59
/100

SOC 51-7041

Sawing Machine Setters, Operators, and Tenders, Wood

ElevatedFrey/Osborne: 86.0%

Risk Score

โš ๏ธ

59/100

Elevated

US Employment

๐Ÿ‘ฅ

43,140

Total workers

Median Wage

๐Ÿ’ฐ

$40K

$30K โ€“ $57K

Projected Growth

๐Ÿ“ˆ

-0.6%

2023-2033 (BLS)

GenAI Exposure

๐Ÿค–

38/100

Moderate exposure

How we calculate these numbers โ†’

๐Ÿ’ก Sawing Machine Setters, Operators, and Tenders, Wood face a risk score of 59/100 โ€” 15 points above the national average of 44. With only 38/100 GenAI exposure, most core tasks remain resistant to current AI capabilities. See our methodology โ†’

๐Ÿ’ก Workers in this field earn $40K. 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 59/100, Sawing Machine Setters, Operators, and Tenders, Wood faces moderate automation pressure. While tasks like automated cnc programming and machine operation are increasingly handled by AI, the role retains significant human elements. The 43,140 workers in this occupation should focus on strengthening skills in setup and calibration of custom production runs and coordinating workflow across diverse production teams to stay ahead. The role will likely evolve rather than disappear.

Will AI Replace Sawing Machine Setters, Operators, and Tenders, Wood?

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

โš ๏ธ Top Risk Factors

1

Automated CNC programming and machine operation

2

Smart factory scheduling and production optimization

3

AI quality inspection via computer vision systems

4

Cobots handling repetitive material handling tasks

๐Ÿ›ก๏ธ Tasks Safe from Automation

โœ“

Setup and calibration of custom production runs

โœ“

Coordinating workflow across diverse production teams

โœ“

Quality judgment requiring tactile and visual inspection

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

Inspect and measure workpieces to mark for cuts and to verify the accuracy of cuts, using rulers, squares, or caliper rules.

โ€ข

Adjust saw blades, using wrenches and rulers, or by turning handwheels or pressing pedals, levers, or panel buttons.

โ€ข

Mount and bolt sawing blades or attachments to machine shafts.

โ€ข

Set up, operate, or tend saws or machines that cut or trim wood to specified dimensions, such as circular saws, band saws, multiple-blade sawing machines, scroll saws, ripsaws, or crozer machines.

โ€ข

Inspect stock for imperfections or to estimate grades or qualities of stock or workpieces.

๐Ÿ’ป Technology Skills

โ€ข

Document management software

โ€ข

Inventory management software

โ€ข

Industrial control software

โ€ข

Spreadsheet software

โ€ข

Office suite software

๐ŸŽ“ Key Knowledge Areas

โ€ข

Production and Processing

โ€ข

Mechanical

โ€ข

Public Safety and Security

โ€ข

Mathematics

โ€ข

Education and Training

๐Ÿ“Š vs National Average

Median Wage$40K
$-6K

National avg: $46K

Risk Score59/100
+15

National avg: 44/100

GenAI Exposure38/100
0

National avg: 38/100

Projected Growth-0.6%
-4.3%

National avg: 3.7%

๐Ÿ”„ Career Transition Paths

OccupationRiskWageOverlap
Engineers20$106K63%
First-Line Supervisors of Transportation and Material Moving Workers, Except Aircraft Cargo Handling Supervisors25$62K53%
Fabric and Apparel Patternmakers33$68K82%