Automation index
How much of a Environmental engineer’s job can AI already do?
A discharge model comes earlier. A plant that complies and does not poison the river does not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Environmental engineer
25%
AI can already do 25% of this job.
#229 / 633
View rankingEnvironmental 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 |
|---|---|---|---|
Model emissions, discharges and noise.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 48% | +8.6 |
Impact studies, permits and specs.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 32% | +5.1 |
Field, sampling and treatment plants.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Authorities, public and objections.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 18% | +2.9 |
Rules, reports and monitoring.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 16% | +2.9 |
Not dressing an environmental figure.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 14% | +2.2 |
| Total | 100% | 25% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- Model emissions, discharges and noise
- Impact studies, permits and specs
- Field, sampling and treatment plants
- Authorities, public and objections
- Rules, reports and monitoring
- Not dressing an environmental figure
- ingeniero ambiental
- environmental engineer
Sources for this job· O*NET 17-2081.00· ESCO/ISCO 2143
IS WORK OVER?
Agile coach
24%
#257 / 633
View rankingAgile 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.
| Task | Share | AI | Points |
|---|---|---|---|
Boards, metrics and the cadence design.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
The real retro and the elephant in the room.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
Train, unblock and the manager who will not let go.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 32% | +5.1 |
Scale, dependencies and fake agile.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Conflict, power and not selling extra frameworks.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 18% | +3.2 |
That they stop faking it, and not inflating velocity.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 14% | +2.2 |
| Total | 100% | 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