Strength of current models on the capabilities this job's tasks require.
Task automation potential0/100
Task-level exposure, weighted by task importance. A component of the headline, not the headline itself.
Observed AI adoption0/100
Evidence that AI is actually being used for this work.
Labour-market signal0/100
Observed changes in postings, employment or earnings.
Evidence strength35/100
Quantity and source quality of the evidence behind the score.
1 evidence item(s) contribute. Calculated 19 hours ago. 12 Oct 2026 UTC.
Overview
All postsecondary teachers not listed separately.
Employment
≈1,300,000
approx. BLS OES
Median wage
≈$88,000
approx. BLS OES
Tasks tracked
0
linked to this occupation
Employment and wage values are approximate reference figures from the BLS Occupational Employment and Wage Statistics programme, stored with an approximation flag. Verify against the O*NET record and BLS before quoting them.
Core tasks only. Exposure describes how much of the task output current AI can produce or substantially assist - not whether the task disappears. Secondary shared-baseline edges are hidden until per-occupation curation is complete.
No core tasks are linked to this occupation yet.
Evidence
Evidence trail
1 attributed item(s). Confidence reflects study design: randomised and production deployments score higher than platform observations, which score higher than projections.
Task-level usage data shows AI most used for lesson and material preparation and for feedback drafting, with far less usage recorded for live instruction and classroom management.
A good example of capability and adoption diverging inside one occupation: preparation is heavily automated while the defining activity of the job is not.
Backcast series: recomputed at quarterly checkpoints using only the models and evidence published by each date.
Score · 23 points · 2021-01-01 to 2026-07-01
Reconstruction, not measurement. 14 observed daily snapshot(s) exist for this occupation; the earlier part of the curve is derived by applying the current methodology to the model releases and published evidence available at each past date.
Recent events
Signals affecting this occupation
Research published
▲ IMPACT 40
Teaching neural decoders with language
arXiv:2610.12921v1 Announce Type: new Abstract: Brain-computer interfaces decode neural activity, yet class-label supervision (CLS) leaves relationships among classes implicit. We propose Language as Supervision (LaS), which aligns neural features with natural-language class descriptions through learned projections and predicts classes using candidate text prototypes. We evaluate seven encoder architectures with independently trained models for visual, motor, and speech decoding from scalp and intracranial recordings. LaS improves speech-decoding accuracy by up to 17.15~pp over matched CLS bas
Labor research/Confidence:74 · moderate/Verified by AIKillsWhat
Research published
▲ IMPACT 40
Teaching Agents to Code Reliably
arXiv:2610.03984v1 Announce Type: new Abstract: Autonomous coding agents solve repository issues by reading code, running commands, editing files, and submitting patches. Extra inference-time compute yields gains only when it produces a useful repair and supplies reliable evidence for choosing one. Three behaviors decide both, and we argue they are teachable rather than byproducts of scale, so a policy can carry them instead of a scaffold. Location diversity remains narrow, since attempts return to the same site and extra samples add no coverage. Edit diversity is left unexploited, since metho
Labor research/Confidence:74 · moderate/Verified by AIKillsWhat
Research published
▲ IMPACT 20
AI is being taught how to do your job. Will artificial intelligence replace us, or just change the way we work?
It's become a booming industry: teaching artificial intelligence how to get better at doing all kinds of jobs. As AI advances, many fear what this tech means for the future of work.
Labor research/Confidence:50 · low/Verified by AIKillsWhat
Research published
▲ IMPACT 20
60 Minutes Transcript: Artificial intelligence and the future of work
Some Americans are working to improve artificial intelligence, teaching it the skills and knowledge accrued over the course of a career.
Labor research/Confidence:50 · low/Verified by AIKillsWhat
AI Exposure Score moved from a previous calculation to 41/100 under methodology v1.0. 1 evidence item(s) contributed.
Verified signal/Confidence:45 · low/Verified by AIKillsWhat
New model
▲ IMPACT 45
Introducing Claude for Teachers
Verified US K-12 educators get free access to premium Claude capabilities, a teaching skills library, and standards-aligned curricula for all 50 states.
Frontier release/Confidence:78 · moderate/Verified by AIKillsWhat
Research published
▲ IMPACT 20
Anthropic brings AI education to Africa with Rwanda and ALX
A Claude-based learning companion reaches Rwandan teachers and 200,000+ ALX students across Africa.
Labor research/Confidence:50 · low/Verified by AIKillsWhat
AI adoption signal
▲ IMPACT 48
Measured AI usage in education is concentrated in preparation and feedback
Task-level usage data shows AI most used for lesson and material preparation and for feedback drafting, with far less usage recorded for live instruction and classroom management.
Enterprise deployment/Confidence:68 · moderate/Verified by AIKillsWhat
Research published
▲ IMPACT 20
Higher education advisory board and AI Fluency courses
Anthropic announces a Higher Education Advisory Board chaired by Rick Levin and three Creative Commons AI Fluency courses for institutions.
Labor research/Confidence:50 · low/Verified by AIKillsWhat