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Will AI replace Self-Enrichment Teachers?

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. The percentage shown is a task-exposure model, not a prediction of certain job loss.

O*NET 30.3 · 25-3021.00 · modeled exposure, not guaranteed job loss
LOW TASK EXPOSURE
27%
Estimated share of representative tasks exposed to current AI capabilities.
Task automation shareⓘ
27%Automatable
Automatable27%
Augmentable40%
Hard to automate33%
Based on analysis of representative responsibilities and current AI capability maturity.
Category#
Education
Teaching & Research
Modeled pay midpoint$
$72,500/yr
Directional estimate — verify locally
Time until impact⌁
6–10+ years
Earliest 2032 · widespread 2036+
Task-level replaceability ⓘ
Representative tasks ranked from highest to lowest AI exposure.
◇Instruct students individually and in groups, using various teaching methods, such as lectures, discussions, and demonstrations.37%
⚙Adapt teaching methods and instructional materials to meet students' varying needs and interests.31%
✦Mentorship and classroom judgment25%
▥Prepare students for further development by encouraging them to explore learning opportunities and to persevere with challenging tasks.24%
✦Adapting to individual learners21%
Impact timeline ⓘ
How AI assistance may move from early support to wider adoption.
2032Next2036+
Light supportAI provides limited help with instruct students individually and in groups, using various teaching methods, such as lectures, discussions, and demonstrations..
AugmentationTools improve productivity without owning outcomes.
Human-ledCore work stays anchored in mentorship and classroom judgment.
6–10+ yearsdirectional confidence window
HOW AI CHANGES THIS JOBtyping the logic in plain English
01>Start with the real work done by Self-Enrichment Teachers.
02>AI can help with: Instruct students individually and in groups, using various teaching methods, such as lectures, discussions, and demonstrations.
03>If a task is repetitive and easy to check, AI pressure goes up.
04>But a person is still needed for: Mentorship and classroom judgment.
05>Likely result: AI mostly acts as a helper while the core job stays human-led.
06>Important: 27% is estimated task exposure—not a 27% chance of losing the job.
What AI can do
Instruct students individually and in groups, using various teaching methods, such as lectures, discussions, and demonstrations.LOW MATCH
Adapt teaching methods and instructional materials to meet students' varying needs and interests.LOW MATCH
Prepare students for further development by encouraging them to explore learning opportunities and to persevere with challenging tasks.LOW MATCH
How estimates work →
Your human moat
◆

Mentorship and classroom judgment

MEDIUM-HIGH

Combined with adapting to individual learners, this keeps a human in the loop.

Strength8.4
Similar-role comparison
RoleRisk
Self-Enrichment Teachers27%
Chemistry Teachers, Postsecondary27%
Library Technicians26%
Law Teachers, Postsecondary28%
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Why this score?

✓The model evaluates 3 representative core tasks.
✓The core work depends on presence, dexterity, or accountability.
✓Occupation and task language comes from O*NET 30.3.
✓The strongest human advantage is mentorship and classroom judgment.
Research basis

O*NET 30.3 occupation tasks plus the ILO 2025 exposure framework. Scores are directional estimates.

Read ILO research →
Data: O*NET 30.3 · Model framework: ILO 2025About O*NETShare report
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Chemistry Teachers, Postsecondary · 27% exposureLibrary Technicians · 26% exposureLaw Teachers, Postsecondary · 28% exposure