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?
Neurologist
24%
#274 / 623
View rankingNeurologist
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 |
|---|---|---|---|
Read MRIs, EEGs and a first differential.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 48% | +8.6 |
Examination, cranial nerves and gait.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
Long clinic, family and bad news.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 18% | +2.9 |
Reports, prescriptions and consults.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
On-call, stroke and ward rounds.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Meeting, team and owning the diagnosis.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 12% | +1.9 |
| Total | 100% | 24% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- Read MRIs, EEGs and a first differential
- Examination, cranial nerves and gait
- Long clinic, family and bad news
- Reports, prescriptions and consults
- On-call, stroke and ward rounds
- Meeting, team and owning the diagnosis
- neurologo
- neurologist
Sources for this job· O*NET 29-1217.00· ESCO/ISCO 2212