Automation index
How much of a Volunteer coordinator’s job can AI already do?
A spreadsheet rota comes earlier. Getting them to come, stay, and do no harm, do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Volunteer coordinator
25%
AI can already do 25% of this job.
#218 / 623
View rankingVolunteer coordinator
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 |
|---|---|---|---|
Recruitment, rotas and the volunteer register.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 44% | +7 |
Train, support and the one who arrives lost.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 16% | +2.9 |
Insurance, agreements and the volunteering act.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 32% | +5.1 |
Recognise, keep them and the one who burns out.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
The clash between volunteer and staff.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 18% | +3.2 |
That they add, and do not replace paid work.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 14% | +2.2 |
| Total | 100% | 25% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- recruit volunteers
- make rotas
- train volunteers
- volunteering law
- retain volunteers
- volunteer insurance
- staff conflict
- volunteer register
Sources for this job· O*NET 11-9151.00· ESCO/ISCO 1344
IS WORK OVER?
Data architect
28%
#83 / 623
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