Headline risk
12%
Low RiskSelf-enrichment teachers
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
Teach or instruct individuals or groups for the primary purpose of self-enrichment or recreation, rather than for an occupational objective, educational attainment, competition, or fitness.
Task evidence
100% weighted task match · 18% effective coverage
Scores combine AI task overlap, human advantages, and local demand. How it works
United States Now
Median Wage
USD 45,590
Employment 2024
417.5K
Projected Change (2024–34)
3.7%
Openings (2024–34)
51.4K
Wage distribution
Demand outlook
Projections published, but no prose outlook available.
Role Profile
Tasks
- 1. Instruct students individually and in groups, using various teaching methods, such as lectures, discussions, and demonstrations. AI use: 0%
- 2. Prepare students for further development by encouraging them to explore learning opportunities and to persevere with challenging tasks. AI use: 0%
- 3. Adapt teaching methods and instructional materials to meet students' varying needs and interests. AI use: 82%
- 4. Monitor students' performance to make suggestions for improvement and to ensure that they satisfy course standards, training requirements, and objectives. AI use: 0%
- 5. Observe students to determine qualifications, limitations, abilities, interests, and other individual characteristics. AI use: 0%
- 6. Establish clear objectives for all lessons, units, and projects and communicate those objectives to students. AI use: 0%
Technologies
Requirements
Work context
Worker profile
Median age 49.2 · 1.1M employed
Under 25: 3% · 25–54: 60% · 55+: 36%
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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
title_match · 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.