Skills it runs on
The capabilities O*NET rates most important for this occupation — the human ground the work is built on.
See all skills →Occupation · SOC 51-9071.06
Fabricate, finish, or evaluate the quality of gems and diamonds used in jewelry or industrial tools.
Also called: Diamond Cutter · Diamond Setter · Gemologist · Lapidarist · Diamond Grader · Diamond Picker · Diamond Polisher · Diamond Sawer · Facetor · Brilliandeer · Brilliandeer Lopper · Clarity Expert
Job family: Production Occupations
A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch
/roles/role-51-9071-06/context.md directly.
A fast read on where AI already shows up in this occupation, where it stays a copilot, where humans remain in the loop, and what the labor market is doing. Built from observed Claude.ai conversations mapped to O*NET tasks and from published research — measures of usage and exposure, not advice or predictions that the job is going away.
The capabilities O*NET rates most important for this occupation — the human ground the work is built on.
See all skills →Independent published positions, read together — not a forecast.
39th-percentile task overlap — yet about 4,000 openings a year (-5.5% projected, BLS) . What exposure means →
What today's research says about this occupation's exposure to AI, how AI is actually being used in it, and where employment is headed. These are positions within published studies — measures of exposure and usage, not predictions that this job will disappear.
Each study uses its own scale, so the raw scores are not comparable across rows — the percentile (this job's rank among all U.S. occupations with data) is the comparable figure, and sizes the bars.
| Measure | Rank vs all occupations | Percentile | Score |
|---|---|---|---|
| Overall AI exposure (Felten et al.) Moderate | 45th | -0.2 | |
| LLM task exposure, γ (OpenAI / Eloundou) Moderate | 42nd | 0.5 | |
| AI assistant applicability (Microsoft) Moderate | 35th | 0.1 |
OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.0), with simple added tooling (β 0.2), and including AI-powered software (γ 0.5). Higher means more of the job's tasks could be done at least twice as fast — not that they will be automated away.
Most of this job's tasks can be done remotely (Dingel–Neiman), which tends to track with higher digital and AI exposure.
Mixed signals. Today's AI/LLM studies show relatively low exposure for this job, but the older (2013) Frey–Osborne work rated it higher for computerization and robotics. Different eras, different technologies — the AI measures above reflect the current state.
A pre-LLM (2013) estimate of how automatable this job is by computerization and robotics. Shown for historical context only — it is not part of any current AI ranking.
Frey–Osborne probability 0.9 · 89th percentile among occupations · High
Independent U.S. Bureau of Labor Statistics employment projection for 2024–2034 — a labor-market forecast, not an AI-impact forecast.
| Outlook | Declining · -5.5% by 2034 |
| Projected annual openings | 4,000 |
| Employment 2024 → 2034 | 35,100 → 33,200 |
“Annual openings” counts new jobs plus replacements for workers who leave the occupation, so it can be large even when growth is modest.
The ILO's 2025 global study scores generative-AI exposure on the international ISCO-08 occupation system, not US SOC. Bridged through the published (and approximate, many-to-many) IBS O*NET-SOC ↔ ISCO-08 crosswalk, this US occupation corresponds to the international occupation below. Exposure here means how much of the work's tasks today's AI can attempt — task overlap, not automation, adoption, or jobs lost.
| International occupation (ISCO-08) | Task exposure (2025) | Most tasks fall in |
|---|---|---|
| Jewellery and Precious Metal Workers · 7313 | 18% | Not exposed |
Read the whole six-band gradient on the GenAI exposure gradient page. The crosswalk is approximate: a US occupation can map to several international ones, and the ILO scores describe the international occupation, not this exact US role.
All 22 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.
O*NET importance rating, from 1 (not important) to 5 (extremely important).
| Near Vision | 4.1 | |
| Finger Dexterity | 3.6 | |
| Arm-Hand Steadiness | 3.5 | |
| Visual Color Discrimination | 3.4 | |
| Problem Sensitivity | 3.3 | |
| Deductive Reasoning | 3.1 | |
| Category Flexibility | 3.1 | |
| Flexibility of Closure | 3.1 | |
| Manual Dexterity | 3.1 | |
| Control Precision | 3.1 | |
| Oral Comprehension | 3.0 | |
| Oral Expression | 3.0 | |
| Information Ordering | 3.0 | |
| Visualization | 3.0 | |
| Selective Attention | 3.0 | |
| Speech Recognition | 3.0 | |
| Speech Clarity | 3.0 | |
| Written Comprehension | 2.9 | |
| Inductive Reasoning | 2.9 | |
| Number Facility | 2.9 | |
| Mathematical Reasoning | 2.8 | |
| Perceptual Speed | 2.8 |
| Customer and Personal Service | 3.6 | |
| Production and Processing | 3.2 | |
| English Language | 3.0 | |
| Mathematics | 3.0 | |
| Sales and Marketing | 3.0 | |
| Administration and Management | 2.8 |
| Quality Control Analysis | 3.4 | |
| Judgment and Decision Making | 2.9 | |
| Social Perceptiveness | 2.8 | |
| Service Orientation | 2.8 | |
| Complex Problem Solving | 2.8 | |
| Operations Monitoring | 2.8 |
| Active Listening | 3.1 | |
| Speaking | 3.1 | |
| Critical Thinking | 3.0 | |
| Monitoring | 3.0 | |
| Reading Comprehension | 2.9 | |
| Mathematics | 2.8 |
Skills employers ask for in job postings for this occupation (Lightcast), with whether each is a common or specialized skill.
| Example | Category | |
|---|---|---|
| Business accounting software | Accounting software | |
| Gem identification databases | Data base user interface and query software | |
| GemCad | Computer aided design CAD software | |
| Inventory tracking software | Inventory management software | |
| Jewelry design software | Computer aided design CAD software | |
| Spectrophotometer analysis software | Analytical or scientific software | |
| Web browser software | Internet browser software |
How characteristic each condition is of the job, on O*NET's 1–5 context scale (higher = more present in day-to-day work). Each condition links to how it varies across all occupations.
