53
/100

SOC 51-2041

Structural Metal Fabricators and Fitters

ElevatedFrey/Osborne: 41.0%

Risk Score

โš ๏ธ

53/100

Elevated

US Employment

๐Ÿ‘ฅ

53,380

Total workers

Median Wage

๐Ÿ’ฐ

$50K

$37K โ€“ $71K

Projected Growth

๐Ÿ“ˆ

-16.3%

2023-2033 (BLS)

GenAI Exposure

๐Ÿค–

10/100

Low exposure

How we calculate these numbers โ†’

๐Ÿ’ก Structural Metal Fabricators and Fitters face a risk score of 53/100 โ€” 9 points above the national average of 44. With only 10/100 GenAI exposure, most core tasks remain resistant to current AI capabilities. See our methodology โ†’

๐Ÿ’ก Workers in this field earn $50K ($4K 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 53/100, Structural Metal Fabricators and Fitters faces moderate automation pressure. While tasks like predictive maintenance reducing manual inspection roles are increasingly handled by AI, the role retains significant human elements. The 53,380 workers in this occupation should focus on strengthening skills in handling non-standard materials and configurations and setup and calibration of custom production runs to stay ahead. The role will likely evolve rather than disappear.

Will AI Replace Structural Metal Fabricators and Fitters?

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

โš ๏ธ Top Risk Factors

1

Predictive maintenance reducing manual inspection roles

2

Cobots handling repetitive material handling tasks

3

Automated CNC programming and machine operation

4

Industrial robotics replacing manual assembly tasks

๐Ÿ›ก๏ธ Tasks Safe from Automation

โœ“

Handling non-standard materials and configurations

โœ“

Setup and calibration of custom production runs

โœ“

Quality judgment requiring tactile and visual inspection

โœ“

Troubleshooting complex equipment malfunctions

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

Verify conformance of workpieces to specifications, using squares, rulers, and measuring tapes.

โ€ข

Study engineering drawings and blueprints to determine materials requirements and task sequences.

โ€ข

Position, align, fit, and weld parts to form complete units or subunits, following blueprints and layout specifications, and using jigs, welding torches, and hand tools.

โ€ข

Lay out and examine metal stock or workpieces to be processed to ensure that specifications are met.

โ€ข

Tack-weld fitted parts together.

๐Ÿ’ป Technology Skills

โ€ข

Computer aided design CAD software

โ€ข

Enterprise resource planning ERP software

โ€ข

Spreadsheet software

โ€ข

Office suite software

โ€ข

Electronic mail software

๐ŸŽ“ Key Knowledge Areas

โ€ข

Mathematics

โ€ข

Production and Processing

โ€ข

Mechanical

โ€ข

English Language

โ€ข

Administration and Management

๐Ÿ“Š vs National Average

Median Wage$50K
+$4K

National avg: $46K

Risk Score53/100
+9

National avg: 44/100

GenAI Exposure10/100
-28

National avg: 38/100

Projected Growth-16.3%
-20.0%

National avg: 3.7%

๐Ÿ”„ Career Transition Paths

OccupationRiskWageOverlap
Engineers20$106K51%
First-Line Supervisors of Transportation and Material Moving Workers, Except Aircraft Cargo Handling Supervisors25$62K61%
Fabric and Apparel Patternmakers33$68K70%