The Task Exposure Indexv2026.Q3
Occupation · SOC 51-9051.00 · Job Zone 2

AI exposure: Furnace, Kiln, Oven, Drier, and Kettle Operators and Tenders

Operate or tend heating equipment other than basic metal, plastic, or food processing equipment. Includes activities such as annealing glass, drying lumber, curing rubber, removing moisture from materials, or boiling soap.

Reading this score

computed

At 21.4% of weighted task load, Furnace, Kiln, Oven, Drier, and Kettle Operators and Tenders sits at the 39th percentile, below the point where a job's centre of gravity has moved. 65.8% of what this role does is untouched, meaning current systems cannot produce that work at all, whatever the commercial incentive.

What holds the line here is embodiment. Across this occupation's 17 tasks it averages 2.26 out of 3, the highest of the five friction dimensions. In plain terms, the work has to happen in physical space. A language model cannot move matter. Until the robotics to do this work is both good enough and cheap enough to deploy widely, capability in software does not reach it.

The most exposed thing this job does is Record gauge readings, test results, and shift production in log books, at 73.3%. The least is Replace worn or defective equipment parts, at 0.0%. A gap of 73.3% between two parts of the same job is the reason this index publishes at task level. An occupation-wide number would have hidden both.

Within production occupations, this one is more exposed than most. The median across the 107 roles in the group is 16.1%, and only 21 of them score higher than this. Occupational families are not uniform, and the spread inside them is often wider than the gap between them.

What would move this score. Of 17 tasks, 5 are currently banded exposed, 2 assisted and 10 untouched. For that distribution to shift materially would take robotics cheap and reliable enough to deploy at scale, not a better language model. The score is re-computed every quarter against a fresh capability reference, and the change is published rather than quietly applied.

Where the score comes from

judged

Every task is scored through the standardised work activities it maps to. These are this occupation’s averages on the six rubric dimensions. Capability is what AI can do; the other five are what stands in the way.

DimensionMeanScale
Capability1.200-4
Embodiment2.260-3
Presence0.460-3
Accountability0.660-3
Context1.170-3
Verification cost0.850-3

Task by task

17 tasks, O*NET 31.0
TaskExposedAssistedUntouchedImportanceBand
Record gauge readings, test results, and shift production in log books.73.3%26.7%0.0%4.21exposed
Calculate amounts of materials to be loaded into furnaces, adjusting amounts as necessary for specific conditions.55.0%20.0%25.0%4.05exposed
Read and interpret work orders and instructions to determine work assignments, process specifications, and production schedules.41.7%20.8%37.5%4.16exposed
Press and adjust controls to activate, set, and regulate equipment according to specifications.33.3%16.7%50.0%4.22exposed
Monitor equipment operation, gauges, and panel lights to detect deviations from standards.30.0%20.0%50.0%4.51exposed
Melt or refine metal before casting, calculating required temperatures, and observe metal color, adjusting controls as necessary to maintain required temperatures.23.8%13.8%62.5%3.95untouched
Confer with supervisors or other equipment operators to report equipment malfunctions or to resolve production problems.23.3%26.7%50.0%4.25assisted
Direct crane operators and crew members to load vessels with materials to be processed.20.0%30.0%50.0%3.80assisted
Examine or test samples of processed substances, or collect samples for laboratory testing, to ensure conformance to specifications.11.7%13.3%75.0%4.15untouched
Clean, lubricate, and adjust equipment, using scrapers, solvents, air hoses, oil, and hand tools.4.8%3.5%91.7%3.29untouched
Transport materials and products to and from work areas, manually or using carts, handtrucks, or hoists.0.0%0.0%100.0%3.97untouched
Stop equipment and clear blockages or jams, using fingers, wire, or hand tools.0.0%0.0%100.0%4.19untouched
Load equipment receptacles or conveyors with material to be processed, by hand or using hoists.0.0%0.0%100.0%4.15untouched
Remove products from equipment, manually or using hoists, and prepare them for storage, shipment, or additional processing.0.0%0.0%100.0%4.06untouched
Weigh or measure specified amounts of ingredients or materials for processing, using devices such as scales and calipers.0.0%0.0%100.0%3.89untouched
Feed fuel, such as coal and coke, into fireboxes or onto conveyors, and remove ashes from furnaces, using shovels and buckets.0.0%0.0%100.0%3.60untouched
Replace worn or defective equipment parts, using hand tools.0.0%0.0%100.0%3.53untouched

Task text and importance ratings sourced from O*NET 31.0. Shares computed. The occupation score is the importance-weighted mean.

Occupations either side of this one

The four closest scores in the same occupational family, then the four closest anywhere in the index.

Read this carefully. Exposure is not displacement. A high score means current AI systems can produce this work, not that anyone will stop paying a person to do it. Adoption depends on economics, regulation and inertia that this index deliberately does not model. How the score is built.

What this means in practice

Most of this work is not reachable by current systems, so the immediate pressure is on the administrative edges of the role rather than its core: the scheduling, the reporting, the written records. That is where time is recovered.