OBSERVED IN REAL USE · Anthropic 2026
20%
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.
54% 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
- Code, classify, and catalog books, publications, films, audio-visual aids, and other library materials, based on subject matter or standard library classification systems
- Explain use of library facilities, resources, equipment, and services, and provide information about library policies
- Teach library patrons basic computer skills, such as searching computerized databases
- Engage in professional development activities, such as taking continuing education classes and attending or participating in conferences, workshops, professional meetings, and associations
- Maintain hardware and software, including computers, media equipment, scanners, color copiers, and color laser printers
WHAT IT STILL CAN’T
- Troubleshoot problems with audio-visual equipment
- Represent library or institution on internal and external committees
- Train faculty and media staff on the use of software and audio-visual equipment
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 54% 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