AI exposure by occupation, O*NET 53-7063.00

Will AI replace Machine Feeders and Offbearers?

Machine Feeders and Offbearers: AI does not yet handle any of the role's 13 tasks; most of the work is hands-on, and the part AI can address mostly needs an efficient-tier model.

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Every task, scored

The 13 tasks O*NET 30.3 lists for Machine Feeders and Offbearers, from most to least exposed. None reaches 60, the level at which AI already handles a task.

Task AI exposure Evidence Model tier Importance
Inspect materials and products for defects, and to ensure conformance to specifications. 20 Estimated Efficient 4.4
Clean and maintain machinery, equipment, and work areas to ensure proper functioning and safe working conditions. 20 Estimated Efficient 4.1
Record production and operational data, such as amount of materials processed. 15 Estimated No tier 4.4
Push dual control buttons and move controls to start, stop, or adjust machinery and equipment. 15 Estimated No tier 4.3
Weigh or measure materials or products to ensure conformance to specifications. 15 Estimated No tier 4.3
Identify and mark materials, products, and samples, following instructions. 15 Estimated No tier 4.2
Remove materials and products from machines and equipment, and place them in boxes, trucks or conveyors, using hand tools and moving devices. 15 Estimated No tier 4.0
Load materials and products into machines and equipment, or onto conveyors, using hand tools and moving devices. 15 Estimated No tier 4.0
Transfer materials and products to and from machinery and equipment, using industrial trucks or hand trucks. 15 Estimated No tier 4.0
Shovel or scoop materials into containers, machines, or equipment for processing, storage, or transport. 15 Estimated No tier 3.9
Open and close gates of belt and pneumatic conveyors on machines that are fed directly from preceding machines. 15 Estimated No tier 3.9
Fasten, package, or stack materials and products, using hand tools and fastening equipment. 15 Estimated No tier 3.9
Add chemicals, solutions, or ingredients to machines or equipment as required by the manufacturing process. 15 Estimated No tier 3.6

Observed: scored from AI use recorded in the Anthropic Economic Index (June 2026 release), 0 of 13 tasks. Estimated: scored from the task's O*NET 30.3 work activity, 13 of 13. Importance is O*NET's 1 to 5 rating of how central the task is. Model tier is the lowest tier that can do the task under the published rubric; "No tier" marks hands-on work.

The model tier this role needs

An efficient-tier model or lower covers 16% of the role's importance-weighted task work. 16% of the work is something AI can address at some tier, and 84% is hands-on.

Efficient, standard and frontier tiers come from the JobRoute model tier reference. The recommended tier is the lowest one that covers 80% of the work AI can address. How the method works.

Wages, employment and outlook

US employment
42,330
Median annual wage
$41,220
Middle half of earners
$36,420 to $48,480
Projected change, 2024 to 2034
-13.0%

Employment and wages: BLS Occupational Employment and Wage Statistics, May 2025, national. Projection: BLS Employment Projections 2024 to 2034.

Adjacent roles

The occupations that reuse the most of this role's skills, with the usual time to move. These are the first places to look when you plan to redeploy or retrain people in this role.

Skill overlap and transition time from the JobRoute role adjacency graph on O*NET 30.3 skills.

Questions about Machine Feeders and Offbearers and AI

Will AI replace Machine Feeders and Offbearers?

Not on current evidence. None of the 13 tasks O*NET lists for this occupation reaches a task exposure of 60, the level at which JobRoute counts a task as handled by AI, and the role's importance-weighted exposure is 16 out of 100. JobRoute scores tasks, not whole jobs, so the score shows how much of the work changes rather than whether the job disappears.

What is the AI exposure of Machine Feeders and Offbearers?

16 out of 100 on JobRoute's task exposure measure, the importance-weighted average of the role's O*NET task scores. Higher means more of the work is AI-doable today. 0 of the 13 task scores are observed in the Anthropic Economic Index (June 2026 release), and the other 13 are estimated from each task's O*NET work activity.

Which Machine Feeders and Offbearers tasks can AI already do?

None reaches 60 yet. The most exposed task is: Inspect materials and products for defects, and to ensure conformance to specifications, at 20 out of 100.

What AI model tier does this role need?

An efficient-tier model or lower covers 16% of the role's importance-weighted task work, and 84% is hands-on work that no model tier covers. JobRoute assigns each task the lowest tier that can do it under a published rubric and recommends the lowest tier that covers 80% of the work AI can address.

How many people work as Machine Feeders and Offbearers, and what do they earn?

42,330 people in the United States, with a median annual wage of $41,220 (BLS Occupational Employment and Wage Statistics, May 2025). BLS Employment Projections expect a change of -13.0% from 2024 to 2034.

How to cite

Data version 2026-11-02, JobRoute method v1.0.0. Download all occupations or this occupation as JSON. Methodology.

JobRoute (2026). AI exposure: Machine Feeders and Offbearers. Data version 2026-11-02, method v1.0.0. Built on O*NET 30.3, BLS OEWS May 2025 and the Anthropic Economic Index (June 2026). CC BY 4.0. https://www.jobroute.ai/jobs/machine-feeders-and-offbearers

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