IS WORK OVER?

Automation index

How much of a Tax inspector’s job can AI already do?

A data match comes earlier. Sitting across from the taxpayer and signing the adjustment do not.

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

Task comparison

Tax inspector

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
Data matching, returns and sampling.
Estimate

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

18%52%+9.4
Requests, minutes and the proposal.
Estimate

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

16%40%+6.4
The visit, the second till and what is not in the sheet.
Estimate

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

18%14%+2.5
Objections, appeals and the tax tribunal.
Estimate

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

16%28%+4.5
The team, deadlines and the file that slips.
Estimate

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

16%22%+3.5
A fair adjustment and signing the minute.
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

  • match tax data
  • raise assessments
  • request papers
  • visit taxpayers
  • adjust tax
  • objections
  • tax tribunal
  • tax inspection

Sources for this job· O*NET 13-2081.00· ESCO/ISCO 3352

Logistics analyst

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
Costs, OTIF and the dashboard.
Estimate

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

18%52%+9.4
Simulate network, warehouses and the what-if.
Estimate

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

16%40%+6.4
Ops, dirty data and going down to the dock.
Estimate

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

16%22%+3.5
Report, the board and the cut that hurts.
Estimate

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

16%28%+4.5
The haulier, the contract and not breaking the service.
Estimate

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

18%14%+2.5
A real saving, and not dressing OTIF.
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

  • logistics costs
  • OTIF
  • simulate network
  • what-if
  • dirty data
  • haulage contracts
  • dashboards
  • network cuts

Sources for this job· O*NET 13-1081.00· ESCO/ISCO 2421

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