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?
Development cooperation officer
26%
#212 / 623
View rankingDevelopment cooperation officer
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 |
|---|---|---|---|
Agreements, alignment and the SDGs on the card.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 48% | +7.7 |
Follow-up, missions and reports to the agency.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 36% | +5.8 |
The local partner, the counterpart and the disagreement.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 16% | +2.9 |
Budget, currency and what stays in management.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
The context that shifts and reworking the approach.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 18% | +3.2 |
Not imposing, and accounting on both sides.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 14% | +2.2 |
| Total | 100% | 26% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- cooperation agreements
- align with SDGs
- agency reports
- southern partners
- monitoring missions
- hard-currency budget
- counterparts
- accountability
Sources for this job· O*NET 19-3094.00· ESCO/ISCO 2635