Automation index
How much of a Fundraiser’s job can AI already do?
A letter and a CRM come earlier. Asking for the money in person and getting it again do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Fundraiser
26%
AI can already do 26% of this job.
#194 / 623
View rankingFundraiser
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 |
|---|---|---|---|
Campaigns, CRM and the donor letter.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 48% | +7.7 |
The meeting, the no, and asking again.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
Events, legacies and the member base.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 36% | +5.8 |
Transparency, the annual report and what you can say.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
The major donor, the board and the conflict of interest.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 18% | +3.2 |
That they give again, and not spending more than comes in.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 12% | +1.9 |
| Total | 100% | 26% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- raise funds
- donor campaigns
- member CRM
- ask for legacies
- run events
- transparency report
- major donors
- keep members
Sources for this job· O*NET 13-1131.00· ESCO/ISCO 2432
IS WORK OVER?
Prompt engineer
34%
#21 / 623
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