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Comparison · dataset August 2026

University Professor vs High-school Teacher: which is more exposed to AI?

University Professor carries 11 points more AI exposure than High-school Teacher.

University Professor sits at 40% time-weighted AI exposure against 29% for High-school Teacher, an 11-point gap driven by the 24% of university professor work time that current models can already substitute outright. High-school Teacher holds a larger human-critical core — 57% of the role's time sits in work like "behavioral and emotional support" that models score poorly on. Both roles sit inside Education, so the exposure difference reflects task design rather than a change of field.

11PP GAP

Seven dimensions, side by side.

METRICUNIVERSITY PROFESSORHIGH-SCHOOL TEACHERDELTA
AI exposure40%29%11pp gap
Resilience score76/10082/1006pt gap
Substitutable work time24%20%Fully automatable today
Human-critical work time54%57%Models score poorly here
Median salary$88k$62k$26k apart
10-year growth2%1%University Professor
US workforce812k1.0MBLS OEWS
Task level

What actually creates the gap.

Both roles hand a similar slice of the week to substitutable work — 24% for University Professors, 20% for High-school Teachers — but it is different work. University Professor exposure concentrates in "conduct literature reviews"; High-school Teacher exposure concentrates in "draft assessments and quizzes". Two roles can share a score and face completely different disruption timelines.

University Professor
MOST EXPOSED TASKS
  • Conduct literature reviews82% · 10% time
  • Write and update course materials74% · 14% time
HUMAN-CRITICAL CORE
  • Mentor PhD and graduate students8% · 14% time
  • Academic governance and committees14% · 6% time
  • Original research and publication18% · 12% time
High-school Teacher
MOST EXPOSED TASKS
  • Draft assessments and quizzes78% · 8% time
  • Create lesson plans and curricula74% · 12% time
HUMAN-CRITICAL CORE
  • Behavioral and emotional support6% · 11% time
  • Student mentorship and support8% · 14% time
  • Parent and community engagement11% · 8% time
What transfers

Both roles lean on social, judgement, cognitive — that is the part of your experience that travels intact. The real divide is cognitive: University Professors score 92 there against 61 for High-school Teachers, a 31-point spread. That is the gap you would actually have to close.

DIMENSIONUNIVERSITY PROFESSORHIGH-SCHOOL TEACHER
Cognitive9261
Creative7254
Social7491
Switching between them
LowDIFFICULTY

High-school Teacher appears in our dataset as a mapped adjacent career for University Professors: the move lowers exposure by 11 points, landing at 29%. Switch difficulty reads low — capability profiles are 17 points apart on average and both sit in the same family.

Score your own exposure in 8 questions →

Common questions.

Is University Professor or High-school Teacher more at risk from AI?

University Professor. It scores 40% time-weighted AI exposure against 29% for High-school Teacher — an 11-point gap. 24% of university professor work time is already fully substitutable by current models, versus 20% for High-school Teachers.

Which pays more, University Professor or High-school Teacher?

University Professor, by roughly $26k at the median ($88k versus $62k). Note that the higher-paying role here is also the more AI-exposed one, which matters if you are weighing pay against durability.

Can a university professor switch to being a high-school teacher?

High-school Teacher appears in our dataset as a mapped adjacent career for University Professors: the move lowers exposure by 11 points, landing at 29%. Switch difficulty reads low — capability profiles are 17 points apart on average and both sit in the same family.

Which role is growing faster, University Professor or High-school Teacher?

University Professor, at 2% projected ten-year growth versus 1% — a 1-point difference. Growth and AI exposure are separate signals: a role can grow in headcount while the content of the work is substantially rewritten.

Career families
Education
Methodology
Scores are time-weighted across each role's canonical O*NET tasks, graded against current frontier-model capability. How we score.