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.
#174 / 703
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?
Instructional designer
27%
#158 / 703
View rankingInstructional designer
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 |
|---|---|---|---|
Aim, the storyboard and the module.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 48% | +8.6 |
Pilot, the learner and what is not understood.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
Activity, the feedback and not putting a silly test.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
LMS, the figure and not inflating completion.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
The client, the deadline and not cutting the practice.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
That they learn, and not leaving the empty video.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
- course storyboard
- modules
- learner pilot
- activities
- LMS
- completion
- feedback
- not a silly test
Sources for this job· O*NET 25-9031.00· ESCO/ISCO 2351