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Manufacturing & Production · Updated Aug 2026

Paper Goods Machine Setters, Operators, and Tenders

Set up, operate, or tend paper goods machines that perform a variety of functions, such as converting, sawing, corrugating, banding, wrapping, boxing, stitching, forming, or sealing paper or paperboard sheets into products.

JVS 2.0.0-phase4b
AI Exposure
39/100
Low

How much of this occupation’s work can be materially affected by current AI systems.

Replacement Risk
39/100
Low

How likely exposure is to translate into reduced human demand.

Includes provisional estimates for AI adoption pressure and labour-market resilience. How this is measured

Evidence quality
Confidence83/100
Task coverage89%

Confidence reflects task coverage, mapping and capability-evidence quality, and how much of the score rests on provisional inputs.

Task-level evidence

What is driving the score?

Occupation scores are built from the task mix—not a single prediction about a job title.

JVS 2.0.0-phase4b
TaskImportanceAI impactExposure
Place rolls of paper or cardboard on machine feed tracks, and thread paper through gluing, coating, and slitting rollers.High
68
Stamp products with information such as dates, using hand stamps or automatic stamping devices.Medium
70
Adjust guide assemblies, forming bars, and folding mechanisms according to specifications, using hand tools.High
67
Lift tote boxes of finished cartons, and dump cartons into feed hoppers.Medium
70
Monitor finished cartons as they drop from forming machines into rotating hoppers and into gravity feed chutes to prevent jamming.High
36
Examine completed work to detect defects and verify conformance to work orders, and adjust machinery as necessary to correct production problems.High
31
Observe operation of various machines to detect and correct machine malfunctions such as improper forming, glue flow, or pasteboard tension.High
31
Install attachments to machines for gluing, folding, printing, or cutting.High
22
Start machines and move controls to regulate tension on pressure rolls, to synchronize speed of machine components, and to adjust temperatures of glue or paraffin.High
23
Measure, space, and set saw blades, cutters, and perforators, according to product specifications.High
22
Remove finished cores, and stack or place them on conveyors for transfer to other work areas.Medium
17
Cut products to specified dimensions, using hand or power cutters.High
16
Most exposed

Where AI can do more

Routine, digitized, and highly repeatable tasks face the greatest pressure.

  1. Stamp products with information such as dates, using hand stamps or automatic stamping devices.70
  2. Lift tote boxes of finished cartons, and dump cartons into feed hoppers.70
  3. Place rolls of paper or cardboard on machine feed tracks, and thread paper through gluing, coating, and slitting rollers.68
  4. Adjust guide assemblies, forming bars, and folding mechanisms according to specifications, using hand tools.67
Hardest to automate

Where people still matter

These tasks score lowest on automation feasibility—physical presence, judgement, accountability and real-world variability all resist end-to-end automation.

  1. Cut products to specified dimensions, using hand or power cutters.01
  2. Remove finished cores, and stack or place them on conveyors for transfer to other work areas.02
  3. Measure, space, and set saw blades, cutters, and perforators, according to product specifications.03
  4. Install attachments to machines for gluing, folding, printing, or cutting.04
  5. Start machines and move controls to regulate tension on pressure rolls, to synchronize speed of machine components, and to adjust temperatures of glue or paraffin.05
Where else this work leads

Related occupations

Occupations O*NET links to this one. Relatedness reflects shared work, not a claim that these roles are safer.

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Beyond AI capability

Adoption and labour-market outlook

Structural factors are kept separate from raw capability so you can see what actually resists automation. Adoption pressure and labour-market resilience are still provisional models—25% of this occupation’s replacement-risk weight rests on them.

Human dependency64
Physical dependency67
Adoption pressure41
Labour-market resilience63
Methodology & sources

O*NET 30.3 occupational data interpreted through the JobsVsAI capability, automation and structural-constraint models.

Confidence83/100
CalculatedAug 21, 2026
Read methodology →