EXPOSURE TO AI
16%
RESILIENT
OBSERVED IN REAL USE · Anthropic 2026
3%
of this role’s work is already showing up in real Claude usage (Anthropic Economic Index).
The last desk the machine reaches. Breathe.
16% 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. Certified hard to automate. Today’s AI barely touches the core of this one.
WHAT AI CAN ALREADY DO
- Record information about work completed and machine settings
- Program electronic equipment
- Study guides, loom patterns, samples, charts, or specification sheets, or confer with supervisors or engineering staff to determine setup requirements
- Observe woven cloth to detect weaving defects
WHAT IT STILL CAN’T
- Remove defects in cloth by cutting and pulling out filling
- Inspect products to ensure that specifications are met and to determine if machines need adjustment
- Thread yarn, thread, and fabric through guides, needles, and rollers of machines for weaving, knitting, or other processing
- Examine looms to determine causes of loom stoppage, such as warp filling, harness breaks, or mechanical defects
- Set up, or set up and operate textile machines that perform textile processing and manufacturing operations such as winding, twisting, knitting, weaving, bonding, or stretching
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 16% 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