Automation index
How much of a Paid media specialist’s job can AI already do?
A media plan comes earlier. The pixel firing without burning the brand do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Paid media specialist
28%
AI can already do 28% of this job.
#123 / 623
View rankingPaid media 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.
| Task | Share | AI | Points |
|---|---|---|---|
Plan, platforms and the pixel.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 52% | +9.4 |
Creatives, frequency and audience cuts.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
The client, going live and the campaign that drifts.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Reports, attribution and the last-click fight.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Brand safety and inventory you cannot touch.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
That the pixel fires, and not burning extra CPM.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 12% | +1.9 |
| Total | 100% | 28% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- media plan
- pixel
- frequency
- brand safety
- attribution
- creatives
- audiences
- digital inventory
Sources for this job· O*NET 13-1161.00· ESCO/ISCO 2431
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