AI exposure Production
Will AI replace pourers and casters?
Pourers and Casters, Metal. US occupation 51-4052.
The reading
0.0%
of the time pourers and casters spend on their work goes on tasks where AI is already being used to do that work.of pourers and casters' working hours go on tasks AI has already started taking off their plate.
Ranked 346 of 756 US occupations. No AI use seen in the work yet, along with 410 other occupations.No handover started yet, along with 410 other occupations.
Per cent of working time Square-law scale
Average US job 7.7%
Among the least exposed jobs there are.Still waiting for liberation.
What AI already does for pourers and castersWhat pourers and casters no longer do alone
O*NET lists 16 tasks for pourers and casters. None of them shows meaningful AI use at work yet.
What it does not touch, yetWhat still needs a human
16 of the 16 tasks show no AI use at work in the data.
- Collect samples, or signal workers to sample metal for analysis.Core task
- Examine molds to ensure they are clean, smooth, and properly coated.Core task
- Load specified amounts of metal and flux into furnaces or clay crucibles.Core task
- Position equipment such as ladles, grinding wheels, pouring nozzles, or crucibles, or signal other workers to position equipment.Core 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.Core task
- Read temperature gauges and observe color changes, adjusting furnace flames, torches, or electrical heating units as necessary to melt metal to specifications.Core task
Show the other 10
- Remove solidified steel or slag from pouring nozzles, using long bars or oxygen burners.Core task
- Skim slag or remove excess metal from ingots or equipment, using hand tools, strainers, rakes, or burners, collecting scrap for recycling.Core task
- Transport metal ingots to storage areas, using forklifts.Core task
- Add metal to molds to compensate for shrinkage.
- Assemble and embed cores in casting frames, using hand tools and equipment.
- Pull levers to lift ladle stoppers and to allow molten steel to flow into ingot molds to specified heights.
- Remove metal ingots or cores from molds, using hand tools, cranes, and chain hoists.
- Repair and maintain metal forms and equipment, using hand tools, sledges, and bars.
- Stencil identifying information on ingots and pigs, using special hand tools.
- Turn valves to circulate water through cores, or spray water on filled molds to cool and solidify metal.
How that compares
Among the 98 production occupations, pourers and casters rank 74. The group averages 0.8%, and its most exposed job is Computer Numerically Controlled Tool Programmers at 12.1%. The average US occupation sits at 7.7%.
Level with 0.0%
What this does and does not mean
Exposure is observed use, not a forecast. Anthropic maps work conversations with Claude onto the tasks O*NET lists for each job and asks, of the tasks AI could speed up, which are actually being used for at work. A use that does the task outright counts in full and a use that assists a person counts half. The task scores are averaged into the occupation figure by the share of time spent on each task.
A high figure means AI is already part of how this work gets done. It does not mean anyone has been replaced. Anthropic's own reading of the labour market finds no systematic rise in unemployment among exposed workers so far, and about 14% fewer 22 to 25 year olds starting exposed jobs.No measurable rise in unemployment among exposed workers so far, and about 14% fewer 22 to 25 year olds starting these jobs. Gap years for everyone. Labor market impacts, 5 March 2026.
Task list and titles from O*NET 31.0 by the US Department of Labor, Employment and Training Administration, used under the CC BY 4.0 licence. Scores from the Anthropic Economic Index (CC BY). Checked 1 November 2026. How the ranking works.