Transportation and Material Moving · United States (national)
Machine Feeders and Offbearers
How exposed this work is to automation, shown as ranges with the reasoning and sources.
The short version: this role is moderately exposed to automation, and meaningful change looks likely over the next 5 to 10 years.
It is a sourced range, not a verdict, and the detail is below.
Built on O*NET tasks, BLS pay and projections, and peer-reviewed AI-exposure research. Sources shown.
Data snapshot SNAPSHOT-2026-11-06. How it works
AI / softwarerange 0.0 to 21.1
Physical / roboticsrange 48.0 to 72.0
When the change is likely
Partial, 5 to 10 yearslocal demand stable
What to do about it
Use AI to outpace AI.
Strategies to protect your livelihood, most important first.
1
Use your 5 to 10 year runway
Change here is gradual. Build resilient skills steadily and watch the signals rather than waiting for a shock.
2
Move up from the task to the system
Robotics targets the physical work. Shift toward supervising, maintaining, or programming the automation instead of competing with it.
3
Pivot toward Crushing, Grinding, and Polishing Machine Setters, Operators, and Tenders
It is skill-adjacent and less exposed (60.0 vs 60). A lateral move now beats a forced one later.
4
Build a financial buffer
Keep 6 to 12 months of expenses and diversify your income, so a disruption is a setback rather than a catastrophe.
5
Add a recognised credential
A certification or license raises the bar against automation and signals value in a tightening market.
Keep the monitor on
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Which of my tasks are exposed
Inspect materials and products for defects, and to ensure conformance to specifications.
60.0
Record production and operational data, such as amount of materials processed.
60.0
Push dual control buttons and move controls to start, stop, or adjust machinery and equipment.
60.0
Weigh or measure materials or products to ensure conformance to specifications.
60.0
Identify and mark materials, products, and samples, following instructions.
60.0
Clean and maintain machinery, equipment, and work areas to ensure proper functioning and safe working conditions.
60.0
Load materials and products into machines and equipment, or onto conveyors, using hand tools and moving devices.
60.0
Transfer materials and products to and from machinery and equipment, using industrial trucks or hand trucks.
60.0
Longer, orange bars are more automatable; short green bars are resistant.
What is driving my result
lowers risk
raises risk
Task: Inspect materials and products for defects, and to ensure conformance to specifications.
Task: Record production and operational data, such as amount of materials processed.
Lower-risk adjacent roles
Crushing, Grinding, and Polishing Machine Setters, Operators, and Tenders
60.0
A full, ranked mitigation plan is part of the paid tiers.
How this score is calculated
Map Machine Feeders and Offbearers to its standard O*NET task list (8 core tasks).
Score each task for AI/software exposure (Eloundou et al. 2023) and physical/robotics exposure (an O*NET work-context proxy), each 0 to 100.
The two axis scores are the task averages: AI 9.1, robotics 60.0.
The timeline comes from the higher axis (60.0), shifted for local demand (stable), and seniority. It is read against your remaining working years.
Ranges are about ±12 points. A backtest against real BLS employment change shows the risk ranking holds in aggregate, but individual outcomes are predicted weakly, so results are ranges, never a flat verdict.
Sources: O*NET, Eloundou et al. (2023), GPTs are GPTs, O*NET Work Context, BLS CPI-U, BLS OEWS.
Snapshot SNAPSHOT-2026-11-06. Full method and backtest on How it works.