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Graders and Sorters, Agricultural Products

Graders and Sorters, Agricultural Products — AI exposure, safer roles, and a pivot plan.

Also known as: Bean Sorter · Bulb Grader · Apple Sorter · Apple Turner · Banana Expert · Banana Grader

AI Task Exposure Score

Low exposure

More exposed than 20% of 968 occupations · Rank #750 (1 = most exposed)

This score estimates how exposed the tasks in a role are to current and near-term AI capabilities. It does not predict whether a specific person will lose a job.

Most exposed tasks

Highest structured exposure values in this role’s task mix — the work AI systems can already do most of.

No strongly automatable task in the current data release.

Augmentable tasks

Work where AI assists rather than replaces — the productivity frontier of this role.

  • Record grade or identification numbers on tags or on shipping, receiving, or sales sheets.43
  • Grade and sort products according to factors such as color, species, length, width, appearance, feel, smell, and quality to ensure correct processing and usage.36
  • Weigh products or estimate their weight, visually or by feel.35

Most durable tasks

Lowest exposure — typically judgment, relationships, physical presence, or accountability. This is the human moat.

  • Place products in containers according to grade and mark grades on containers.32
  • Discard inferior or defective products or foreign matter, and place acceptable products in containers for further processing.33

Task exposure values and classifications come from the versioned data release — they are structured data, not model output. Bars show exposure contribution relative to this role’s task mix.

What this means

A score of 36 puts Graders and Sorters, Agricultural Products in the least-exposed quarter of analyzed occupations. In practice, exposure this level is about the mix: 0 of 5 analyzed tasks lean automatable, 3 augmentable, and 2 durable. The useful question isn’t “will AI take this job” — it’s which tasks go first, which get faster, and where to reposition time. That’s what the personalized report maps against your actual week.

One next move: lean into the durable core above and adopt AI on the routine remainder before it becomes a mandate.

Lower-exposure adjacent roles

No adjacent role in the current data release is at least 10 points lower with ≥50% skill overlap — we don’t label anything “safer” unless the data supports it.

Labor-market context

  • $35,730median wage
  • 25,180employed
  • 5,100annual openings
  • -5.4%projected growth

Context only — labor statistics are not inputs to the exposure score. See methodology.

Your week probably doesn’t match the average

This page scores the occupation. The $9 Personalized Risk & Action Report scores your task mix — paste what you actually do and get your own score, confidence level, task matrix, human moat, and a 7/30/90-day plan.

Personalize my result — $9

Related roles

Adjacent by skills or family — no exposure claim implied.

FAQ — Graders and Sorters, Agricultural Products

What does a score of 36 mean for a Graders and Sorters, Agricultural Products?
It means that, weighted across the 5 tasks we analyzed for this role, the task mix sits at 36 on a 0–100 exposure scale — in the least-exposed quarter of analyzed occupations. It measures task exposure to current and near-term AI capabilities, not the probability of losing a job.
Which tasks in this role are most exposed to AI?
This role has no strongly automatable task in the current data release.
Which parts of this job are most durable?
The most durable responsibilities are: Place products in containers according to grade and mark grades on containers; Discard inferior or defective products or foreign matter, and place acceptable products in containers for further processing. Durable tasks typically depend on judgment, relationships, physical presence, or accountability.
Is this score personalized to me?
No — this page shows the occupation-level baseline. Two people with the same title often do different work. The $9 personalized report recalculates the score from the tasks you actually do and builds a concrete 7/30/90-day plan around them.

Score version jr-v1 · data release 2026.07.11-r1 · updated 2026-07-11 · baseline mapping: 5 of 5 tasks carry source-level provenance · methodology