Grade, sort, or classify unprocessed food and other agricultural products by size, weight, color, or condition.
U.S. Workers
26,870
Median Salary
$35,430
10-Year Growth
-5.4%
Annual Openings
5,100
Typical entry: No formal educational credential
6 of 6 tasks have some AI capability
Exposure Trend
This score reflects estimated AI technical capability for tasks in this occupation. It does not predict employment changes, and it does not account for company-specific constraints, regulation, or adoption barriers.
Place products in containers according to grade and mark grades on containers.
AI: Fully automatable - Industrial vision systems and pick‑and‑place robots can sort products by grade and apply markings or labels to containers automatically.
Weigh products or estimate their weight, visually or by feel.
AI: Fully automatable - Accurate weighing is fully automatable with scales and conveyors, and visual weight estimation can be replaced by sensors and machine vision for consistent throughput.
Discard inferior or defective products or foreign matter, and place acceptable products in containers for further processing.
AI: Fully automatable - Machine vision combined with automated actuators is capable of rejecting defective items and placing acceptable products into containers on processing lines.
Record grade or identification numbers on tags or on shipping, receiving, or sales sheets.
AI: Fully automatable - Recording grades and ID numbers to tags and electronic documents is straightforward to fully automate with labelers and database integration.
Grade and sort products according to factors such as color, species, length, width, appearance, feel, smell, and quality to ensure correct processing and usage.
AI: Partial - Many attributes like color, size and visible defects are automatable, but tactile (feel) and nuanced smell‑based quality judgements remain only partially solved by 2025.
Separate fiber tufts between fingers to assess strength, uniformity, and cohesive quality of fibers.
AI: Partial - Instrumented tests can measure fiber strength and uniformity, but the specific manual, tactile assessment of separating tufts between fingers is not fully replicated by available robotic tactile systems.