IS WORK OVER?

Automation index

How much of a Insurance claims adjuster’s job can AI already do?

A claim form and some photos come earlier. Valuing the damage on site and closing the claim do not.

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

Task comparison

Insurance claims adjuster

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
Read policy, claim form and cover.
Estimate

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

16%40%+6.4
On-site inspection, photos and facts.
Estimate

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

18%18%+3.2
Value damage, parts and write the report.
Estimate

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

18%48%+8.6
Negotiate with garage, injured party and insurer.
Estimate

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

16%28%+4.5
Fraud, recoveries and clash with another adjuster.
Estimate

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

16%22%+3.5
Close the file and own the valuation.
Estimate

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

16%14%+2.2
Total100%28%

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

Skills and activities

  • adjust claims
  • assess damage
  • inspect on site
  • value repairs
  • spot fraud
  • negotiate payouts
  • write survey reports
  • close claims

Sources for this job· O*NET 13-1031.00· ESCO/ISCO 3315

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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