Automation index
How much of a Collections officer’s job can AI already do?
An ageing comes earlier. Collecting without breaking the client or letting the invoice die do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Collections officer
27%
AI can already do 27% of this job.
#155 / 623
View rankingCollections officer
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 |
|---|---|---|---|
Ageing, buckets and the call.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 48% | +8.6 |
Deal, the promissory note and the one who does not answer.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
Legal, the formal notice and the one who hides.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Sales, credit and not selling to a debtor.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
The default, the insolvency and not dressing the balance.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
Collect, and not breaking the client.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
- ageing
- collection calls
- promissory notes
- formal notice
- trade credit
- defaults
- debtors
- buckets
Sources for this job· O*NET 43-3011.00· ESCO/ISCO 4214
IS WORK OVER?
Prompt engineer
34%
#21 / 623
View rankingPrompt 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 |
|---|---|---|---|
Design prompts, tools and chains.EstimateNo public source provides a precise figure. This is our estimate. | 24% | 58% | +13.9 |
Evals, datasets and regressions.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 52% | +9.4 |
Integrate with product and safety limits.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Talk to the business about a good output.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 18% | +2.9 |
Watch hallucinations, bias and cost.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 20% | +2.8 |
Decide what the model gets, and what it does not.EstimateNo public source provides a precise figure. This is our estimate. | 12% | 16% | +1.9 |
| Total | 100% | 34% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- Design prompts, tools and chains
- Evals, datasets and regressions
- Integrate with product and safety limits
- Talk to the business about a good output
- Watch hallucinations, bias and cost
- prompt engineer
- ingeniero de prompts
- llm engineer
Sources for this job· O*NET 15-1252.00· ESCO/ISCO 2512