Jewelers and precious stone and metal workers
SOC Code: 51-9071
Jewelers and precious stone and metal workers carries a 46% AI exposure score (High automation risk), with a median annual wage of $49,140 and -5.5% projected employment growth from 2024 to 2034 (BLS), affecting approximately 35,100 workers. Full task breakdown, skills, and employer data are below.
Proportion of tasks susceptible to AI automation (O*NET analysis)
AI Exposure vs Industry Growth
Total occupations tracked
832
Covering all SOC major groups
Data currency
2024
BLS Employment Projections
AI exposure avg
40%
Fleet-wide median across all roles
Composite score weighing O*NET task data completeness, BLS projection methodology, and cross-validation with employer risk grades.
Employment Projections
Occupation Insight
Jewelers and precious stone and metal workers (SOC 51-9071) carries an AI exposure score of 46%, placing it in the High automation-risk tier. This score is computed from O*NET Database 30.0 task-level analysis, where each task an occupation performs is evaluated against current generative AI, robotic process automation, and machine-learning capabilities. A score in the 40–70% range indicates meaningful automation pressure on specific task categories, but the role as a whole still requires human judgment for coordination, exception handling, or client interaction.
The economic context matters alongside the risk score. BLS counted approximately 35,100 workers in this occupation in 2024, and projects a -5.5% change through 2034 — a decline that often compounds with high AI exposure to create displacement headwinds. Median annual compensation stands at $49,140, reflecting both skill scarcity and the value employers place on the tasks that remain difficult to automate. Entry typically requires High school diploma or equivalent, plus None of related experience.
For career planners, this profile should be read alongside the task, skill, and knowledge breakdowns below and the list of employers whose workforce composition includes Jewelers and precious stone and metal workers. Adjacent occupations shown further down offer lateral moves that preserve industry knowledge while potentially reducing exposure. Pair the AI exposure score with the BLS employment projection and wage percentiles above for a complete career assessment.
Education & Entry Requirements
Top Tasks (O*NET)
- 1. Examine gems during processing to ensure accuracy of angles and positions of cuts or bores, using magnifying glasses, loupes, or shadowgraphs.
- 2. Assign polish, symmetry, and clarity grades to stones, according to established grading systems.
- 3. Clean and polish metal items and jewelry pieces, using jewelers' tools, polishing wheels, and chemical baths.
- 4. Smooth soldered joints and rough spots, using hand files and emery paper, and polish smoothed areas with polishing wheels or buffing wire.
- 5. Create jewelry from materials such as gold, silver, platinum, and precious or semiprecious stones.
- 6. 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.
- 7. Estimate wholesale and retail value of gems, following pricing guides, market fluctuations, and other relevant economic factors.
- 8. Immerse stones in prescribed chemical solutions to determine specific gravities and key properties of gemstones or substitutes.
- 9. Cut and file pieces of jewelry such as rings, brooches, bracelets, and lockets.
- 10. Examine assembled or finished products to ensure conformance to specifications, using magnifying glasses or precision measuring instruments.
Key Skills Required
- Quality Control Analysis
- Active Listening
- Speaking
- Critical Thinking
- Monitoring
- Reading Comprehension
- Judgment and Decision Making
- Mathematics
- Social Perceptiveness
- Service Orientation
Knowledge Areas
- Customer and Personal Service
- Production and Processing
- English Language
- Mathematics
- Sales and Marketing
- Administration and Management
- Education and Training
- Economics and Accounting
- Design
- Computers and Electronics
Frequently Asked Questions
Will AI replace Jewelers and precious stone and metal workers?
Jewelers and precious stone and metal workers has an AI exposure score of 46%, indicating a high level of automation risk. Some tasks in this role can be augmented or partially automated by AI, but core responsibilities require human judgment.
What is the job outlook for Jewelers and precious stone and metal workers?
According to BLS Employment Projections 2024-2034, Jewelers and precious stone and metal workers is projected to decline by 5.5% over the decade. Current employment stands at approximately 35,100 workers.
What skills are needed for Jewelers and precious stone and metal workers?
Key skills for Jewelers and precious stone and metal workers include Quality Control Analysis, Active Listening, Speaking, and others. Typical entry-level education is High school diploma or equivalent.
How much do Jewelers and precious stone and metal workers earn?
The median annual wage for Jewelers and precious stone and metal workers is $49,140, according to BLS Occupational Employment and Wage Statistics (May 2024). Actual earnings vary by location, experience, industry, and employer. The BLS publishes detailed wage percentiles by region in its Occupational Employment and Wage Statistics program.
What education is required for Jewelers and precious stone and metal workers?
The typical entry-level education for Jewelers and precious stone and metal workers is High school diploma or equivalent. Employers generally expect None of related work experience. On-the-job training typically involves Long-term on-the-job training. Requirements can vary by employer and specialization.
Which companies employ Jewelers and precious stone and metal workers?
Jewelers and precious stone and metal workers roles exist across many industries and employers. Workforce composition is estimated from BLS industry-occupation employment distributions matched to SEC-registered public companies.
AI Exposure Rating
High automation risk based on 10 analyzed tasks. A moderate share of tasks may be augmented by AI tools.
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Data sources: Bureau of Labor Statistics Employment Projections 2024–2034 and O*NET Database 30.0. Employment figures are rounded. Wage data from BLS Occupational Employment Statistics (OES).