IS WORK OVER?

Automation index

How much of a Billing clerk’s job can AI already do?

An ERP comes earlier. Issuing the right invoice without blocking the client do not.

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

Task comparison

Billing clerk

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
Orders, delivery notes and the invoice.
Estimate

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

18%48%+8.6
VAT, withholdings and the one that does not square.
Estimate

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

16%40%+6.4
Credit notes, the credit and the client who argues.
Estimate

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

16%22%+3.5
Close, the immediate supply and the deadline.
Estimate

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

16%28%+4.5
Sales, the extra and not over-billing.
Estimate

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

18%14%+2.5
The right invoice, and not blocking the client.
Estimate

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

16%12%+1.9
Total100%27%

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

Skills and activities

  • delivery notes
  • invoices
  • VAT
  • credit notes
  • immediate supply
  • billing close
  • withholdings
  • orders

Sources for this job· O*NET 43-3021.00· ESCO/ISCO 4311

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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