AI exposure by occupation, O*NET 51-6042.00
Will AI replace Shoe Machine Operators and Tenders?
Shoe Machine Operators and Tenders: AI can already handle 1 of 19 tasks; most of the work is hands-on, and the part AI can address mostly needs an efficient-tier model.
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Every task, scored
The 19 tasks O*NET 30.3 lists for Shoe Machine Operators and Tenders, from most to least exposed. 1 reach 60 or more, the level at which AI already handles a task.
| Task | AI exposure | Evidence | Model tier |
|---|---|---|---|
| Remove and examine shoes, shoe parts, and designs to verify conformance to specifications such as proper embedding of stitches in channels. | Estimated | Efficient | |
| Inspect finished products to ensure that shoes have been completed according to specifications. | Estimated | Efficient | |
| Align parts to be stitched, following seams, edges, or markings, before positioning them under needles. | Estimated | No tier | |
| Operate or tend machines to join, decorate, reinforce, or finish shoes and shoe parts. | Estimated | No tier | |
| Switch on machines, lower pressure feet or rollers to secure parts, and start machine stitching, using hand, foot, or knee controls. | Estimated | No tier | |
| Fill shuttle spools with thread from a machine's bobbin winder by pressing a foot treadle. | Estimated | No tier | |
| Staple sides of shoes, pressing a foot treadle to position and hold each shoe under the feeder of the machine. | Estimated | No tier | |
| Draw thread through machine guide slots, needles, and presser feet in preparation for stitching, or load rolls of wire through machine axles. | Estimated | No tier | |
| Study work orders or shoe part tags to obtain information about workloads, specifications, and the types of materials to be used. | Estimated | No tier | |
| Perform routine equipment maintenance such as cleaning and lubricating machines or replacing broken needles. | Estimated | No tier | |
| Position dies on material in a manner that will obtain the maximum number of parts from each portion of material. | Estimated | No tier | |
| Test machinery to ensure proper functioning before beginning production. | Estimated | No tier | |
| Collect shoe parts from conveyer belts or racks and place them in machinery such as ovens or on molds for dressing, returning them to conveyers or racks to send them to the next work station. | Estimated | No tier | |
| Select and place spools of thread or pre-wound bobbins into shuttles, or onto spindles or loupers of stitching machines. | Estimated | No tier | |
| Cut excess thread or material from shoe parts, using scissors or knives. | Estimated | No tier | |
| Turn setscrews on needle bars, and position required numbers of needles in stitching machines. | Estimated | No tier | |
| Turn knobs to adjust stitch length and thread tension. | Estimated | No tier | |
| Turn screws to regulate size of staples. | Estimated | No tier | |
| Hammer loose staples for proper attachment. | Estimated | No tier |
Observed: scored from AI use recorded in the Anthropic Economic Index (June 2026 release), 0 of 19 tasks. Estimated: scored from the task's O*NET 30.3 work activity, 19 of 19. Importance is O*NET's 1 to 5 rating of how central the task is. Model tier is the lowest tier that can do the task under the published rubric; "No tier" marks hands-on work.
The model tier this role needs
An efficient-tier model or lower covers 11% of the role's importance-weighted task work. 11% of the work is something AI can address at some tier, and 89% is hands-on.
Efficient, standard and frontier tiers come from the JobRoute model tier reference. The recommended tier is the lowest one that covers 80% of the work AI can address. How the method works.
Wages, employment and outlook
- US employment
- 3,280
- Median annual wage
- $35,650
- Middle half of earners
- $29,090 to $43,090
- Projected change, 2024 to 2034
- -3.7%
Employment and wages: BLS Occupational Employment and Wage Statistics, May 2025, national. Projection: BLS Employment Projections 2024 to 2034.
Adjacent roles
The occupations that reuse the most of this role's skills, with the usual time to move. These are the first places to look when you plan to redeploy or retrain people in this role.
- Sewing Machine Operators 77% skill overlap, about 8 months to move Exposure22
- Shoe and Leather Workers and Repairers 74% skill overlap, about 9 months to move Exposure17
- Adhesive Bonding Machine Operators and Tenders 69% skill overlap, about 11 months to move Exposure19
- Textile Knitting and Weaving Machine Setters, Operators, and Tenders 68% skill overlap, about 12 months to move Exposure19
- Packaging and Filling Machine Operators and Tenders 67% skill overlap, about 12 months to move Exposure27
Skill overlap and transition time from the JobRoute role adjacency graph on O*NET 30.3 skills.
Questions about Shoe Machine Operators and Tenders and AI
Will AI replace Shoe Machine Operators and Tenders?
AI already handles 1 of the 19 tasks O*NET lists for this occupation, at a task exposure of 60 or more, and the role's importance-weighted exposure is 19 out of 100. JobRoute scores tasks, not whole jobs, so the score shows how much of the work changes rather than whether the job disappears. BLS projects employment to change by -3.7% from 2024 to 2034.
What is the AI exposure of Shoe Machine Operators and Tenders?
19 out of 100 on JobRoute's task exposure measure, the importance-weighted average of the role's O*NET task scores. Higher means more of the work is AI-doable today. 0 of the 19 task scores are observed in the Anthropic Economic Index (June 2026 release), and the other 19 are estimated from each task's O*NET work activity.
Which Shoe Machine Operators and Tenders tasks can AI already do?
The tasks with the highest exposure are: Remove and examine shoes, shoe parts, and designs to verify conformance to specifications such as proper embedding of stitches in channels. It is the only task that reach 60 or more.
What AI model tier does this role need?
An efficient-tier model or lower covers 11% of the role's importance-weighted task work, and 89% is hands-on work that no model tier covers. JobRoute assigns each task the lowest tier that can do it under a published rubric and recommends the lowest tier that covers 80% of the work AI can address.
How many people work as Shoe Machine Operators and Tenders, and what do they earn?
3,280 people in the United States, with a median annual wage of $35,650 (BLS Occupational Employment and Wage Statistics, May 2025). BLS Employment Projections expect a change of -3.7% from 2024 to 2034.
How to cite
Data version 2026-11-02, JobRoute method v1.0.0. Download all occupations or this occupation as JSON. Methodology.
JobRoute (2026). AI exposure: Shoe Machine Operators and Tenders. Data version 2026-11-02, method v1.0.0. Built on O*NET 30.3, BLS OEWS May 2025 and the Anthropic Economic Index (June 2026). CC BY 4.0. https://www.jobroute.ai/jobs/shoe-machine-operators-and-tenders
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