IS WORK OVER?

Automation index

How much of a Risk manager’s job can AI already do?

A risk map and a VaR come earlier. Stopping a product and convincing the committee do not.

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

Task comparison

Risk manager

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
Maps, models and risk reporting.
Estimate

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

22%52%+11.4
Policies, limits and stress tests.
Estimate

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

18%45%+8.1
Escalate an incident and talk to desks.
Estimate

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

16%18%+2.9
Committee, exceptions and negotiation.
Estimate

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

16%15%+2.4
Data quality and model assumptions.
Estimate

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

14%16%+2.2
Stop the risk and sign the opinion.
Estimate

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

14%14%+2
Total100%29%

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

Skills and activities

  • Maps, models and risk reporting
  • Policies, limits and stress tests
  • Escalate an incident and talk to desks
  • Committee, exceptions and negotiation
  • Data quality and model assumptions
  • Stop the risk and sign the opinion
  • risk manager
  • gestor de riesgos
  • riesgo operacional

Sources for this job· O*NET 13-2099.02· ESCO/ISCO 2413

Agile coach

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
Boards, metrics and the cadence design.
Estimate

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

16%40%+6.4
The real retro and the elephant in the room.
Estimate

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

18%14%+2.5
Train, unblock and the manager who will not let go.
Estimate

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

16%32%+5.1
Scale, dependencies and fake agile.
Estimate

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

16%28%+4.5
Conflict, power and not selling extra frameworks.
Estimate

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

18%18%+3.2
That they stop faking it, and not inflating velocity.
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

  • retros
  • agile cadence
  • unblock teams
  • flow metrics
  • fake agile
  • agile training
  • dependencies
  • velocity

Sources for this job· O*NET 13-1111.00· ESCO/ISCO 2421

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