How much of this occupation’s work can be materially affected by current AI systems.
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
Confidence reflects task coverage, mapping and capability-evidence quality, and how much of the score rests on provisional inputs.
What is driving the score?
Occupation scores are built from the task mix—not a single prediction about a job title.
Where AI can do more
Routine, digitized, and highly repeatable tasks face the greatest pressure.
- Place glass into dies or molds of presses and control presses to form products, such as glassware components or optical blanks.74
- Spray or swab molds with oil solutions to prevent adhesion of glass.74
- Heat glass to pliable stage, using gas flames or ovens and rotating glass to heat it uniformly.74
- Record manufacturing information, such as quantities, sizes, or types of goods produced.74
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.
- Place glass into dies or molds of presses and control presses to form products, such as glassware components or optical blanks.01
- Spray or swab molds with oil solutions to prevent adhesion of glass.02
- Heat glass to pliable stage, using gas flames or ovens and rotating glass to heat it uniformly.03
- Blow tubing into specified shapes to prevent glass from collapsing, using compressed air or own breath, or blow and rotate gathers in molds or on boards to obtain final shapes.04
- Record manufacturing information, such as quantities, sizes, or types of goods produced.05
Related occupations
Occupations O*NET links to this one. Relatedness reflects shared work, not a claim that these roles are safer.
Extruding, Forming, Pressing, and Compacting Machine Setters, Operators, and Tenders
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Compare these careers →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.
O*NET 30.3 occupational data interpreted through the JobsVsAI capability, automation and structural-constraint models.
