EXPOSURE TO AI
49%
MODERATE
OBSERVED IN REAL USE · Anthropic 2026
16%
of this role’s work is already showing up in real Claude usage (Anthropic Economic Index).
Half in the fire, half out. Choose which half you become.
49% of this role’s O*NET tasks are within reach of today’s AI. That is the core-weighted exposure score from Eloundou et al. 2023 (“GPTs are GPTs”). It measures a capability ceiling, not a headcount forecast. In the blast radius. A real slice of the work is already automatable. The rest isn’t.
WHAT AI CAN ALREADY DO
- Prepare reports and maintain records, such as student grades, attendance rolls, and training activity details
- Prepare outlines of instructional programs and training schedules and establish course goals
- Review enrollment applications and correspond with applicants to obtain additional information
- Observe and evaluate students' work to determine progress, provide feedback, and make suggestions for improvement
- Present lectures and conduct discussions to increase students' knowledge and competence using visual aids, such as graphs, charts, videotapes, and slides
WHAT IT STILL CAN’T
- Supervise and monitor students' use of tools and equipment
- Conduct on-the-job training classes or training sessions to teach and demonstrate principles, techniques, procedures, or methods of designated subjects
- Acquire, maintain, and repair laboratory equipment and tools
THE HONEST PART. A percentage is not a pink slip. High exposure usually means a role shrinks and shifts toward judgment, direction and responsibility: the parts a model can’t sign its name to. Exposure ≠ displacement. Breathe.
"My job is 49% cooked. What’s yours?"
SOURCES: O*NET 30.3 occupational tasks · Eloundou et al. 2023 (“GPTs are GPTs”,
arXiv:2303.10130) · Anthropic Economic Index 2026 (CC-BY) |
how this is calculated |
last updated 2026-07-16