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AI Automation Index
Will AI Replace Meat, Poultry, and Fish Cutters and Trimmers?
Task-level automation exposure for Meat, Poultry, and Fish Cutters and Trimmers: 12 O*NET tasks scored against their work activities, plus the simulator.
E-E-A-T Verified
Developed & audited by Gini Loh Automation Exposure
8%
weighted task index
12 of 12 tasks scored
Median Salary
$38,300 / year
BLS OEWS, May 2025 — this exact occupation
Employment Level
High
145,700 people hold this job — size, not growth
Projected 2025–35
+5.7%
employment change
17,000 openings a year · BLS line item
Pay by state
BLS OEWS publishes 52 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.
$24,550 – $50,390
Highest medians
Colorado $50,390
Arizona $48,550
Kansas $48,080
Nebraska $47,580
New Hampshire $47,260
Lowest medians
Puerto Rico $24,550
Guam $27,660
Louisiana $27,850
Alabama $31,080
Florida $31,160
State figures come from the 51-3022 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 8%
Importance-weighted mean of the scored tasks. This is the headline index.
Physical work 82%
Share of weighted tasks in hands-on or machine-operating work activities.
Judgment & influence 10%
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 15/100
Low
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
12 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%
12 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 →Emerging & rewritten tasks
Tasks O*NET added or rewrote for this occupation in its recent updates (05/2025 – 08/2026), with who proposed them. Additions are not in the scored task inventory — they are new work O*NET is still measuring, so they appear here and nowhere in the index. A Revision replaces a task that is scored, which is why only those move the "Rewritten by O*NET" share.
- New 07/2017 · Incumbent
Clean meat cutting equipment.
Constituent Tasks
#8795 · Core · 4% automatable
Use knives, cleavers, meat saws, bandsaws, or other equipment to perform meat cutting and trimming.
physical manipulation — Manual meat cutting
Cut meat products.
#8804 · Core · 17% automatable
Weigh meats and tag containers for weight and contents.
physical manipulation — Physically weighing finished products on scale
Mark products, workpieces, or equipment with identifying information. Weigh finished products.
#8799 · Core · 12% automatable
Inspect meat products for defects, bruises or blemishes and remove them along with any excess fat.
visual inspection — Food product inspection is sensory and hands-on
Inspect food products. Prepare meat products for sale or consumption.
#8797 · Core · 4% automatable
Cut and trim meat to prepare for packing.
physical manipulation — Manual meat cutting
Cut meat products.
#8803 · Core · 7% automatable
Separate meats and byproducts into specified containers and seal containers.
physical manipulation — Physical product sorting needs manipulation in warehouse
Sort materials or products for processing, storing, shipping, or grading. Prepare meat products for sale or consumption.
#8801 · Supplemental · 4% automatable
Process primal parts into cuts that are ready for retail use.
physical manipulation — Manual meat cutting
Cut meat products.
#8807 · Supplemental · 4% automatable
Prepare ready-to-heat foods by filleting meat or fish or cutting it into bite-sized pieces, preparing and adding vegetables or applying sauces or breading.
physical manipulation — Hands-on meat preparation
Prepare meat products for sale or consumption. Cut meat products.
#8796 · Supplemental · 5% automatable
Clean, trim, slice, and section carcasses for future processing.
physical manipulation — Carcass processing is physical meat-handling work
Cut meat products. Process animal carcasses.
#8798 · Supplemental · 6% automatable
Remove parts, such as skin, feathers, scales or bones, from carcass.
physical manipulation — Carcass processing is physical meat-handling work
Process animal carcasses.
#8802 · Supplemental · 20% automatable
Obtain and distribute specified meat or carcass.
physical manipulation — Physically delivering supplies to workers
Distribute supplies to workers.
#8800 · Supplemental · 4% automatable
Produce hamburger meat and meat trimmings.
physical manipulation — Hands-on meat preparation
Prepare meat products for sale or consumption.
#8805 · Supplemental · 6% automatable
Clean and salt hides.
physical manipulation — Carcass processing is physical meat-handling work
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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