68
/100

SOC 51-9061

Inspectors, Testers, Sorters, Samplers, and Weighers

High RiskFrey/Osborne: 98.0%

Risk Score

โš ๏ธ

68/100

High Risk

US Employment

๐Ÿ‘ฅ

591,180

Total workers

Median Wage

๐Ÿ’ฐ

$47K

$35K โ€“ $76K

Projected Growth

๐Ÿ“ˆ

0%

2023-2033 (BLS)

GenAI Exposure

๐Ÿค–

63/100

High exposure

How we calculate these numbers โ†’

๐Ÿ’ก Inspectors, Testers, Sorters, Samplers, and Weighers face a risk score of 68/100 โ€” 24 points above the national average of 44. With 63/100 GenAI exposure, this occupation faces significant pressure from AI tools despite weak projected growth. See our methodology โ†’

๐Ÿ’ก Workers in this field earn $47K ($1K 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 68/100, Inspectors, Testers, Sorters, Samplers, and Weighers faces moderate automation pressure. While tasks like automated data interpretation and insight generation are increasingly handled by AI, the role retains significant human elements. The 591,180 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 Inspectors, Testers, Sorters, Samplers, and Weighers?

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

โš ๏ธ Top Risk Factors

1

Automated data interpretation and insight generation

2

Industrial robotics replacing manual assembly tasks

3

Large language model automation of analysis tasks

4

AI summarization replacing manual report compilation

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

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

Discard or reject products, materials, or equipment not meeting specifications.

โ€ข

Mark items with details, such as grade or acceptance-rejection status.

โ€ข

Measure dimensions of products to verify conformance to specifications, using measuring instruments, such as rulers, calipers, gauges, or micrometers.

โ€ข

Notify supervisors or other personnel of production problems.

โ€ข

Inspect, test, or measure materials, products, installations, or work for conformance to specifications.

๐Ÿ’ป Technology Skills

โ€ข

Data base management system software

โ€ข

Content workflow software

โ€ข

Computer aided design CAD software

โ€ข

Computer aided manufacturing CAM software

โ€ข

Industrial control software

๐ŸŽ“ Key Knowledge Areas

โ€ข

Production and Processing

โ€ข

English Language

โ€ข

Customer and Personal Service

โ€ข

Mechanical

โ€ข

Mathematics

๐Ÿ“Š vs National Average

Median Wage$47K
+$1K

National avg: $46K

Risk Score68/100
+24

National avg: 44/100

GenAI Exposure63/100
+25

National avg: 38/100

Projected Growth0.0%
-3.7%

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$68K70%