IS WORK OVER?

Automation index

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

A tensile curve comes earlier. Picking the alloy so it does not fail in service do not.

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

Task comparison

Materials 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
Tests, metallography and the spec.
Estimate

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

18%48%+8.6
Shop, heat treatment and the part that fails spec.
Estimate

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

16%22%+3.5
Material choice, corrosion and fatigue.
Estimate

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

16%36%+5.8
Supplier, certificates and the doubtful batch.
Estimate

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

16%28%+4.5
The field failure and the root cause.
Estimate

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

18%14%+2.5
That it does not fail, and not swapping the material blind.
Estimate

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

16%12%+1.9
Total100%27%

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

Skills and activities

  • materials tests
  • metallography
  • choose alloys
  • corrosion
  • fatigue
  • heat treatment
  • failure analysis
  • batch certificates

Sources for this job· O*NET 17-2131.00· ESCO/ISCO 2149

QA automation 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
Test, the selector and the flake.
Estimate

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

18%48%+8.6
Pipeline, the green and the one that lies.
Estimate

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

16%40%+6.4
Bug, the repro and not closing it blind.
Estimate

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

16%22%+3.5
Data, the environment and not sharing prod.
Estimate

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

16%28%+4.5
The developer, the rush and not skipping the one that fails.
Estimate

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

18%14%+2.5
Catch the bug, and not painting a lying green.
Estimate

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

16%12%+1.9
Total100%27%

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

Skills and activities

  • automated tests
  • selectors
  • flakes
  • QA pipelines
  • repro
  • environments
  • lying green
  • debug tests

Sources for this job· O*NET 15-1253.00· ESCO/ISCO 2519

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