EXPOSURE TO AI
43%
MODERATE
OBSERVED IN REAL USE · Anthropic 2026
7%
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.
43% 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 documentation of all loss prevention activity
- Maintain databases such as bad check logs, reports on multiple offenders, and alarm activation lists
- Administer systems and programs to reduce loss, maintain inventory control, or increase safety
- Review loss prevention exception reports and cash discrepancies to ensure adherence to guidelines
- Provide recommendations and solutions in crisis situations such as workplace violence, protests, and demonstrations
WHAT IT STILL CAN’T
- Investigate or interview individuals suspected of shoplifting or internal theft
- Hire or supervise loss prevention staff
- Visit stores to ensure compliance with company policies and procedures
- Train loss prevention staff, retail managers, or store employees on loss control and prevention measures
- Develop and maintain partnerships with federal, state, or local law enforcement agencies or members of the retail loss prevention community
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 43% 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