59
/100

SOC 49-2011

Computer, Automated Teller, and Office Machine Repairers

ElevatedFrey/Osborne: 74.0%

Risk Score

โš ๏ธ

59/100

Elevated

US Employment

๐Ÿ‘ฅ

73,010

Total workers

Median Wage

๐Ÿ’ฐ

$47K

$35K โ€“ $70K

Projected Growth

๐Ÿ“ˆ

-0.9%

2023-2033 (BLS)

GenAI Exposure

๐Ÿค–

49/100

Moderate exposure

How we calculate these numbers โ†’

๐Ÿ’ก Computer, Automated Teller, and Office Machine Repairers face a risk score of 59/100 โ€” 15 points above the national average of 44. With only 49/100 GenAI exposure, most core tasks remain resistant to current AI capabilities. See our methodology โ†’

๐Ÿ’ก Workers in this field earn $47K ($550 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 59/100, Computer, Automated Teller, and Office Machine Repairers faces moderate automation pressure. While tasks like ai parts inventory and supply chain optimization are increasingly handled by AI, the role retains significant human elements. The 73,010 workers in this occupation should focus on strengthening skills in diagnosing novel equipment failures through physical inspection and working in confined, elevated, or hazardous spaces to stay ahead. The role will likely evolve rather than disappear.

Will AI Replace Computer, Automated Teller, and Office Machine Repairers?

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

โš ๏ธ Top Risk Factors

1

AI parts inventory and supply chain optimization

2

Robotic inspection of hard-to-reach equipment

3

Augmented reality-guided remote diagnostics

4

Predictive maintenance AI reducing reactive repair needs

๐Ÿ›ก๏ธ Tasks Safe from Automation

โœ“

Diagnosing novel equipment failures through physical inspection

โœ“

Working in confined, elevated, or hazardous spaces

โœ“

Adapting repairs to non-standard or legacy equipment

โœ“

Customer communication about technical issues

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

Reassemble machines after making repairs or replacing parts.

โ€ข

Converse with customers to determine details of equipment problems.

โ€ข

Disassemble machines to examine parts, such as wires, gears, or bearings for wear or defects, using hand or power tools and measuring devices.

โ€ข

Advise customers concerning equipment operation, maintenance, or programming.

โ€ข

Align, adjust, or calibrate equipment according to specifications.

๐Ÿ’ป Technology Skills

โ€ข

Document management software

โ€ข

Helpdesk or call center software

โ€ข

Network security or virtual private network VPN management software

โ€ข

Data base user interface and query software

โ€ข

Program testing software

๐ŸŽ“ Key Knowledge Areas

โ€ข

Computers and Electronics

โ€ข

Customer and Personal Service

โ€ข

Mechanical

โ€ข

Engineering and Technology

โ€ข

English Language

๐Ÿ“Š vs National Average

Median Wage$47K
+$550

National avg: $46K

Risk Score59/100
+15

National avg: 44/100

GenAI Exposure49/100
+11

National avg: 38/100

Projected Growth-0.9%
-4.6%

National avg: 3.7%

๐Ÿ”„ Career Transition Paths

OccupationRiskWageOverlap
Engineers20$106K63%
Electrical Power-Line Installers and Repairers28$93K77%
Supervisors of Installation, Maintenance, and Repair Workers33$78K82%