42/100
ModerateHow much of this occupation’s work can be materially affected by current AI systems.
42/100
ModerateHow 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.
Task-level evidence
What is driving the score?
Occupation scores are built from the task mix—not a single prediction about a job title.
TaskImportanceAI impactExposure
Assign polish, symmetry, and clarity grades to stones, according to established grading systems.High72
Estimate wholesale and retail value of gems, following pricing guides, market fluctuations, and other relevant economic factors.High73
Sort rough diamonds into categories based on shape, size, color, and quality.High75
Select shaping wheels for tasks, and mix and apply abrasives, bort, or polishing compounds.Medium75
Identify and document stones' clarity characteristics, using plot diagrams.High74
Examine gems during processing to ensure accuracy of angles and positions of cuts or bores, using magnifying glasses, loupes, or shadowgraphs.High21
Examine diamonds or gems to ascertain the shape, cut, and width of cut stones, or to select the cuts that will result in the biggest, best quality stones.High21
Measure sizes of stones' bore holes and cuts to ensure adherence to specifications, using precision measuring instruments.Medium24
Hold stones, gems, dies, or styluses against rotating plates, wheels, saws, or slitters to cut, shape, slit, grind, or polish them.High18
Secure gems or diamonds in holders, chucks, dops, lapidary sticks, or blocks for cutting, polishing, grinding, drilling, or shaping.High18
Examine gem surfaces and internal structures, using polariscopes, refractometers, microscopes, and other optical instruments, to differentiate between stones, to identify rare specimens, or to detect flaws, defects, or peculiarities affecting gem values.High24
Where AI can do more
Routine, digitized, and highly repeatable tasks face the greatest pressure.
- Sort rough diamonds into categories based on shape, size, color, and quality.75
- Select shaping wheels for tasks, and mix and apply abrasives, bort, or polishing compounds.75
- Identify and document stones' clarity characteristics, using plot diagrams.74
- Estimate wholesale and retail value of gems, following pricing guides, market fluctuations, and other relevant economic factors.73
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.
- Hold stones, gems, dies, or styluses against rotating plates, wheels, saws, or slitters to cut, shape, slit, grind, or polish them.01
- Secure gems or diamonds in holders, chucks, dops, lapidary sticks, or blocks for cutting, polishing, grinding, drilling, or shaping.02
- Examine diamonds or gems to ascertain the shape, cut, and width of cut stones, or to select the cuts that will result in the biggest, best quality stones.03
- Examine gems during processing to ensure accuracy of angles and positions of cuts or bores, using magnifying glasses, loupes, or shadowgraphs.04
- Measure sizes of stones' bore holes and cuts to ensure adherence to specifications, using precision measuring instruments.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.
Jewelers and Precious Stone and Metal Workers
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Related work
Compare these careers →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.
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 →