Will AI replace Furniture Finishers?
Estimated risk score: 7 out of 100
Very low replacement risk
Estimate from published task research, not reviewed by a person · how we estimate
Within about 19 points for 4 in 5 of the jobs we checked (0 to 26).
For the occupation as a whole, from ratings of its 22 O*NET tasks published in 2023 and calibrated to our hand scores. A specialty inside it can sit higher or lower.
O*NET-SOC 51-7021.00 · Production
Tasks rated in 2023 as ones AI could do or speed up
Tasks a GPT-4-class model could do, or do in half the time or less: 0 of its 22 rated tasks. In O*NET’s words.
None of its rated tasks.
Tasks rated in 2023 as not sped up by AI
Tasks such a model was rated as not speeding up or taking over: 20 of its 22 rated tasks; the first 6 are shown. In O*NET’s words.
- Brush, spray, or hand-rub finishing ingredients, such as paint, oil, stain, or wax, onto and into wood grain and apply lacquer or other sealers.
- Disassemble items to prepare them for finishing, using hand tools.
- Distress surfaces with woodworking tools or abrasives before staining to create an antique appearance, or rub surfaces to bring out highlights and shadings.
- Examine furniture to determine the extent of damage or deterioration, and to decide on the best method for repair or restoration.
- Fill and smooth cracks or depressions, remove marks and imperfections, and repair broken parts, using plastic or wood putty, glue, nails, or screws.
- Mix finish ingredients to obtain desired colors or shades.
What the job is
Shape, finish, and refinish damaged, worn, or used furniture or new high-grade furniture to specified color or finish.
Also called: Caner, Grainer, Antiquer, Recoater, Stain Wiper, Wood Coater, Wood Filler, Wood Grainer.
Source. This site includes information from the O*NET 30.1 Database by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA). Used under the CC BY 4.0 license. O*NET® is a trademark of USDOL/ETA. USDOL/ETA has not approved, endorsed, or tested these modifications. (O*NET, CC BY 4.0.) Task ratings: Eloundou, Manning, Mishkin and Rock (2023), “GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models”, data used under the MIT licence (licence texts). Our change: we averaged the ratings over this occupation’s tasks and calibrated them to our 0–100 scale. It is not a prediction about any one person and not career advice. Disagree? Write to hello@yourstopwashit.com. How we estimate