AI exposure: Slaughterers and Meat Packers
Perform nonroutine or precision functions involving the preparation of large portions of meat. Work may include specialized slaughtering tasks, cutting standard or premium cuts of meat for marketing, making sausage, or wrapping meats. Work typically occurs in slaughtering, meat packing, or wholesale establishments.
Reading this score
computedSlaughterers and Meat Packers is among the least exposed occupations measured, at 0.0% of weighted task load, rank 918 of 923. 100.0% of this job is work current AI systems cannot produce at all. That is not a statement about skill or value. It is a statement about what these systems can and cannot do.
What holds the line here is embodiment. Across this occupation's 14 tasks it averages 3.00 out of 3, the highest of the five friction dimensions. In plain terms, the work has to happen in physical space. A language model cannot move matter. Until the robotics to do this work is both good enough and cheap enough to deploy widely, capability in software does not reach it.
The most exposed thing this job does is Remove bones, and cut meat into standard cuts in preparation for marketing, at 0.0%. The least is Wrap dressed carcasses or meat cuts, at 0.0%. A gap of 0.0% between two parts of the same job is the reason this index publishes at task level. An occupation-wide number would have hidden both.
Within production occupations, this one is less exposed than the median of 16.2% across the group's 107 roles, with 106 scoring higher. Being in an exposed family does not make a particular job exposed, and the reverse holds too.
What would move this score. Of 14 tasks, 0 are currently banded exposed, 0 assisted and 14 untouched. For that distribution to shift materially would take robotics cheap and reliable enough to deploy at scale, not a better language model. The score is re-computed every quarter against a fresh capability reference, and the change is published rather than quietly applied.
Where the score comes from
judgedEvery task is scored through the standardised work activities it maps to. These are this occupation’s averages on the six rubric dimensions. Capability is what AI can do; the other five are what stands in the way.
| Dimension | Mean | Scale |
|---|---|---|
| Capability | 0.00 | 0-4 |
| Embodiment | 3.00 | 0-3 |
| Presence | 0.21 | 0-3 |
| Accountability | 0.94 | 0-3 |
| Context | 1.00 | 0-3 |
| Verification cost | 1.00 | 0-3 |
Task by task
14 tasks, O*NET 31.0| Task | Exposed | Assisted | Untouched | Importance | Band |
|---|---|---|---|---|---|
| Remove bones, and cut meat into standard cuts in preparation for marketing. | 0.0% | 0.0% | 100.0% | 4.69 | untouched |
| Sever jugular veins to drain blood and facilitate slaughtering. | 0.0% | 0.0% | 100.0% | 4.64 | untouched |
| Tend assembly lines, performing a few of the many cuts needed to process a carcass. | 0.0% | 0.0% | 100.0% | 4.53 | untouched |
| Shackle hind legs of animals to raise them for slaughtering or skinning. | 0.0% | 0.0% | 100.0% | 4.50 | untouched |
| Slit open, eviscerate, and trim carcasses of slaughtered animals. | 0.0% | 0.0% | 100.0% | 4.45 | untouched |
| Stun animals prior to slaughtering. | 0.0% | 0.0% | 100.0% | 4.42 | untouched |
| Skin sections of animals or whole animals. | 0.0% | 0.0% | 100.0% | 4.38 | untouched |
| Cut, trim, skin, sort, and wash viscera of slaughtered animals to separate edible portions from offal. | 0.0% | 0.0% | 100.0% | 4.35 | untouched |
| Shave or singe and defeather carcasses, and wash them in preparation for further processing or packaging. | 0.0% | 0.0% | 100.0% | 4.34 | untouched |
| Saw, split, or scribe carcasses into smaller portions to facilitate handling. | 0.0% | 0.0% | 100.0% | 4.30 | untouched |
| Trim head meat, and sever or remove parts of animals' heads or skulls. | 0.0% | 0.0% | 100.0% | 4.30 | untouched |
| Grind meat into hamburger, and into trimmings used to prepare sausages, luncheon meats, and other meat products. | 0.0% | 0.0% | 100.0% | 4.21 | untouched |
| Trim, clean, or cure animal hides. | 0.0% | 0.0% | 100.0% | 4.20 | untouched |
| Wrap dressed carcasses or meat cuts. | 0.0% | 0.0% | 100.0% | 3.97 | untouched |
Task text and importance ratings sourced from O*NET 31.0. Shares computed. The occupation score is the importance-weighted mean.
Occupations either side of this one
The four closest scores in the same occupational family, then the four closest anywhere in the index.
Read this carefully. Exposure is not displacement. A high score means current AI systems can produce this work, not that anyone will stop paying a person to do it. Adoption depends on economics, regulation and inertia that this index deliberately does not model. How the score is built.
What this means in practice
Most of this work is not reachable by current systems, so the immediate pressure is on the administrative edges of the role rather than its core: the scheduling, the reporting, the written records. That is where time is recovered.