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AI Automation Index
Will AI Replace Slaughterers and Meat Packers?
Task-level automation exposure for Slaughterers and Meat Packers: 14 O*NET tasks scored against their work activities, plus the simulator.
E-E-A-T Verified
Developed & audited by Gini Loh Automation Exposure
5%
weighted task index
14 of 14 tasks scored
Median Salary
$40,130 / year
BLS OEWS, May 2025 — this exact occupation
Employment Level
Medium
69,950 people hold this job — size, not growth
Projected 2025–35
+2.0%
employment change
7,700 openings a year · BLS line item
Pay by state
BLS OEWS publishes 48 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.
$22,710 – $50,480
Highest medians
Colorado $50,480
Arizona $49,020
Nebraska $48,910
Kansas $48,240
Montana $46,700
Lowest medians
Puerto Rico $22,710
Nevada $30,430
New Mexico $30,560
Delaware $31,200
Mississippi $33,650
State figures come from the 51-3023 row in the May 2025 state panel. States where the estimate was suppressed or too small to publish are absent.
What the score is made of
Each task is mapped to its work activities, scored for AI automation potential, and weighted by how important those activities are to the job. These are the components.
Automation potential 5%
Importance-weighted mean of the scored tasks. This is the headline index.
Physical work 100%
Share of weighted tasks in hands-on or machine-operating work activities.
Judgment & influence 0%
Share in analysis, decisions, teaching, directing, advising, or caring for others.
Routine administration 0%
Share in documenting, recording, and administrative activities.
Rewritten by O*NET 0%
Share of weighted tasks O*NET rewrote in a recent update. Reported, not folded into the score.
Consequence of error 39/100
Moderate
O*NET's own rating of how serious an uncorrectable mistake would be here — respondents, not us. Deliberately not in the index: the score measures what AI can do with the task content, and multiplying it by stakes would be our judgment dressed as data.
Constituent Task Mix
14 tasks for this occupation, weighted by work-activity importance. Shares below are of total task weight, not task count.
High exposure (≥ 60% of the task is automatable) 0%
0 tasks
Medium exposure (≥ 35%) 0%
0 tasks
Low exposure (below 35%) 100%
14 tasks
How would you survive?
Move your week away from the high-exposure tasks and toward the ones that need judgment. The simulator recalculates the index as you shift the mix.
Simulate Upskilling →Constituent Tasks
#13986 · Supplemental · 4% automatable
Remove bones, and cut meat into standard cuts in preparation for marketing.
physical manipulation — Manual meat cutting
Cut meat products.
#13991 · Supplemental · 5% automatable
Sever jugular veins to drain blood and facilitate slaughtering.
physical manipulation — Animal slaughter is hands-on with unpredictable bodies
Slaughter animals.
#13990 · Supplemental · 5% automatable
Tend assembly lines, performing a few of the many cuts needed to process a carcass.
physical manipulation — Carcass processing is physical meat-handling work
Cut meat products. Process animal carcasses.
#13994 · Supplemental · 5% automatable
Shackle hind legs of animals to raise them for slaughtering or skinning.
physical manipulation — Animal slaughter is hands-on with unpredictable bodies
Slaughter animals.
#13989 · Supplemental · 5% automatable
Slit open, eviscerate, and trim carcasses of slaughtered animals.
physical manipulation — Carcass processing is physical meat-handling work
Cut meat products. Process animal carcasses.
#13999 · Supplemental · 5% automatable
Stun animals prior to slaughtering.
physical manipulation — Animal slaughter is hands-on with unpredictable bodies
Slaughter animals.
#13995 · Supplemental · 6% automatable
Skin sections of animals or whole animals.
physical manipulation — Carcass processing is physical meat-handling work
Process animal carcasses.
#13987 · Supplemental · 6% automatable
Cut, trim, skin, sort, and wash viscera of slaughtered animals to separate edible portions from offal.
physical manipulation — Manual cleaning of materials for production
Clean materials to prepare them for production. Cut meat products. Process animal carcasses.
#13992 · Supplemental · 7% automatable
Shave or singe and defeather carcasses, and wash them in preparation for further processing or packaging.
physical manipulation — Manual cleaning of materials for production
Clean materials to prepare them for production. Process animal carcasses.
#13997 · Supplemental · 6% automatable
Saw, split, or scribe carcasses into smaller portions to facilitate handling.
physical manipulation — Carcass processing is physical meat-handling work
Process animal carcasses.
#13996 · Supplemental · 5% automatable
Trim head meat, and sever or remove parts of animals' heads or skulls.
physical manipulation — Carcass processing is physical meat-handling work
Cut meat products. Process animal carcasses.
#13998 · Supplemental · 4% automatable
Grind meat into hamburger, and into trimmings used to prepare sausages, luncheon meats, and other meat products.
physical manipulation — Hands-on meat preparation
Prepare meat products for sale or consumption.
#13993 · Supplemental · 6% automatable
Trim, clean, or cure animal hides.
physical manipulation — Carcass processing is physical meat-handling work
Process animal carcasses.
#14000 · Supplemental · 5% automatable
Wrap dressed carcasses or meat cuts.
physical manipulation — Carcass processing is physical meat-handling work
Prepare meat products for sale or consumption. Process animal carcasses.
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How this was scored
- 1. Tasks. O*NET task statements for this occupation, from a release whose newest record is dated 08/2026.
- 2. Work activities. Each task maps to 1–5 Detailed Work Activities; each activity belongs to one of 41 Generalized Work Activities that O*NET rates for importance (1–5) in this occupation.
- 3. Automation potential. Every work activity carries one score for how far current AI can perform it end-to-end. Tasks inherit the mean of their activities.
- 4. Weighting. Task weight = 0.35 + 0.65 × (importance − 1)/4, scaled by how often the task is performed and by 0.7 for Supplemental tasks. Importance is the task's own O*NET rating where it exists (18,369 of 18,838 tasks); the rest inherit their work activities' importance. The index is the weighted mean.
Check: across the 910 occupations where O*NET also rates how far machine speed sets the pace, this index moves opposite to it (Spearman ρ = -0.49). The more a job is paced by equipment, the less of its task content AI can address — the relationship you would expect if the scoring is working.
Sources · O*NET 31.0 (task records to 08/2026) · BLS OEWS May 2025 · BLS projections 2025-2035 · rubric v2.1 · tasks for O*NET, not a forecast
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