IS WORK OVER?

Automation index

How much of a Tender specialist’s job can AI already do?

A specification comes earlier. Filing on time without leaving an empty envelope do not.

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

Task comparison

Tender specialist

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
Spec, requirements and the calendar.
Estimate

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

18%48%+8.6
Bid, scoring and the certificate that is late.
Estimate

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

16%40%+6.4
Board, clarifications and not contradicting.
Estimate

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

16%22%+3.5
Appeal, the tie and the one that falls.
Estimate

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

16%28%+4.5
Sales, the price and not dumping the margin.
Estimate

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

18%14%+2.5
On time, and the envelope complete.
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

  • specs
  • scoring
  • award boards
  • certificates
  • appeals
  • tender calendar
  • clarifications
  • envelopes

Sources for this job· O*NET 13-1199.00· ESCO/ISCO 2422

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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