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AI Automation Index
Will AI Replace Tutors?
Task-level automation exposure for Tutors: 19 O*NET tasks scored against their work activities, plus the simulator.
E-E-A-T Verified
Developed & audited by Gini Loh Automation Exposure
58%
weighted task index
19 of 19 tasks scored
Median Salary
$43,350 / year
BLS OEWS, May 2025 — this exact occupation
Employment Level
High
175,070 people hold this job — size, not growth
Projected 2025–35
-0.2%
employment change
34,200 openings a year · BLS line item
Pay by state
BLS OEWS publishes 52 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.
$30,410 – $82,290
Highest medians
Wyoming $82,290
Rhode Island $77,850
Massachusetts $60,900
Vermont $53,920
New Hampshire $53,790
Lowest medians
Guam $30,410
Nevada $30,420
Arkansas $30,830
Missouri $32,270
South Carolina $33,220
State figures come from the 25-3041 row in the May 2025 state panel. States where the estimate was suppressed or too small to publish are absent.
What the score is made of
Each task is mapped to its work activities, scored for AI automation potential, and weighted by how important those activities are to the job. These are the components.
Automation potential 58%
Importance-weighted mean of the scored tasks. This is the headline index.
Physical work 0%
Share of weighted tasks in hands-on or machine-operating work activities.
Judgment & influence 67%
Share in analysis, decisions, teaching, directing, advising, or caring for others.
Routine administration 20%
Share in documenting, recording, and administrative activities.
Rewritten by O*NET 0%
Share of weighted tasks O*NET rewrote in a recent update. Reported, not folded into the score.
Consequence of error 0/100
Low
O*NET's own rating of how serious an uncorrectable mistake would be here — respondents, not us. Deliberately not in the index: the score measures what AI can do with the task content, and multiplying it by stakes would be our judgment dressed as data.
Constituent Task Mix
19 tasks for this occupation, weighted by work-activity importance. Shares below are of total task weight, not task count.
High exposure (≥ 60% of the task is automatable) 41%
8 tasks
Medium exposure (≥ 35%) 47%
9 tasks
Low exposure (below 35%) 12%
2 tasks
How would you survive?
Move your week away from the high-exposure tasks and toward the ones that need judgment. The simulator recalculates the index as you shift the mix.
Simulate Upskilling →Constituent Tasks
#17027 · Core · 22% automatable
Provide feedback to students, using positive reinforcement techniques to encourage, motivate, or build confidence in students.
interpersonal — Genuine student encouragement is relational and human
Encourage students.
#17026 · Core · 56% automatable
Review class material with students by discussing text, working solutions to problems, or reviewing worksheets or other assignments.
text generation — Drafting project updates is AI-assisted; delivery is human
Communicate project information to others. Apply multiple teaching methods.
#17034 · Core · 70% automatable
Assess students' progress throughout tutoring sessions.
decision support — Grading aided; rubric judgment and accountability human
Evaluate student work.
#17036 · Core · 55% automatable
Teach students study skills, note-taking skills, and test-taking strategies.
interpersonal — AI can tutor content; diagnosing learner needs is human
Tutor students who need extra assistance.
#17037 · Core · 55% automatable
Provide private instruction to individual or small groups of students to improve academic performance, improve occupational skills, or prepare for academic or occupational tests.
interpersonal — AI can tutor content; diagnosing learner needs is human
Tutor students who need extra assistance.
#17023 · Core · 18% automatable
Participate in training and development sessions to improve tutoring practices or learn new tutoring techniques.
interpersonal — Attending meetings requires physical human presence
Attend training sessions or professional meetings to develop or maintain professional knowledge.
#17033 · Core · 55% automatable
Collaborate with students, parents, teachers, school administrators, or counselors to determine student needs, develop tutoring plans, or assess student progress.
decision support — Needs student interaction and professional judgment
Assess educational needs of students. Collaborate with other teaching professionals to develop educational programs.
#17025 · Core · 62% automatable
Monitor student performance or assist students in academic environments, such as classrooms, laboratories, or computing centers.
data analysis — AI grades and tracks metrics; human interprets holistically
Monitor student performance.
#17020 · Core · 68% automatable
Schedule tutoring appointments with students or their parents.
data analysis — AI builds instructional schedules; human adjusts
Schedule instructional activities.
#17024 · Core · 82% automatable
Organize tutoring environment to promote productivity and learning.
text generation — Organize and structure informational materials
Organize informational materials.
#17032 · Core · 50% automatable
Communicate students' progress to students, parents, or teachers in written progress reports, in person, by phone, or by email.
interpersonal — Progress discussions need relationship and judgment
Discuss student progress with parents or guardians.
#17029 · Core · 78% automatable
Maintain records of students' assessment results, progress, feedback, or school performance, ensuring confidentiality of all records.
data analysis — Maintain structured student records in databases
Maintain student records.
#17030 · Core · 45% automatable
Identify, develop, or implement intervention strategies, tutoring plans, or individualized education plans (IEPs) for students.
decision support — AI suggests strategies; individualized special-needs judgment human
Develop strategies or programs for students with special needs.
#17022 · Core · 55% automatable
Prepare and facilitate tutoring workshops, collaborative projects, or academic support sessions for small groups of students.
interpersonal — AI can tutor content; diagnosing learner needs is human
Tutor students who need extra assistance.
#17028 · Core · 80% automatable
Prepare lesson plans or learning modules for tutoring sessions according to students' needs and goals.
text generation — Draft lesson plans from curriculum inputs
Document lesson plans.
#17031 · Core · 80% automatable
Develop teaching or training materials, such as handouts, study materials, or quizzes.
text generation — Develop instructional materials; human reviews
Develop instructional materials.
#17019 · Supplemental · 55% automatable
Travel to students' homes, libraries, or schools to conduct tutoring sessions.
interpersonal — AI can tutor content; diagnosing learner needs is human
Tutor students who need extra assistance.
#17035 · Supplemental · 57% automatable
Administer, proctor, or score academic or diagnostic assessments.
decision support — Grading aided; rubric judgment and accountability human
Administer tests to assess educational needs or progress. Evaluate student work.
#17021 · Supplemental · 60% automatable
Research or recommend textbooks, software, equipment, or other learning materials to complement tutoring.
interpersonal — Career guidance drafted; mentor relationship human
Advise students on academic or career matters.
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How this was scored
- 1. Tasks. O*NET task statements for this occupation, from a release whose newest record is dated 08/2026.
- 2. Work activities. Each task maps to 1–5 Detailed Work Activities; each activity belongs to one of 41 Generalized Work Activities that O*NET rates for importance (1–5) in this occupation.
- 3. Automation potential. Every work activity carries one score for how far current AI can perform it end-to-end. Tasks inherit the mean of their activities.
- 4. Weighting. Task weight = 0.35 + 0.65 × (importance − 1)/4, scaled by how often the task is performed and by 0.7 for Supplemental tasks. Importance is the task's own O*NET rating where it exists (18,369 of 18,838 tasks); the rest inherit their work activities' importance. The index is the weighted mean.
Check: across the 910 occupations where O*NET also rates how far machine speed sets the pace, this index moves opposite to it (Spearman ρ = -0.49). The more a job is paced by equipment, the less of its task content AI can address — the relationship you would expect if the scoring is working.
Sources · O*NET 31.0 (task records to 08/2026) · BLS OEWS May 2025 · BLS projections 2025-2035 · rubric v2.1 · tasks for O*NET, not a forecast
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