Headline risk
15%
Moderate RiskTeaching assistants, postsecondary
United States AI Work Index tracks this occupation on the shared structural baseline and then layers on local demand resilience, wages, and confidence.
Why This Score
Share of job tasks that overlap with current AI capabilities
Median annual wage
Projected employment change over 10 years
Typical preparation needed for this occupation
Occupation profile
Assist faculty or other instructional staff in postsecondary institutions by performing instructional support activities, such as developing teaching materials, leading discussion groups, preparing and giving examinations, and grading examinations or papers.
Task evidence
100% weighted task match · 12% effective coverage
Scores combine AI task overlap, human advantages, and local demand. How it works
United States Now
Median Wage
USD 44,930
Employment 2024
193.6K
Projected Change (2024–34)
3.1%
Openings (2024–34)
24.6K
Wage distribution
Demand outlook
Projections published, but no prose outlook available.
Role Profile
Tasks
- 1. Evaluate and grade examinations, assignments, or papers, and record grades. AI use: 0%
- 2. Teach undergraduate-level courses. AI use: 0%
- 3. Develop teaching materials, such as syllabi, visual aids, answer keys, supplementary notes, or course Web sites. AI use: 86%
- 4. Tutor or mentor students who need additional instruction. AI use: 0%
- 5. Return assignments to students in accordance with established deadlines. AI use: 0%
- 6. Inform students of the procedures for completing and submitting class work, such as lab reports. AI use: 0%
Technologies
Requirements
Work context
Worker profile
Median age 38.0 · 1.5M employed
Under 25: 21% · 25–54: 59% · 55+: 19%
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Source coverage
11/11 source families · O*NET 30.2 / OEWS 2024 / ORS 2025 / OOH 2025-08-28 / Projections 2024-34 / CPS 2025 / Anthropic task penetration
Mapping quality
major_group_fallback · employment series present
Narrative & sources
Published limitations
This page shows the local country layer, not realised individual job outcomes. The global structural baseline is shared across countries; only the local demand and wage layer changes here.
Built from O*NET occupation descriptions, task statements, technology skills, work context, Job Zones, Anthropic task penetration, BLS OEWS wages, BLS projection tables, BLS ORS requirements, BLS OOH narrative content, BLS skills data, and BLS CPS occupation age tables.