Automation index
How much of a Vocational teacher’s job can AI already do?
A syllabus and a test come earlier. Running a workshop until the student welds straight does not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Vocational teacher
22%
AI can already do 22% of this job.
#368 / 633
View rankingVocational teacher
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 |
|---|---|---|---|
Plan modules, rubrics and exams.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
Workshop, practice and safety watch.EstimateNo public source provides a precise figure. This is our estimate. | 22% | 12% | +2.6 |
Tutor placements, firms and difficult students.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Assess, minutes and vocational cycles.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Staff meeting, coordination and workshop stock.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 18% | +2.9 |
Not leaving anyone without a trade or a diploma.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 14% | +2 |
| Total | 100% | 22% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- teach class
- mark students
- lesson plans
- teach
- Plan modules, rubrics and exams
- Workshop, practice and safety watch
- Assess, minutes and vocational cycles
- profesor de fp
- vocational teacher
Sources for this job· O*NET 25-2032.00· ESCO/ISCO 2320
IS WORK OVER?
Data architect
28%
#83 / 633
View rankingData architect
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 |
|---|---|---|---|
Models, lineage and the catalogue.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 52% | +9.4 |
Pipelines, quality and the data contract.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
The analyst who finds nothing and the mess.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Privacy, retention and the field you cannot keep.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
The business, shadow IT and not building another lake.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
That it gets used, and not letting raw data rot.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 12% | +1.9 |
| Total | 100% | 28% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- model data
- lineage
- data catalogue
- data contracts
- pipeline quality
- retention
- data lakes
- privacy
Sources for this job· O*NET 15-1243.00· ESCO/ISCO 2511