AI Delegation Index

AI Delegation Index

What work could you hand off to an AI agent?

Career/Technical Education Teachers, Secondary School

Limited

AI agents could help with a focused set of planning and documentation tasks, while hands-on work and judgment remain human-led.

Where agents can help most

  1. 1

    Manage classroom behavior and document issues

    Use an agent to turn your behavior notes, class rules, and incident logs into a running record for a section, lab, or project block.

  2. 2

    Grade assessments and assign practice

    Use an agent to grade completed work, sort common mistakes, and draft extra practice for students who need another try.

  3. 3

    Draft guidance for lab skills and check safety

    Use an agent to turn your lesson plan, equipment list, and safety notes into a classroom setup checklist before lab time.

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O*NET-SOC 25-2032.00 · #474 of 923

Result context

How to read this result

Teach occupational, vocational, career, or technical subjects to students at the secondary school level.

National position
#474 of 923 occupations
Top 52% of occupations
Overall AI delegation potential
Limited
Potential of score-contributing workflows
Moderate · 67/100
Meaningful work covered
50%

The overall rating combines how useful the best agent workflows are with how much of the occupation they address. It is not an estimate of job automation or replacement.

Recommended agent uses

3 workflows you could delegate to AI

1

Manage classroom behavior and document issues

How you could use an agent

Use an agent to turn your behavior notes, class rules, and incident logs into a running record for a section, lab, or project block. You provide the behavior concerns and follow-up notes; it helps you draft the report, track repeat issues, and prepare a summary for administration or student support staff.

Where you stay involved

You decide how to address the behavior in class, apply the school rules, and choose when a matter needs admin support. You keep the classroom moving while documenting serious or repeated problems accurately.

Review level: High

2

Grade assessments and assign practice

How you could use an agent

Use an agent to grade completed work, sort common mistakes, and draft extra practice for students who need another try. You supply the assignment, rubric notes, and marked-up work; it summarizes gaps, prepares a redo or practice set, and helps you track who needs more help.

Where you stay involved

You review the grading, decide what feedback to give, and choose the right follow-up work for each student. You refer concerns that may need formal support services to the proper school staff.

Review level: Medium

3

Draft guidance for lab skills and check safety

How you could use an agent

Use an agent to turn your lesson plan, equipment list, and safety notes into a classroom setup checklist before lab time. You provide the project goals and materials; it helps you prepare the room, draft the step-by-step teaching notes, and record any safety reminders for the class.

Where you stay involved

You set up the room, teach the lesson, watch how students use the tools, and decide when someone needs a closer correction. You handle injuries, equipment problems, or unsafe behavior right away through the school’s normal channels.

Review level: High

Supporting analysis

Why this occupation's AI delegation potential is Limited

Underlying methodology score

60 / 100

This technical score determines the qualitative rating; it is not an estimate of the share of the occupation that can be automated.

Importance & frequency82
AI capability75
Digital actionability59
End-to-end leverage63
Safety & reversibility56
Meaningful-work coverage
50%
Physical-work modifier
Limited
Safety modifier
Moderate
Qualitative judgment
No material constraint
O*NET task evidence
33 tasks

O*NET 31.0 · methodology 3.3.0. Every workflow passes an action-level physical-execution and protected human-and-veterinary clinical-action gate. Documentation workflows must own a complete digital loop and use digital task evidence only; support-only workflows are disclosed separately and excluded from scoring. Artistic, editorial, normative, and policy-dependent work receives a transparent human-judgment constraint. National ranking within 923 scored O*NET occupations under methodology 3.3.0.

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