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AI Automation Index
Will AI Replace Water and Wastewater Treatment Plant and System Operators?
Task-level automation exposure for Water and Wastewater Treatment Plant and System Operators: 8 O*NET tasks scored against their work activities, plus the simulator.
E-E-A-T Verified
Developed & audited by Gini Loh Automation Exposure
25%
weighted task index
8 of 8 tasks scored
Median Salary
$60,020 / year
BLS OEWS, May 2025 — this exact occupation
Employment Level
High
128,490 people hold this job — size, not growth
Projected 2025–35
-5.7%
employment change
10,000 openings a year · BLS line item
Pay by state
BLS OEWS publishes 52 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.
$29,220 – $81,770
Highest medians
California $81,770
Nevada $81,440
Washington $80,800
Connecticut $78,820
New Jersey $78,760
Lowest medians
Puerto Rico $29,220
Arkansas $44,320
Kentucky $45,430
Oklahoma $45,890
Louisiana $46,210
State figures come from the 51-8031 row in the May 2025 state panel. States where the estimate was suppressed or too small to publish are absent.
What the score is made of
Each task is mapped to its work activities, scored for AI automation potential, and weighted by how important those activities are to the job. These are the components.
Automation potential 25%
Importance-weighted mean of the scored tasks. This is the headline index.
Physical work 61%
Share of weighted tasks in hands-on or machine-operating work activities.
Judgment & influence 12%
Share in analysis, decisions, teaching, directing, advising, or caring for others.
Routine administration 14%
Share in documenting, recording, and administrative activities.
Rewritten by O*NET 0%
Share of weighted tasks O*NET rewrote in a recent update. Reported, not folded into the score.
Consequence of error 33/100
Moderate
O*NET's own rating of how serious an uncorrectable mistake would be here — respondents, not us. Deliberately not in the index: the score measures what AI can do with the task content, and multiplying it by stakes would be our judgment dressed as data.
Constituent Task Mix
8 tasks for this occupation, weighted by work-activity importance. Shares below are of total task weight, not task count.
High exposure (≥ 60% of the task is automatable) 14%
1 tasks
Medium exposure (≥ 35%) 0%
0 tasks
Low exposure (below 35%) 86%
7 tasks
How would you survive?
Move your week away from the high-exposure tasks and toward the ones that need judgment. The simulator recalculates the index as you shift the mix.
Simulate Upskilling →Emerging & rewritten tasks
Tasks O*NET added or rewrote for this occupation in its recent updates (05/2025 – 08/2026), with who proposed them. Additions are not in the scored task inventory — they are new work O*NET is still measuring, so they appear here and nowhere in the index. A Revision replaces a task that is scored, which is why only those move the "Rewritten by O*NET" share.
- New 08/2025 · Occupational Expert
Complete wastewater discharge monitoring reports and maintenance logs.
- New 08/2025 · Occupational Expert
Maintain and repair portable safety equipment and permanent safety infrastructure to ensure operational readiness and compliance with safety protocols.
Constituent Tasks
#928 · Core · 15% automatable
Collect and test water and sewage samples, using test equipment and color analysis standards.
physical manipulation — Chemical/physical testing requires lab manipulation
Test chemical or physical characteristics of materials or products. Collect samples of materials or products for testing.
#926 · Core · 15% automatable
Operate and adjust controls on equipment to purify and clarify water, process or dispose of sewage, and generate power.
physical manipulation — Chemical and water systems controlled physically on site
Operate chemical processing or water treatment systems or equipment.
#929 · Core · 82% automatable
Record operational data, personnel attendance, or meter and gauge readings on specified forms.
data analysis — Record production data into structured logs
Record operational or production data.
#925 · Core · 15% automatable
Add chemicals, such as ammonia, chlorine, or lime, to disinfect and deodorize water and other liquids.
physical manipulation — Chemical and water systems controlled physically on site
Operate chemical processing or water treatment systems or equipment.
#927 · Core · 18% automatable
Inspect equipment or monitor operating conditions, meters, and gauges to determine load requirements and detect malfunctions.
visual inspection — Physical inspection of production machinery in situ
Inspect production equipment.
#932 · Core · 30% automatable
Direct and coordinate plant workers engaged in routine operations and maintenance activities.
interpersonal — Directing production operations is human supervisory authority
Direct operational or production activities.
#18585 · Core · 7% automatable
Clean and maintain tanks, filter beds, and other work areas, using hand tools and power tools.
physical manipulation — Physical production equipment maintenance
Clean work areas. Clean production equipment. Maintain production or processing equipment.
#930 · Core · 10% automatable
Maintain, repair, and lubricate equipment, using hand tools and power tools.
physical manipulation — Hands-on repair of production machinery
Repair production equipment or tools. Maintain production or processing equipment. Lubricate production equipment.
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How this was scored
- 1. Tasks. O*NET task statements for this occupation, from a release whose newest record is dated 08/2026.
- 2. Work activities. Each task maps to 1–5 Detailed Work Activities; each activity belongs to one of 41 Generalized Work Activities that O*NET rates for importance (1–5) in this occupation.
- 3. Automation potential. Every work activity carries one score for how far current AI can perform it end-to-end. Tasks inherit the mean of their activities.
- 4. Weighting. Task weight = 0.35 + 0.65 × (importance − 1)/4, scaled by how often the task is performed and by 0.7 for Supplemental tasks. Importance is the task's own O*NET rating where it exists (18,369 of 18,838 tasks); the rest inherit their work activities' importance. The index is the weighted mean.
Check: across the 910 occupations where O*NET also rates how far machine speed sets the pace, this index moves opposite to it (Spearman ρ = -0.49). The more a job is paced by equipment, the less of its task content AI can address — the relationship you would expect if the scoring is working.
Sources · O*NET 31.0 (task records to 08/2026) · BLS OEWS May 2025 · BLS projections 2025-2035 · rubric v2.1 · tasks for O*NET, not a forecast
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