Automation index
How much of a Semiconductor technician’s job can AI already do?
A wafer recipe comes earlier. The batch coming out without eating the cleanroom do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Semiconductor technician
22%
AI can already do 22% of this job.
#394 / 633
View rankingSemiconductor technician
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 |
|---|---|---|---|
Recipe, tool and the batch.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
Room, the suit and the one that contaminates.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
Metrology, the defect and stopping.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Shift, the yield and not hiding it.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
The engineer, the change and not touching blind.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 18% | +3.2 |
The batch comes out, and the room intact.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 12% | +1.9 |
| Total | 100% | 22% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- wafers
- cleanroom
- yield
- metrology
- process recipes
- contamination
- chip batches
- suits
Sources for this job· O*NET 51-9141.00· ESCO/ISCO 3114
IS WORK OVER?
Prompt engineer
34%
#21 / 633
View rankingPrompt 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 |
|---|---|---|---|
Design prompts, tools and chains.EstimateNo public source provides a precise figure. This is our estimate. | 24% | 58% | +13.9 |
Evals, datasets and regressions.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 52% | +9.4 |
Integrate with product and safety limits.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Talk to the business about a good output.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 18% | +2.9 |
Watch hallucinations, bias and cost.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 20% | +2.8 |
Decide what the model gets, and what it does not.EstimateNo public source provides a precise figure. This is our estimate. | 12% | 16% | +1.9 |
| Total | 100% | 34% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- Design prompts, tools and chains
- Evals, datasets and regressions
- Integrate with product and safety limits
- Talk to the business about a good output
- Watch hallucinations, bias and cost
- prompt engineer
- ingeniero de prompts
- llm engineer
Sources for this job· O*NET 15-1252.00· ESCO/ISCO 2512