48
/100

SOC 51-9051

Furnace, Kiln, Oven, Drier, and Kettle Operators and Tenders

ElevatedFrey/Osborne: 37.0%

Risk Score

โš ๏ธ

48/100

Elevated

US Employment

๐Ÿ‘ฅ

16,160

Total workers

Median Wage

๐Ÿ’ฐ

$47K

$35K โ€“ $66K

Projected Growth

๐Ÿ“ˆ

+3%

2023-2033 (BLS)

GenAI Exposure

๐Ÿค–

53/100

Moderate exposure

How we calculate these numbers โ†’

๐Ÿ’ก Furnace, Kiln, Oven, Drier, and Kettle Operators and Tenders face a risk score of 48/100 โ€” 4 points above the national average of 44. With 53/100 GenAI exposure, this occupation faces significant pressure from AI tools despite strong projected growth. See our methodology โ†’

๐Ÿ’ก Workers in this field earn $47K ($700 above the national median). The 3 recommended career transitions all maintain competitive wages while reducing automation exposure. Explore transition paths โ†’

๐Ÿ” AI Impact Analysis

With a risk score of 48/100, Furnace, Kiln, Oven, Drier, and Kettle Operators and Tenders faces moderate automation pressure. While tasks like industrial robotics replacing manual assembly tasks are increasingly handled by AI, the role retains significant human elements. The 16,160 workers in this occupation should focus on strengthening skills in troubleshooting complex equipment malfunctions and quality judgment requiring tactile and visual inspection to stay ahead. The role will likely evolve rather than disappear.

Will AI Replace Furnace, Kiln, Oven, Drier, and Kettle Operators and Tenders?

Read our full analysis with verdict, risk factors, safe tasks, and career transition paths โ†’

โš ๏ธ Top Risk Factors

1

Industrial robotics replacing manual assembly tasks

2

Predictive maintenance reducing manual inspection roles

3

Cobots handling repetitive material handling tasks

4

AI quality inspection via computer vision systems

๐Ÿ›ก๏ธ Tasks Safe from Automation

โœ“

Troubleshooting complex equipment malfunctions

โœ“

Quality judgment requiring tactile and visual inspection

โœ“

Setup and calibration of custom production runs

โœ“

Handling non-standard materials and configurations

๐Ÿ“Š Task Automation Breakdown

Based on O*NET task analysis and GenAI exposure scoring. Shows the estimated proportion of this occupation's core tasks that are automatable by current AI, augmented by AI tools, or require essential human skills.

๐Ÿ“‹ O*NET Task Profile

โ€ข

Monitor equipment operation, gauges, and panel lights to detect deviations from standards.

โ€ข

Confer with supervisors or other equipment operators to report equipment malfunctions or to resolve production problems.

โ€ข

Press and adjust controls to activate, set, and regulate equipment according to specifications.

โ€ข

Record gauge readings, test results, and shift production in log books.

โ€ข

Read and interpret work orders and instructions to determine work assignments, process specifications, and production schedules.

๐Ÿ’ป Technology Skills

โ€ข

Inventory management software

โ€ข

Industrial control software

โ€ข

Spreadsheet software

โ€ข

Word processing software

๐ŸŽ“ Key Knowledge Areas

โ€ข

Mechanical

โ€ข

Production and Processing

โ€ข

Public Safety and Security

โ€ข

Computers and Electronics

โ€ข

English Language

๐Ÿ“Š vs National Average

Median Wage$47K
+$700

National avg: $46K

Risk Score48/100
+4

National avg: 44/100

GenAI Exposure53/100
+15

National avg: 38/100

Projected Growth3.0%
-0.7%

National avg: 3.7%

๐Ÿ”„ Career Transition Paths

OccupationRiskWageOverlap
Engineers20$106K61%
First-Line Supervisors of Transportation and Material Moving Workers, Except Aircraft Cargo Handling Supervisors25$62K51%
Fabric and Apparel Patternmakers33$68K75%