IS WORK OVER?

Automation index

How much of a Community health worker’s job can AI already do?

A workshop and a leaflet come earlier. Reaching the person who never walks into the clinic do not.

This percentage does not predict how many people will lose their jobs.

Task comparison

Community health worker

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
Health map, workshops and the calendar.
Estimate

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

16%40%+6.4
Street, doorway and the neighbour who does not come.
Estimate

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

18%14%+2.5
Vaccines, screening and referring to the clinic.
Estimate

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

16%32%+5.1
Data, report and the health table.
Estimate

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

16%28%+4.5
The rumour, the distrust and not moralising.
Estimate

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

18%18%+3.2
That they come, and not inflating workshop numbers.
Estimate

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

16%14%+2.2
Total100%24%

Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low

Skills and activities

  • health workshops
  • health map
  • door-to-door
  • refer to clinic
  • screening
  • health table
  • community vaccination
  • health distrust

Sources for this job· O*NET 21-1094.00· ESCO/ISCO 3253

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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