IS WORK OVER?

Automation index

How much of a Varnisher’s job can AI already do?

A colour card comes earlier. A finish that does not show the grain the wrong way does not.

This percentage does not predict how many people will lose their jobs.

Task comparison

Varnisher

Where the time goes

Task weights are our estimates based on O*NET frequency data, not time shares published by O*NET.

The time saving for each task is estimated separately.

TaskShareAIPoints
Colour cards, ranges and orders.
Estimate

No public source provides a precise figure. This is our estimate.

16%32%+5.1
Sand, stain, apply and dry.
Estimate

No public source provides a precise figure. This is our estimate.

22%10%+2.2
Booth, filters and dust.
Estimate

No public source provides a precise figure. This is our estimate.

16%14%+2.2
Cabinetmaker, deadlines and touch-up.
Estimate

No public source provides a precise figure. This is our estimate.

16%22%+3.5
Repairs in the home and on site.
Estimate

No public source provides a precise figure. This is our estimate.

16%18%+2.9
Not delivering a piece with orange peel.
Estimate

No public source provides a precise figure. This is our estimate.

14%14%+2
Total100%18%

Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low

Skills and activities

  • Colour cards, ranges and orders
  • Sand, stain, apply and dry
  • Booth, filters and dust
  • Cabinetmaker, deadlines and touch-up
  • Repairs in the home and on site
  • Not delivering a piece with orange peel
  • barnizador
  • lacador
  • varnisher

Sources for this job· O*NET 51-9123.00· ESCO/ISCO 7522

Data engineer

Where the time goes

Task weights are our estimates based on O*NET frequency data, not time shares published by O*NET.

The time saving for each task is estimated separately.

TaskShareAIPoints
Design pipelines, models and orchestration.
Estimate

No public source provides a precise figure. This is our estimate.

24%50%+12
Write SQL, Spark and data tests.
Estimate

No public source provides a precise figure. This is our estimate.

18%45%+8.1
Incidents, quality and lineage in production.
Estimate

No public source provides a precise figure. This is our estimate.

16%22%+3.5
Talk to analysts and negotiate data contracts.
Estimate

No public source provides a precise figure. This is our estimate.

16%18%+2.9
Cloud cost, permissions and PII.
Estimate

No public source provides a precise figure. This is our estimate.

14%15%+2.1
Decide architecture and technical debt.
Estimate

No public source provides a precise figure. This is our estimate.

12%20%+2.4
Total100%31%

Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low

Skills and activities

  • Design pipelines, models and orchestration
  • Write SQL, Spark and data tests
  • Cloud cost, permissions and PII
  • Decide architecture and technical debt
  • ingeniero de datos
  • data engineer
  • etl

Sources for this job· O*NET 15-1243.00· ESCO/ISCO 2511

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