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
IS WORK OVER?
Risk manager
29%
AI can already do 29% of this job.
#60 / 733
View rankingRisk 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.
| Task | Share | AI | Points |
|---|---|---|---|
Maps, models and risk reporting.EstimateNo public source provides a precise figure. This is our estimate. | 22% | 52% | +11.4 |
Policies, limits and stress tests.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 45% | +8.1 |
Escalate an incident and talk to desks.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 18% | +2.9 |
Committee, exceptions and negotiation.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 15% | +2.4 |
Data quality and model assumptions.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 16% | +2.2 |
Stop the risk and sign the opinion.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 14% | +2 |
| Total | 100% | 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
IS WORK OVER?
Reliability engineer
27%
#175 / 733
View rankingReliability engineer
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.
| Task | Share | AI | Points |
|---|---|---|---|
Data, MTBF and the Pareto.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 48% | +8.6 |
Failure, the cause and not patching twice.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
Spare, the critical and not hiding it.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
RCM, the plan and the one that is not done.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Production, the rush and not running the tired one.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
That it does not drop at three, and not hiding the spare.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 12% | +1.9 |
| Total | 100% | 27% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- MTBF
- Pareto
- root causes
- critical spares
- RCM
- failures
- maintenance plans
- not patch twice
Sources for this job· O*NET 17-2112.00· ESCO/ISCO 2141