# Dental Laboratory Technicians

> Construct and repair full or partial dentures or dental appliances.

- **SOC code:** 51-9081.00
- **Canonical URL:** https://singulariki.com/roles/role-51-9081-00
- **Also known as:** Dental Ceramist, Dental Laboratory Technician (Dental Lab Tech), Dental Technician (Dental Tech), Denture Technician (Denture Tech), Ceramist, Crown and Bridge Dental Laboratory Technician (Crown and Bridge Dental Lab Tech), Metal Finisher, Orthodontic Laboratory Technician (Ortho Lab Tech)
- **Frame:** "AI exposure" means task overlap (how codifiable the work is), not jobs lost or a forecast. Every figure below is traced to a named public dataset.

## What this work is

**Core tasks** (O*NET):
- Read prescriptions or specifications and examine models or impressions to determine the design of dental products to be constructed.
- Test appliances for conformance to specifications and accuracy of occlusion, using articulators and micrometers.
- Fabricate, alter, or repair dental devices, such as dentures, crowns, bridges, inlays, or appliances for straightening teeth.
- Prepare metal surfaces for bonding with porcelain to create artificial teeth, using small hand tools.
- Rebuild or replace linings, wire sections, or missing teeth to repair dentures.
- Place tooth models on an apparatus that mimics bite and movement of patient's jaw to evaluate functionality of model.
- Apply porcelain paste or wax over prosthesis frameworks or setups, using brushes and spatulas.
- Remove excess metal or porcelain and polish surfaces of prostheses or frameworks, using polishing machines.
- Build and shape wax teeth, using small hand instruments and information from observations or dentists' specifications.
- Load newly constructed teeth into porcelain furnaces to bake the porcelain onto the metal framework.
- Mold wax over denture setups to form the full contours of artificial gums.
- Train or supervise other dental technicians or dental laboratory bench workers.

**Emerging tasks** (O*NET):
- Meet with dentists or patients to discuss dental appliances.
- Order parts or materials needed to make dental appliances.
- Scan dental models to create digital files.
- Stain porcelain on dental appliances to match the color of patients' teeth.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Finger Dexterity _(ability)_
- Near Vision _(ability)_
- Arm-Hand Steadiness _(ability)_
- Control Precision _(ability)_
- Administration and Management _(knowledge)_
- Design _(knowledge)_
- English Language _(knowledge)_
- Visualization _(ability)_
- Medicine and Dentistry _(knowledge)_
- Production and Processing _(knowledge)_
- Education and Training _(knowledge)_
- Reading Comprehension _(essential_skill)_

**Skills in demand:**
- Finger Dexterity _(Common Skill)_
- English Language _(Common Skill)_
- Visualization _(Specialized Skill)_
- Reading Comprehension _(Common Skill)_
- Information Ordering _(Specialized Skill)_
- Deductive Reasoning _(Common Skill)_
- Time Management _(Common Skill)_
- Critical Thinking _(Common Skill)_
- Speech Recognition _(Specialized Skill)_
- Microsoft Word _(Common Skill)_
- Microsoft Windows _(Common Skill)_
- Microsoft PowerPoint _(Common Skill)_

**Tools & technology:**
- Intuit QuickBooks _(hot technology)_
- Microsoft Excel _(hot technology)_
- Microsoft Office software _(hot technology)_
- Microsoft Outlook _(hot technology)_
- Microsoft PowerPoint _(hot technology)_
- Microsoft Windows _(hot technology)_
- Microsoft Word _(hot technology)_
- Bookkeeping software
- Computer aided design and drafting CADD software
- Computer imaging software
- Database management software
- Dental product design software

## AI exposure & outlook

- **AI task-overlap index:** 20th percentile (Low) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 48th percentile (Moderate) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 12th percentile (Low) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 7th percentile (Low) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 94th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** no — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** -4.7% growth (Declining); 3.9k annual openings; 35.2k → 33.6k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $48,310; 33,920 employed.

## Sources

- **O*NET** (30.3) — U.S. Department of Labor / National Center for O*NET Development. https://www.onetcenter.org/database.html
- **BLS Occupational Employment and Wage Statistics (OEWS)** (May 2024) — U.S. Bureau of Labor Statistics. https://www.bls.gov/oes/
- **BLS Employment Projections** (2024–2034) — U.S. Bureau of Labor Statistics. https://www.bls.gov/emp/
- **Microsoft “Working with AI”** (working-with-ai) — Microsoft Research. https://www.microsoft.com/en-us/research/
- **“GPTs are GPTs” (Eloundou et al.)** (arXiv 2303.10130) — OpenAI / academic. https://arxiv.org/abs/2303.10130
- **AI Occupational Exposure (AIOE)** (Felten, Raj & Seamans) — academic. https://github.com/AIOE-Data/AIOE
- **Frey & Osborne (2013)** (frey-osborne-automation) — academic. https://www.oxfordmartin.ox.ac.uk/publications/the-future-of-employment/
- **Dingel & Neiman (2020)** (dingel-neiman-workathome) — academic. https://github.com/jdingel/DingelNeiman-workathome

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_Generated from Singulariki's joined dataset; data snapshot 2026-06-02T21:00:32.945303+00:00. https://singulariki.com/roles/role-51-9081-00_