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
IS WORK OVER?
Materials engineer
27%
AI can already do 27% of this job.
#162 / 623
View rankingMaterials 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.
| Task | Share | AI | Points |
|---|---|---|---|
Tests, metallography and the spec.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 48% | +8.6 |
Shop, heat treatment and the part that fails spec.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Material choice, corrosion and fatigue.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 36% | +5.8 |
Supplier, certificates and the doubtful batch.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
The field failure and the root cause.EstimateNo 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.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 12% | +1.9 |
| Total | 100% | 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
IS WORK OVER?
Logistics analyst
28%
#79 / 623
View rankingLogistics analyst
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.
| Task | Share | AI | Points |
|---|---|---|---|
Costs, OTIF and the dashboard.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 52% | +9.4 |
Simulate network, warehouses and the what-if.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
Ops, dirty data and going down to the dock.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Report, the board and the cut that hurts.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
The haulier, the contract and not breaking the service.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
A real saving, and not dressing OTIF.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 12% | +1.9 |
| Total | 100% | 28% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- logistics costs
- OTIF
- simulate network
- what-if
- dirty data
- haulage contracts
- dashboards
- network cuts
Sources for this job· O*NET 13-1081.00· ESCO/ISCO 2421