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# Will kiln and furnace operators be replaced by AI?

Updated October 2026

Kiln and furnace operators score 26 out of 100 for AI exposure. 65% of their task time needs a person. AI can do 9% and helps with 26%.

-   **9%** AI can do it
-   **26%** AI helps
-   **65%** Needs a person

Low exposure

Lower than 69% of the 923 jobs we scored.

## Task by task

We graded 17 tasks, most exposed first. AI can do 1 of them, helps with 4 and leaves 12 to people.

| Task | AI exposure |
| --- | --- |
| Record gauge readings, test results, and shift production in log books. Logging readings and shift output is routine digital recordkeeping. | 70% AI can do it |
| Calculate amounts of materials to be loaded into furnaces, adjusting amounts as necessary for specific conditions. Charge calculations are formula-based, AI can compute and a person verifies. | 60% AI helps |
| Read and interpret work orders and instructions to determine work assignments, process specifications, and production schedules. AI can parse work orders and schedules, a person confirms assignments. | 55% AI helps |
| Monitor equipment operation, gauges, and panel lights to detect deviations from standards. Sensors and software can flag deviations, but people still watch equipment. | 40% AI helps |
| Melt or refine metal before casting, calculating required temperatures, and observe metal color, adjusting controls as necessary to maintain required temperatures. Temperature math is AI-assisted, but judging metal color is visual and hands-on. | 25% AI helps |

## How kiln and furnace operators compare

All jobs (923)

Production (107)

The dark line is **kiln and furnace operators, at 26**. Each dot is a score, and darker dots mean more jobs share it. The short marks are the averages, 37 for all jobs and 22 for production.

## Pay and outlook in the US

Median pay

$48,040 a year, May 2025

People employed

14,280 in the US, May 2025

Projected change in jobs

+2.6% from 2024 to 2034

## Skills to build

-   Verify furnace charge calculations before loading material
-   Log gauge readings and shift output in Microsoft Excel
-   Track material stock in inventory tracking software
-   Run machine operation software to set and monitor controls
-   Judge metal color by eye during melting and refining
-   Clear jams and replace worn parts with hand tools

## Safer roles nearby

5 related jobs with lower scores.

-   [Separating machine operators20 out of 100](https://www.aigentcy.com/ai-exposure/separating-machine-operators/)
-   [Furnace operators22 out of 100](https://www.aigentcy.com/ai-exposure/furnace-operators/)
-   [Heat treaters25 out of 100](https://www.aigentcy.com/ai-exposure/heat-treaters/)
-   [Cleaning equipment operators25 out of 100](https://www.aigentcy.com/ai-exposure/cleaning-equipment-operators/)
-   [Machine feeders20 out of 100](https://www.aigentcy.com/ai-exposure/machine-feeders/)

## Questions about kiln and furnace operators and AI

Will AI replace kiln and furnace operators?

Partly. About 3 in 10 working hours go to tasks AI can already do, mostly logging readings and shift output and calculating furnace charge amounts. Setting physical controls, clearing jams, moving material, and cleaning equipment stay with people because they need a person at the equipment.

Which tasks is AI taking over in this job?

Recordkeeping and charge math come first. Logging gauge readings, test results, and shift output in log books scores 70 on exposure, the highest in this job, so software can write those entries from sensor data. Charge calculations score 60, and AI can compute the material amounts while a person checks them before loading.

Which tasks stay human in this job?

Clearing jams, feeding fuel, moving material, and cleaning equipment stay with people, each scoring 3 to 5 on exposure. Clearing jams manually takes a body at the equipment and dexterity with wire and hand tools. Shoveling coal and ash is heavy work near fire, so no software can do it.

How can kiln and furnace operators stay valuable?

Check AI-generated charge calculations against the material specs before each load. Keep gauge logs in Microsoft Excel and Word so entries match what the panel shows. Learn to judge metal color and adjust controls manually, which keeps those tasks with a person. Use inventory tracking software to confirm stock on hand before each charge.

## Related jobs

-   [Forming press operators26 out of 100](https://www.aigentcy.com/ai-exposure/forming-press-operators/)
-   [Dye machine operators29 out of 100](https://www.aigentcy.com/ai-exposure/dye-machine-operators/)
-   [Crushing and grinding machine operators26 out of 100](https://www.aigentcy.com/ai-exposure/crushing-and-grinding-machine-operators/)
-   [Adhesive bonding machine operators22 out of 100](https://www.aigentcy.com/ai-exposure/adhesive-bonding-machine-operators/)

## Next steps for kiln and furnace operators

-   ### Check your job
    
    Your job title is a rough guide. Your tasks decide your score. Paste your job description or CV to see which tasks AI can do.
    
    [Check your job](https://www.aigentcy.com/tools/ai-exposure-checker/) [Check your CV](https://www.aigentcy.com/tools/cv-checker/)
    
-   ### Estimate team savings
    
    The score is per person. Add headcount and salary to see the hours AI can take on in a team of kiln and furnace operators, and what they cost.
    
    [Estimate what AI saves a team of kiln and furnace operators](https://www.aigentcy.com/tools/team-ai-audit/?role=kiln-and-furnace-operators) [Work out the return on automation](https://www.aigentcy.com/tools/ai-savings-calculator/)
    

### Check which roles in your team AI can take on

We map your team's tasks, show what AI can do today and build the automations that pay back first.

[Book an AI audit](https://www.aigentcy.com/audit/)

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-   [**Jobs A to Z**Every job we score, by first letter.](https://www.aigentcy.com/ai-exposure/jobs/)
-   [**AI exposure by industry**Average scores for 22 job groups.](https://www.aigentcy.com/ai-exposure/industries/)
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-   [**How we score AI exposure**The grading, the weights and every source.](https://www.aigentcy.com/ai-exposure/methodology/)

Sources and licences

Occupation data from the O\*NET 30.3 Database by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA), used under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) and modified by Aigentcy. O\*NET® is a trademark of USDOL/ETA. Wage, employment and projection data from the U.S. Bureau of Labor Statistics. EU occupation names from ESCO, European Commission. AI usage signals from the Anthropic Economic Index (CC BY) and Microsoft Research (CC BY 4.0). [Methodology and sources](https://www.aigentcy.com/ai-exposure/methodology/). Scores © Aigentcy. Quote them with a link to the page.
