IS WORK OVER?

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

Fundraiser

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.

TaskShareAIPoints
Campaigns, CRM and the donor letter.
Estimate

No public source provides a precise figure. This is our estimate.

16%48%+7.7
The meeting, the no, and asking again.
Estimate

No public source provides a precise figure. This is our estimate.

18%14%+2.5
Events, legacies and the member base.
Estimate

No public source provides a precise figure. This is our estimate.

16%36%+5.8
Transparency, the annual report and what you can say.
Estimate

No public source provides a precise figure. This is our estimate.

16%28%+4.5
The major donor, the board and the conflict of interest.
Estimate

No 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.
Estimate

No public source provides a precise figure. This is our estimate.

16%12%+1.9
Total100%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

Data 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.

TaskShareAIPoints
Models, lineage and the catalogue.
Estimate

No public source provides a precise figure. This is our estimate.

18%52%+9.4
Pipelines, quality and the data contract.
Estimate

No public source provides a precise figure. This is our estimate.

16%40%+6.4
The analyst who finds nothing and the mess.
Estimate

No public source provides a precise figure. This is our estimate.

16%22%+3.5
Privacy, retention and the field you cannot keep.
Estimate

No public source provides a precise figure. This is our estimate.

16%28%+4.5
The business, shadow IT and not building another lake.
Estimate

No public source provides a precise figure. This is our estimate.

18%14%+2.5
That it gets used, and not letting raw data rot.
Estimate

No public source provides a precise figure. This is our estimate.

16%12%+1.9
Total100%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

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