Automation index
How much of a Driving theory instructor’s job can AI already do?
A DGT test comes earlier. Them understanding the rule without cramming the crib do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Driving theory instructor
27%
AI can already do 27% of this job.
#198 / 733
View rankingDriving theory instructor
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 |
|---|---|---|---|
Topic, the test and the typical error.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 48% | +8.6 |
Classroom, the one who skips and the one who copies.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
The rule, the why and not reciting the article.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Exam, the nerves and not jumping to a pass.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
The school, the rush and not selling the pass.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
That they understand the rule, and not the crib.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
- DGT tests
- driving theory
- typical errors
- traffic rules
- articles
- theory exam
- cribs
- theory classroom
Sources for this job· O*NET 25-3021.00· ESCO/ISCO 2320
IS WORK OVER?
Reliability engineer
27%
#175 / 733
View rankingReliability 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 |
|---|---|---|---|
Data, MTBF and the Pareto.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 48% | +8.6 |
Failure, the cause and not patching twice.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
Spare, the critical and not hiding it.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
RCM, the plan and the one that is not done.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Production, the rush and not running the tired one.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
That it does not drop at three, and not hiding the spare.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
- MTBF
- Pareto
- root causes
- critical spares
- RCM
- failures
- maintenance plans
- not patch twice
Sources for this job· O*NET 17-2112.00· ESCO/ISCO 2141