Automation index
How much of a Cultural manager’s job can AI already do?
A programme and a budget come earlier. Filling the room and paying the people who make it do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Cultural manager
26%
AI can already do 26% of this job.
#202 / 623
View rankingCultural manager
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 |
|---|---|---|---|
Programme, fees and the venue calendar.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 44% | +7 |
Grants, paperwork and sponsorship.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 36% | +5.8 |
Artists, crew and the day the sound dies.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 16% | +2.9 |
Audience, comms and what does not fill.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
The councillor, the clash and soft censorship.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 18% | +3.2 |
Pay on time, and not leaving culture in the spreadsheet.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 14% | +2.2 |
| Total | 100% | 26% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- programme culture
- artist fees
- justify grants
- fill the room
- sponsorship
- deal with artists
- cultural comms
- venue budget
Sources for this job· O*NET 27-1029.00· ESCO/ISCO 2431
IS WORK OVER?
Data engineer
31%
#36 / 623
View rankingData 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 pipelines, models and orchestration.EstimateNo public source provides a precise figure. This is our estimate. | 24% | 50% | +12 |
Write SQL, Spark and data tests.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 45% | +8.1 |
Incidents, quality and lineage in production.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Talk to analysts and negotiate data contracts.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 18% | +2.9 |
Cloud cost, permissions and PII.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 15% | +2.1 |
Decide architecture and technical debt.EstimateNo public source provides a precise figure. This is our estimate. | 12% | 20% | +2.4 |
| Total | 100% | 31% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- Design pipelines, models and orchestration
- Write SQL, Spark and data tests
- Cloud cost, permissions and PII
- Decide architecture and technical debt
- ingeniero de datos
- data engineer
- etl
Sources for this job· O*NET 15-1243.00· ESCO/ISCO 2511