How much of this occupation’s work can be materially affected by current AI systems.
How likely exposure is to translate into reduced human demand.
Includes provisional estimates for AI adoption pressure and labour-market resilience. How this is measured
Confidence reflects task coverage, mapping and capability-evidence quality, and how much of the score rests on provisional inputs.
What is driving the score?
Occupation scores are built from the task mix—not a single prediction about a job title.
Where AI can do more
Routine, digitized, and highly repeatable tasks face the greatest pressure.
- Instruct through lectures, discussions, and demonstrations in one or more subjects, such as English, mathematics, or social studies.75
- Prepare objectives and outlines for courses of study, following curriculum guidelines or requirements of states and schools.75
- Prepare for assigned classes, and show written evidence of preparation upon request of immediate supervisors.75
- Prepare, administer, and grade tests and assignments to evaluate students' progress.74
Where people still matter
These tasks score lowest on automation feasibility—physical presence, judgement, accountability and real-world variability all resist end-to-end automation.
- Perform administrative duties, such as school library assistance, hall and cafeteria monitoring, and bus loading and unloading.01
- Confer with parents or guardians, other teachers, counselors, and administrators to resolve students' behavioral and academic problems.02
- Adapt teaching methods and instructional materials to meet students' varying needs and interests.03
- Guide and counsel students with adjustments, academic problems, or special academic interests.04
- Instruct through lectures, discussions, and demonstrations in one or more subjects, such as English, mathematics, or social studies.05
Related occupations
Occupations O*NET links to this one. Relatedness reflects shared work, not a claim that these roles are safer.
Middle School Teachers, Except Special and Career/Technical Education
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Related work
Compare these careers →Adoption and labour-market outlook
Structural factors are kept separate from raw capability so you can see what actually resists automation. Adoption pressure and labour-market resilience are still provisional models—25% of this occupation’s replacement-risk weight rests on them.
O*NET 30.3 occupational data interpreted through the JobsVsAI capability, automation and structural-constraint models.
