Will AI replace Teaching Assistants, Postsecondary?
Work in Teaching Assistants, Postsecondary sits in the in-between: AI reaches some of it (~53% in theory) but is only measured doing about 10% today — part human, part machine.
O*NET-SOC 25-9044
How your 13 core tasks split
Top = what GPT-4 judged AI could speed up. Bottom = how much AI was actually used for these tasks (Anthropic's March 2026 report, usage from Aug & Nov 2025). The gap is the real story.
Back in 2023, GPT-4 judged AI could, in theory, assist with a moderate share of this job's tasks (~53%). By late 2025, real-world AI use had reached about 10% of its task activity (growing but still limited). The gap between that 2023 forecast and today is the real story.
Where this job sits among 738 jobs
Each dot is one of 738 U.S. jobs. Right = AI can do more of it. Up = AI is actually used more.
Read this as a range, not a verdict
The signals here partly disagree — AI's theoretical reach (~53%) and its real-world use (~10%) tell different stories. AI-risk scores also shift a lot by which model does the rating (2.7%–51.5% in one 2026 study), so this is a direction of travel, not a fixed answer.
See all 13 tasks, ratedBased on real task-level AI scores — click to collapse
- Develop teaching materials, such as syllabi, visual aids, answer keys, supplementary notes, or course Web sites.
- Inform students of the procedures for completing and submitting class work, such as lab reports.
- Return assignments to students in accordance with established deadlines.
- Meet with supervisors to discuss students' grades or to complete required grade-related paperwork.
- Notify instructors of errors or problems with assignments.
- Teach undergraduate-level courses.
- Evaluate and grade examinations, assignments, or papers, and record grades.
- Prepare or proctor examinations.
- Tutor or mentor students who need additional instruction.
- Order or obtain materials needed for classes.
- Lead discussion sections, tutorials, or laboratory sections.
- Schedule and maintain regular office hours to meet with students.
- Copy and distribute classroom materials.
How we measured this — and how fresh it is
AI's theoretical reach data: 2023
From GPTs-are-GPTs (Eloundou et al.), where GPT-4 rated how much of each task an AI tool could meaningfully speed up. This is the most recent open, commercially-usable occupation-level potential dataset — it dates to 2023. Newer multi-model re-runs exist but swing wildly (one 2026 study saw "high-risk" jobs range 2.7%–51.5% by model) and aren't openly licensed, so we show the stable 2023 baseline and pair it with newer real-world data.
Real-world AI use 2026 report
From the Anthropic Economic Index, which observes how real Claude conversations map onto each occupation's tasks. Published in Anthropic's March 2026 labor-market report, based on usage measured in Aug & Nov 2025 (Sonnet 4 / 4.5).
Task list & ratings O*NET 30.3
Tasks come from O*NET 30.3. Each task's "AI can do / speeds up / still on you" tier uses the real task-level exposure scores from GPTs-are-GPTs (E1 / E2 / E0) — not a guess from keywords.
Sources: O*NET 30.3 (CC BY 4.0) · GPTs-are-GPTs (MIT, 2023) · Anthropic Economic Index (CC BY, Aug & Nov 2025). Page compiled June 2026. "O*NET" is a trademark of the U.S. Department of Labor.
This page is for general informational purposes only and is not career, financial, or employment advice. AI exposure reflects research estimates of task overlap, not predictions about any individual's job, employer, or future employment.