What to study: Mechanic and Repair Technologies/Technicians , Visual and Performing Arts . Fields of study crosswalked to this occupation (NCES CIP–SOC), not a requirement.
Share of people in this occupation at each level of education.
| High School Diploma | 57.9% | |
| Bachelor's Degree | 19.0% | |
| Post-Secondary Certificate | 15.2% | |
| Less than a High School Diploma | 8.0% |
The interests and personal qualities O*NET associates with people who do this work.
| Realistic | 5.5 | |
| Conventional | 4.1 | |
| Investigative | 3.1 | |
| Artistic | 2.9 | |
| Enterprising | 2.1 |
| Dependability | 4.0 | |
| Attention to Detail | 3.0 | |
| Cautiousness | 2.5 | |
| Integrity | 2.3 |
| Physical Science | 2.3 | |
| Engineering | 2.0 | |
| Mathematics/Statistics | 2.0 | |
| Physical/Manual Labor | 2.0 | |
| Applied Arts and Design | 1.8 | |
| Accounting | 1.8 | |
| Mechanics/Electronics | 1.8 |
U.S. · annual wages (BLS OEWS)
| 10th percentile | $33,890 |
| 25th percentile | $38,030 |
| Median (50th) | $49,140 |
| 75th percentile | $63,210 |
| 90th percentile | $81,610 |
| People employed | 23,420 |
Wages and employment are reported by BLS for the broader occupation group this specialty belongs to (SOC 51-9071), not for the specialty alone.
Where these workers are employed, by number of jobs (national, BLS OEWS). Pay shown is the occupation's national median, not industry-specific.
| Industry | Workers | National median pay |
|---|---|---|
| Retail Trade · Sector | 12,050 | $50,340 |
| Manufacturing · Sector | 6,180 | $46,180 |
| Jewelry and Silverware Manufacturing · National industry | 6,000 | $46,130 |
| Wholesale Trade · Sector | 2,780 | $58,120 |
| Other Services (except Public Administration) · Sector | 1,030 | $48,250 |
| Management of Companies and Enterprises · Sector | 420 | $70,410 |
| Professional, Scientific, and Technical Services · Sector | 410 | $62,640 |
| Finance and Insurance · Sector | 190 | $50,870 |
| Temporary Help Services · National industry | 40 | $36,520 |
| Health Care and Social Assistance · Sector | — | $55,370 |
Industries where this occupation is far more common than in the economy as a whole. The location quotient is how many times more concentrated it is here (a value of 5 means five times its economy-wide share).
| Industry | Concentration | Workers |
|---|---|---|
| Jewelry and Silverware Manufacturing · National industry | 1982.99× | 6,000 |
| Retail Trade · Sector | 5.09× | 12,050 |
| Manufacturing · Sector | 3.19× | 6,180 |
| Wholesale Trade · Sector | 3.03× | 2,780 |
| Other Services (except Public Administration) · Sector | 1.53× | 1,030 |
| Management of Companies and Enterprises · Sector | 0.98× | 420 |
| Professional, Scientific, and Technical Services · Sector | 0.25× | 410 |
| Finance and Insurance · Sector | 0.2× | 190 |
Part of the Advanced Manufacturing career cluster.
Side-by-side comparisons place two occupations’ pay, preparation, skills, and AI exposure on the same page — same data, same scale, no forecast.
Options the data surfaces for Gem and Diamond Workers — not advice or a forecast. Each is a real cross-link you can follow into the evidence.
Capabilities this work builds that are used across many other occupations.
Occupations O*NET rates as related — the nearby moves on the map.
How people typically prepare for this work.
On the global GenAI exposure gradient this work sits around the 26th percentile of 427 international occupations.
Gem and Diamond Workers show 39th-percentile AI task overlap — and about 4,000 annual U.S. openings
Gem and Diamond Workers show 39th-percentile AI task overlap — and about 4,000 annual U.S. openings • Gem and Diamond Workers rank in the 39th percentile (Moderate band) for AI task overlap across U.S. occupations — a measure of how much of the work today's AI can attempt, not how much is automated. (Eloundou et al. (GPTs are GPTs) + Felten AIOE) • The occupation is projected to see about 4,000 U.S. job openings per year (2024–34), counting growth and replacement — a labor-demand projection made independently of AI. (BLS Employment Projections 2024–34) • BLS projects employment to be declining (-5.5%) from 2024 to 2034. (BLS Employment Projections 2024–34) • Median annual pay is $49,140, across about 23,420 U.S. workers. (BLS OEWS (May 2024)) Source: Singulariki — "Gem and Diamond Workers". https://singulariki.com/roles/role-51-9071-06 Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.
AssetsShare imageMethodology & sourcesPress & newsroomThe newsroom
Every line is built only from figures this page already shows and cites. AI task overlap means what today's AI can attempt — not automation, job loss, or a forecast.
Every figure above traces to a named public dataset and the exact release below — not hand-written opinion. See the full methodology for what each measure does and does not mean.
Data compiled June 2, 2026. Figures are estimates, not advice.
Singulariki. "Gem and Diamond Workers." Singulariki: a source-backed encyclopedia of work. Built from O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026. https://singulariki.com/roles/role-51-9071-06
Singulariki. (2026). Gem and Diamond Workers. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-51-9071-06
@misc{singulariki-role-51-9071-06,
title = {Gem and Diamond Workers},
author = {{Singulariki}},
year = {2026},
note = {O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026},
url = {https://singulariki.com/roles/role-51-9071-06}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.