OBSERVED IN REAL USE · Anthropic 2026
5%
of this role’s work is already showing up in real Claude usage (Anthropic Economic Index).
Still standing — but the ground is warm.
57% 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
- Answer routine telephone or in-person reference inquiries, referring patrons to librarians for further assistance, when necessary
- Process print and non-print library materials to prepare them for inclusion in library collections
- Enter and update patrons' records on computers
- Maintain and troubleshoot problems with library equipment, including computers, photocopiers, and audio-visual equipment
- Collect fines and respond to complaints about fines
WHAT IT STILL CAN’T
- Deliver and retrieve items throughout the library by hand or using pushcart
- Check for damaged library materials, such as books or audio-visual equipment, and provide replacements or make repairs
- Train other staff, volunteers, or student assistants and schedule and supervise their work
- Take actions to halt disruption of library activities by problem patrons
- Issue identification cards to borrowers
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 57% 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