63
/100

SOC 51-9191

Adhesive Bonding Machine Operators and Tenders

High RiskFrey/Osborne: 95.0%

Risk Score

โš ๏ธ

63/100

High Risk

US Employment

๐Ÿ‘ฅ

12,170

Total workers

Median Wage

๐Ÿ’ฐ

$45K

$31K โ€“ $60K

Projected Growth

๐Ÿ“ˆ

+1%

2023-2033 (BLS)

GenAI Exposure

๐Ÿค–

44/100

Moderate exposure

How we calculate these numbers โ†’

๐Ÿ’ก Adhesive Bonding Machine Operators and Tenders face a risk score of 63/100 โ€” 19 points above the national average of 44. With only 44/100 GenAI exposure, most core tasks remain resistant to current AI capabilities. See our methodology โ†’

๐Ÿ’ก Workers in this field earn $45K. 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 63/100, Adhesive Bonding Machine Operators and Tenders faces moderate automation pressure. While tasks like ai quality inspection via computer vision systems are increasingly handled by AI, the role retains significant human elements. The 12,170 workers in this occupation should focus on strengthening skills in coordinating workflow across diverse production teams and troubleshooting complex equipment malfunctions to stay ahead. The role will likely evolve rather than disappear.

Will AI Replace Adhesive Bonding Machine Operators and Tenders?

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

โš ๏ธ Top Risk Factors

1

AI quality inspection via computer vision systems

2

Predictive maintenance reducing manual inspection roles

3

Cobots handling repetitive material handling tasks

4

Industrial robotics replacing manual assembly tasks

๐Ÿ›ก๏ธ Tasks Safe from Automation

โœ“

Coordinating workflow across diverse production teams

โœ“

Troubleshooting complex equipment malfunctions

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

Align and position materials being joined to ensure accurate application of adhesive or heat sealing.

โ€ข

Adjust machine components according to specifications such as widths, lengths, and thickness of materials and amounts of glue, cement, or adhesive required.

โ€ข

Monitor machine operations to detect malfunctions and report or resolve problems.

โ€ข

Start machines, and turn valves or move controls to feed, admit, apply, or transfer materials and adhesives, and to adjust temperature, pressure, and time settings.

โ€ข

Fill machines with glue, cement, or adhesives.

๐Ÿ’ป Technology Skills

โ€ข

Enterprise resource planning ERP software

โ€ข

Spreadsheet software

โ€ข

Office suite software

โ€ข

Presentation software

โ€ข

Word processing software

๐ŸŽ“ Key Knowledge Areas

โ€ข

Production and Processing

โ€ข

Mechanical

โ€ข

English Language

โ€ข

Mathematics

โ€ข

Customer and Personal Service

๐Ÿ“Š vs National Average

Median Wage$45K
$-1K

National avg: $46K

Risk Score63/100
+19

National avg: 44/100

GenAI Exposure44/100
+6

National avg: 38/100

Projected Growth1.0%
-2.7%

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$68K75%