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 the bigger shift looks near-term.
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 12.0
Physical / roboticsrange 45.9 to 69.9
When the change is likely
Near-term, highlocal demand declining
What to do about it
Use AI to outpace AI.
Strategies to protect your livelihood, most important first.
1
Act within the next 1 to 2 years
Displacement for this role is near-term. Start a concrete reskilling plan now, while you still have income and leverage.
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
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.
4
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
Pour and regulate the flow of molten metal into molds and forms to produce ingots or other castings, using ladles or hand-controlled mechanisms.
57.9
Read temperature gauges and observe color changes, adjusting furnace flames, torches, or electrical heating units as necessary to melt metal to specifications.
57.9
Remove solidified steel or slag from pouring nozzles, using long bars or oxygen burners.
57.9
Examine molds to ensure they are clean, smooth, and properly coated.
57.9
Collect samples, or signal workers to sample metal for analysis.
57.9
Load specified amounts of metal and flux into furnaces or clay crucibles.
57.9
Position equipment such as ladles, grinding wheels, pouring nozzles, or crucibles, or signal other workers to position equipment.
57.9
Skim slag or remove excess metal from ingots or equipment, using hand tools, strainers, rakes, or burners, collecting scrap for recycling.
57.9
Longer, orange bars are more automatable; short green bars are resistant.
What is driving my result
lowers risk
raises risk
Local demand is declining
Task: Pour and regulate the flow of molten metal into molds and forms to produce ingots or other castings, using ladles or hand-controlled mechanisms.
Task: Read temperature gauges and observe color changes, adjusting furnace flames, torches, or electrical heating units as necessary to melt metal to specifications.
How this score is calculated
Map Pourers and Casters, Metal 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 0.0, robotics 57.9.
The timeline comes from the higher axis (57.9), shifted for local demand (declining), 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.