π‘ Upholsterers have a composite risk score of 43/100 (Frey-Osborne probability: 39%, GenAI exposure: 44/100). With 20,990 workers in the US, this occupation faces moderate but manageable AI pressure. Full occupation profile β
π― The Verdict
Possible. Significant task automation is underway β workers should actively upskill.
With 20,990 workers and a median wage of $46K,upholsterers represent a significant portion of the US workforce. Their GenAI exposure index is 44%, meaning a minority of their core tasks overlap with current generative AI capabilities.
Risk Score
43/100
Employment
20,990
Median Wage
$46K
GenAI Exposure
44%
β οΈ Top Risk Factors
Smart factory scheduling and production optimization
Predictive maintenance reducing manual inspection roles
Cobots handling repetitive material handling tasks
Automated CNC programming and machine operation
π‘οΈ Tasks AI Can't Easily Replace
Setup and calibration of custom production runs
Quality judgment requiring tactile and visual inspection
Troubleshooting complex equipment malfunctions
Coordinating workflow across diverse production teams
π Career Transition Paths
Related occupations with lower AI risk and high skills overlap:
Engineers
51% skills overlap Β· $106K median wage
First-Line Supervisors of Transportation and Material Moving Workers, Except Aircraft Cargo Handling Supervisors
61% skills overlap Β· $62K median wage
Fabric and Apparel Patternmakers
80% skills overlap Β· $68K median wage
β Frequently Asked Questions
Will AI completely replace upholsterers?
Possible. Significant task automation is underway β workers should actively upskill.
What is the AI risk score for upholsterers?
Upholsterers have a composite AI automation risk score of 43 out of 100, classified as "Elevated".
How many upholsterers are there in the US?
There are approximately 20,990 upholsterers employed in the United States.
What do upholsterers earn?
The median annual wage for upholsterers is $46K.
What skills should upholsterers develop?
Focus on tasks AI can't easily replicate: setup and calibration of custom production runs, quality judgment requiring tactile and visual inspection, troubleshooting complex equipment malfunctions, coordinating workflow across diverse production teams. These human-centric skills will become more valuable as routine tasks are automated.