EXPOSURE TO AI
49%
MODERATE
OBSERVED IN REAL USE · Anthropic 2026
25%
of this role’s work is already showing up in real Claude usage (Anthropic Economic Index).
The boring parts are leaving. The judgment stays.
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
- Maintain accurate laboratory records and data
- Write grant applications to obtain funding
- Prepare or review reports, manuscripts, or meeting presentations
- Design databases, such as mutagenesis libraries
- Design molecular or cellular laboratory experiments, oversee their execution, and interpret results
WHAT IT STILL CAN’T
- Perform laboratory procedures following protocols including deoxyribonucleic acid (DNA) sequencing, cloning and extraction, ribonucleic acid (RNA) purification, or gel electrophoresis
- Supervise technical personnel and postdoctoral research fellows
- Monitor or operate specialized equipment, such as gas chromatographs and high pressure liquid chromatographs, electrophoresis units, thermocyclers, fluorescence activated cell sorters, and phosphorimagers
- Evaluate new supplies and equipment to ensure operability in specific laboratory settings
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