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Manufacturing & Production · Updated Aug 2026

Pourers and Casters, Metal

Operate hand-controlled mechanisms to pour and regulate the flow of molten metal into molds to produce castings or ingots.

JVS 2.0.0-phase4b
AI Exposure
45/100
Moderate

How much of this occupation’s work can be materially affected by current AI systems.

Replacement Risk
46/100
Moderate

How likely exposure is to translate into reduced human demand.

Includes provisional estimates for AI adoption pressure and labour-market resilience. How this is measured

Evidence quality
Confidence82/100
Task coverage86%

Confidence reflects task coverage, mapping and capability-evidence quality, and how much of the score rests on provisional inputs.

Task-level evidence

What is driving the score?

Occupation scores are built from the task mix—not a single prediction about a job title.

JVS 2.0.0-phase4b
TaskImportanceAI impactExposure
Pour and regulate the flow of molten metal into molds and forms to produce ingots or other castings, using ladles or hand-controlled mechanisms.High
69
Load specified amounts of metal and flux into furnaces or clay crucibles.High
70
Pull levers to lift ladle stoppers and to allow molten steel to flow into ingot molds to specified heights.High
70
Position equipment such as ladles, grinding wheels, pouring nozzles, or crucibles, or signal other workers to position equipment.High
67
Turn valves to circulate water through cores, or spray water on filled molds to cool and solidify metal.High
70
Read temperature gauges and observe color changes, adjusting furnace flames, torches, or electrical heating units as necessary to melt metal to specifications.High
37
Collect samples, or signal workers to sample metal for analysis.High
38
Skim slag or remove excess metal from ingots or equipment, using hand tools, strainers, rakes, or burners, collecting scrap for recycling.High
40
Examine molds to ensure they are clean, smooth, and properly coated.High
25
Assemble and embed cores in casting frames, using hand tools and equipment.High
24
Remove metal ingots or cores from molds, using hand tools, cranes, and chain hoists.High
25
Remove solidified steel or slag from pouring nozzles, using long bars or oxygen burners.High
19
Repair and maintain metal forms and equipment, using hand tools, sledges, and bars.High
25
Most exposed

Where AI can do more

Routine, digitized, and highly repeatable tasks face the greatest pressure.

  1. Load specified amounts of metal and flux into furnaces or clay crucibles.70
  2. Pull levers to lift ladle stoppers and to allow molten steel to flow into ingot molds to specified heights.70
  3. Turn valves to circulate water through cores, or spray water on filled molds to cool and solidify metal.70
  4. Pour and regulate the flow of molten metal into molds and forms to produce ingots or other castings, using ladles or hand-controlled mechanisms.69
Hardest to automate

Where people still matter

These tasks score lowest on automation feasibility—physical presence, judgement, accountability and real-world variability all resist end-to-end automation.

  1. Remove solidified steel or slag from pouring nozzles, using long bars or oxygen burners.01
  2. Assemble and embed cores in casting frames, using hand tools and equipment.02
  3. Remove metal ingots or cores from molds, using hand tools, cranes, and chain hoists.03
  4. Repair and maintain metal forms and equipment, using hand tools, sledges, and bars.04
  5. Examine molds to ensure they are clean, smooth, and properly coated.05
Where else this work leads

Related occupations

Occupations O*NET links to this one. Relatedness reflects shared work, not a claim that these roles are safer.

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AI risk 44

Molding, Coremaking, and Casting Machine Setters, Operators, and Tenders, Metal and Plastic

Closely related work

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Beyond AI capability

Adoption and labour-market outlook

Structural factors are kept separate from raw capability so you can see what actually resists automation. Adoption pressure and labour-market resilience are still provisional models—25% of this occupation’s replacement-risk weight rests on them.

Human dependency45
Physical dependency64
Adoption pressure43
Labour-market resilience53
Methodology & sources

O*NET 30.3 occupational data interpreted through the JobsVsAI capability, automation and structural-constraint models.

Confidence82/100
CalculatedAug 21, 2026
Read methodology →