OBSERVED IN REAL USE · Anthropic 2026
38%
of this role’s work is already showing up in real Claude usage (Anthropic Economic Index).
Automate-adjacent. Keep the parts only you can sign off on.
50% 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. Heavily exposed. Most of the tasks are within reach of today’s AI.
WHAT AI CAN ALREADY DO
- Develop and organize training manuals, multimedia visual aids, and other educational materials
- Analyze training needs to develop new training programs or modify and improve existing programs
- Evaluate instructor performance and the effectiveness of training programs, providing recommendations for improvement
- Plan, develop, and provide training and staff development programs, using knowledge of the effectiveness of methods such as classroom training, demonstrations, on-the-job training, meetings, conferences, and workshops
- Prepare training budget for department or organization
WHAT IT STILL CAN’T
- Train instructors and supervisors in techniques and skills for training and dealing with employees
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 50% 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