Laborers and Freight, Stock, and Material Movers, Hand
Manually move freight, stock, luggage, or other materials, or perform other general labor. Includes all manual laborers not elsewhere classified.
Also known as: Bagger · Assorter · Ash Worker · Bag Turner · Bag Worker · Baggageman
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.
Your free role snapshot
Start with the work, not the headline
This occupation baseline already contains different kinds of work. These are the two ends of its current task range and one useful action you can take now.
Most exposed task
Record numbers of units handled or moved, using daily production sheets or work tickets.
Augmentable 55/100 exposure
Most durable task
Carry needed tools or supplies from storage or trucks and return them after use.
Durable 8/100 exposure
Useful next step
Make one change to the task mix
Protect the durable core of the role, then use AI to compress the routine work around it before that becomes a mandate.
Want this mapped to your actual week? Know what to strengthen, what to delegate to AI with review, and what to do over the next 7, 30, and 90 days.
Build my 7/30/90-day action plan — $9Most exposed tasks
No task is classified fully automatable in this release. The highest-exposure task relative to this role is shown in the free snapshot above; the assistive work is detailed next.
Augmentable tasks
Work where AI assists rather than replaces — the productivity frontier of this role.
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Record numbers of units handled or moved, using daily production sheets or work tickets.55
Most durable tasks
Lowest exposure — typically judgment, relationships, physical presence, or accountability. This is the human moat.
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Move freight, stock, or other materials to and from storage or production areas, loading docks, delivery vehicles, ships, or containers, by hand or using trucks, tractors, or other equipment.8
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Carry needed tools or supplies from storage or trucks and return them after use.8
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Attach slings, hooks, or other devices to lift cargo and guide loads.10
Task exposure values and classifications are published, versioned estimates audited against the anchored rubric. This page reads them from the data release rather than generating them at request time. Bars show exposure contribution relative to this role’s task mix.
What this means
A score of 19 puts Laborers and Freight, Stock, and Material Movers, Hand in the least-exposed quarter of analyzed occupations. In practice, exposure this level is about the mix: 0 of 13 analyzed tasks lean automatable, 1 augmentable, and 12 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.
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
- $40,240median wage
- 2,950,280employed
- 384,300annual openings
- +1.5%projected growth
Context only — labor statistics are not inputs to the exposure score. See methodology.
Turn your actual week into a plan
Know which work to strengthen, what to delegate to AI with review, and what to do over the next 7, 30, and 90 days. Your $9 plan includes a confidence-rated personal score, task matrix, human moat, and only genuinely lower-exposure adjacent roles.
Build my 7/30/90-day action plan — $9Related roles
Adjacent by skills or family — no exposure claim implied.
How this score was calculated
The score is the plain average of the AI-exposure values of this role’s 13 analyzed tasks (equal task weights in this release — no hidden factors):
- Augmentable 1 task, averaging 55/100 exposure
- Durable 12 tasks, averaging 16/100 exposure
score = (1×55 + 12×16) ÷ 13 ≈ 19
Every task’s exposure value was scored against a published anchored rubric that scores tasks as actually performed — physical, in-person, and accountability requirements included (data release 2026.07.12-r2). The band (Low) is a corpus quartile; the percentile is tie-aware across all 968 occupations.
FAQ — Laborers and Freight, Stock, and Material Movers, Hand
- Will AI replace Laborers and Freight, Stock, and Material Movers, Hand?
- This score cannot predict whether this occupation or any individual job will be replaced. It shows which tasks current and near-term AI can perform or accelerate, which tasks remain more durable, and where a worker can adapt. Employer decisions, demand, regulation, and how the role changes are outside the score.
- What does a score of 19 mean for a Laborers and Freight, Stock, and Material Movers, Hand?
- It means that, weighted across the 13 tasks we analyzed for this role, the task mix sits at 19 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: Move freight, stock, or other materials to and from storage or production areas, loading docks, delivery vehicles, ships, or containers, by hand or using trucks, tractors, or other equipment; Carry needed tools or supplies from storage or trucks and return them after use; Attach slings, hooks, or other devices to lift cargo and guide loads. 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 2026.07.12-r2 · updated 2026-07-13 · baseline mapping: 13 of 13 tasks carry source-level provenance · methodology