Dental Laboratory Technicians

Healthcare

AI exposure

  • Data source: BLSPublished: 2026-08

    Low· relative

    LowFour relative bandsVery high

    Group-level value

    Scale, basis and source

    Four relative bands (Low / Moderate / High / Very high)

    831 detailed occupations in the BLS Employment Projections table. Assigned per National Employment Matrix (NEM) code, so occupations sharing a NEM code carry the same band

    Source dataset (XLSX download)

  • Data source: AnthropicPublished: 2026-03

    0.000

    0.000Range of values carried here0.745
    Scale, basis and source

    Observed exposure index, 0–1 as published

    Mapped onto O*NET tasks

    Source dataset

  • Data source: ILOPublished: 2025

    0.18

    0.09Range of values carried here0.70

    Group-level value

    Scale, basis and source

    Generative AI exposure index, 0–1 as published

    ISCO-08 unit group — every occupation sharing the code gets this value

    Computed by this site, not published by the ILO: of the 1,012 occupations this site links to the ILO dataset, 90% score at or above this value.

    Source dataset

What kind of figure this source publishes

The BLS category is a relative rank, not an absolute level, and it is not a first-hand measurement: it groups an occupation's percentile ranks across several published studies into four bands. It is not an employment or wage forecast, not a probability of adoption, and it does not separate automation from augmentation.

Task-level exposure

Exposed tasks only

Values in this tab are predicted labels, not observations. Eloundou et al. (2023) published two rating regimes — human raters and GPT-4 — and the β shown here is derived from the GPT-4 rater basis alone; the same task can take a different value under the other regime. The unit and the meaning differ from the observed shares (%) in the other tabs, so do not place them on the same axis.

TaskβE1 + 0.5 × E2
Read prescriptions or specifications and examine models or impressions to determine the design of dental products to be constructed.

O*NET Task ID 7133

0.5
Fabricate, alter, or repair dental devices, such as dentures, crowns, bridges, inlays, or appliances for straightening teeth.

O*NET Task ID 7134

0.0
Test appliances for conformance to specifications and accuracy of occlusion, using articulators and micrometers.

O*NET Task ID 7135

0.0
Place tooth models on an apparatus that mimics bite and movement of patient's jaw to evaluate functionality of model.

O*NET Task ID 7136

0.0
Melt metals or mix plaster, porcelain, or acrylic pastes and pour materials into molds or over frameworks to form dental prostheses or apparatuses.

O*NET Task ID 7137

0.0
Prepare metal surfaces for bonding with porcelain to create artificial teeth, using small hand tools.

O*NET Task ID 7138

0.0
Remove excess metal or porcelain and polish surfaces of prostheses or frameworks, using polishing machines.

O*NET Task ID 7139

0.0
Create a model of patient's mouth by pouring plaster into a dental impression and allowing plaster to set.

O*NET Task ID 7140

0.0
Load newly constructed teeth into porcelain furnaces to bake the porcelain onto the metal framework.

O*NET Task ID 7141

0.0
Build and shape wax teeth, using small hand instruments and information from observations or dentists' specifications.

O*NET Task ID 7142

0.0
Apply porcelain paste or wax over prosthesis frameworks or setups, using brushes and spatulas.

O*NET Task ID 7143

0.0
Fill chipped or low spots in surfaces of devices, using acrylic resins.

O*NET Task ID 7144

0.0
Prepare wax bite blocks and impression trays for use.

O*NET Task ID 7145

0.0
Mold wax over denture setups to form the full contours of artificial gums.

O*NET Task ID 7146

0.0
Train or supervise other dental technicians or dental laboratory bench workers.

O*NET Task ID 7147

0.0
Rebuild or replace linings, wire sections, or missing teeth to repair dentures.

O*NET Task ID 7148

0.0
Shape and solder wire and metal frames or bands for dental products, using soldering irons and hand tools.

O*NET Task ID 7149

0.0

β = E1 + 0.5 × E2 · E1 = tasks where direct LLM access alone cuts time by at least 50%, E2 = tasks where software built on top of an LLM cuts time by at least 50%. Values take only 0 / 0.5 / 1.0.

Data sources & licenses — O*NET®, Eloundou et al. (2023): see full notices on the Credits page

Occupation information