-market figures are separate context, not score inputs.
Teaching Assistants, Preschool, Elementary, Middle, and Secondary School, Except Special Education
More exposed than 29% of the roles we track.
Will AI replace Teaching Assistants, Preschool, Elementary, Middle, and Secondary School, Except Special Education?
No exposure score can predict whether AI will replace this role. The 49/100 score means our current model estimates elevated task exposure from the sources listed on this page. It does not predict an employer decision, headcount, or an individual outcome. The task map below shows the work assessed and where human judgment remains important.
Early-career context (study ages 22-25)
This role is in the Elevated exposure band, but its assessed task mix is not automation-heavy. The study found the decline concentrated where AI was more likely to automate rather than augment work, so the headline figure should not be applied directly.
The November 2025 revision reports a 16% relative employment decline for workers ages 22-25 in the most AI-exposed U.S. occupations, after firm-level controls, relative to workers in less-exposed fields and more experienced workers in the same occupations.
Use the task map to identify durable work and the skills worth building early.
Stanford Digital Economy Lab, Canaries in the Coal Mine - November 2025 revision
This is group-level U.S. payroll evidence, not a personal forecast. The authors do not claim that AI alone caused the change, and this context does not alter the exposure score.
How this role compares to similar Education roles
What this role usually involves
Assist a preschool, elementary, middle, or secondary school teacher with instructional duties. Serve in a position for which a teacher has primary responsibility for the design and implementation of educational programs and services.
Broad guidance for this preparation level; exact requirements vary by role and employer.
Source: O*NET 29.1 exact occupation - Teaching Assistants, Preschool, Elementary, Middle, and Secondary School, Except Special Education, SOC 25-9042.00. Context describes the role; the AI-exposure score remains a separate task-exposure estimate.
Teaching Assistants, Preschool, Elementary, Middle, and Secondary School, Except Special Education tasks, by AI exposure
No automatable tasks identified for this role - its individually-assessed tasks split 90% durable / 10% augmentable.
- Type, file, and duplicate materials.
- Clean classrooms.
- Requisition and stock teaching materials and supplies.
- Observe students' performance, and record relevant data to assess progress.
We analyzed all 20 Teaching Assistants, Preschool, Elementary, Middle, and Secondary School, Except Special Education tasks - 2 augmentable and 18 durable. The full task map - every task with exactly what to do about each - is in your Career Report.
Your report unlocks three concrete artifacts
Every task scored with what to automate, augment, or protect.
Related roles with exposure deltas, salary, demand, and reachability. Lower-exposure options appear only when the data supports them.
A keepable roadmap plus resume and LinkedIn repositioning.
Grounded in O*NET-linked or curated role data, with Penn, Anthropic Economic Index, and AIOE signals where matched. BLS labor-market context is separate - not generic advice.
Adjacent career paths
No evidence-backed lower-exposure match appears in this O*NET adjacency set. The adjacent paths below remain useful comparisons; the strongest resilience moves are task-level.
Type, file, and duplicate materials.
Your AI-Safe Career Report
Every task scored with what to do about it; adjacent paths with honest exposure deltas, salary, demand, and reachability; a skill-gap map; a 30/60/90-day roadmap; Agent Reality Check; plus a résumé and LinkedIn rewrite and professional PDF.
Grounded in O*NET-linked or curated role data, with Penn, Anthropic Economic Index, and AIOE signals where matched. BLS labor-market context is separate.
Workers with AI skills earn a roughly 62% wage premium - adapting pays. - PwC Global AI Jobs Barometer, 2026
Generation starts after checkout; reports are typically ready within a few minutes.