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 15.2
Physical / roboticsrange 42.4 to 66.4
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 Separating, Filtering, Clarifying, Precipitating, and Still Machine Setters, Operators, and Tenders
It is skill-adjacent and less exposed (53.3 vs 54). 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.
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Which of my tasks are exposed
Clean, wash, and sterilize equipment and cooking area, using water hoses, cleaning or sterilizing solutions, or rinses.
54.4
Read work orders, recipes, or formulas to determine cooking times and temperatures, and ingredient specifications.
54.4
Observe gauges, dials, and product characteristics, and adjust controls to maintain appropriate temperature, pressure, and flow of ingredients.
54.4
Measure or weigh ingredients, using scales or measuring containers.
54.4
Tend or operate and control equipment, such as kettles, cookers, vats and tanks, and boilers, to cook ingredients or prepare products for further processing.
54.4
Record production and test data, such as processing steps, temperature and steam readings, cooking time, batches processed, and test results.
54.4
Set temperature, pressure, and time controls, and start conveyers, machines, or pumps.
54.4
Remove cooked material or products from equipment.
54.4
Longer, orange bars are more automatable; short green bars are resistant.
What is driving my result
lowers risk
raises risk
Task: Clean, wash, and sterilize equipment and cooking area, using water hoses, cleaning or sterilizing solutions, or rinses.
Task: Read work orders, recipes, or formulas to determine cooking times and temperatures, and ingredient specifications.
Lower-risk adjacent roles
Separating, Filtering, Clarifying, Precipitating, and Still Machine Setters, Operators, and Tenders
53.3
Bakers
54.0
A full, ranked mitigation plan is part of the paid tiers.
How this score is calculated
Map Food Cooking Machine Operators and Tenders 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 3.2, robotics 54.4.
The timeline comes from the higher axis (54.4), 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.