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AI Automation Index
Will AI Replace Water/Wastewater Engineers?
Task-level automation exposure for Water/Wastewater Engineers: 28 O*NET tasks scored against their work activities, plus the simulator.
E-E-A-T Verified
Developed & audited by Gini Loh Automation Exposure
57%
weighted task index
28 of 28 tasks scored
Median Salary
$100,840 / year
BLS OEWS, May 2025 — this exact occupation
Employment Level
Very High
367,840 people hold this job — size, not growth
Projected 2025–35
+6.4%
employment change
22,700 openings a year · BLS line item
Pay by state
BLS OEWS publishes 53 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.
$61,060 – $122,500
Highest medians
California $122,500
Alaska $114,730
Washington $110,000
Massachusetts $106,730
Louisiana $105,380
Lowest medians
Puerto Rico $61,060
Guam $67,410
Georgia $84,240
Arkansas $85,020
West Virginia $86,930
State figures come from the 17-2051 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 57%
Importance-weighted mean of the scored tasks. This is the headline index.
Physical work 0%
Share of weighted tasks in hands-on or machine-operating work activities.
Judgment & influence 49%
Share in analysis, decisions, teaching, directing, advising, or caring for others.
Routine administration 3%
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 0/100
Low
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
28 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) 48%
14 tasks
Medium exposure (≥ 35%) 49%
13 tasks
Low exposure (below 35%) 3%
1 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 →Constituent Tasks
#16327 · Core · 54% automatable
Provide technical direction or supervision to junior engineers, engineering or computer-aided design (CAD) technicians, or other technical personnel.
decision support — Proposes design changes; human validates feasibility
Supervise engineering or other technical personnel. Provide technical guidance to other personnel. Recommend technical design or process changes to improve efficiency, quality, or performance.
#16325 · Core · 60% automatable
Review and critique proposals, plans, or designs related to water or wastewater treatment systems.
decision support — Design quality evaluation needs engineering judgment
Evaluate designs or specifications to ensure quality.
#16350 · Core · 50% automatable
Design domestic or industrial water or wastewater treatment plants, including advanced facilities with sequencing batch reactors (SBR), membranes, lift stations, headworks, surge overflow basins, ultraviolet disinfection systems, aerobic digesters, sludge lagoons, or control buildings.
decision support — AI drafts civil designs; licensed engineer verifies and stamps
Design civil structures or systems.
#21166 · Core · 66% automatable
Evaluate the operation and maintenance of water or wastewater systems to identify ways to improve their efficiency.
data analysis — AI analyzes operations to flag efficiency gains
Identify opportunities to improve operational efficiency. Evaluate characteristics of equipment or systems.
#16330 · Core · 53% automatable
Design or select equipment for use in wastewater processing to ensure compliance with government standards.
decision support — Tool selection needs context; human decides and procures
Select tools, equipment, or technologies for use in operations or projects. Design civil structures or systems.
#16349 · Core · 45% automatable
Design pumping systems, pumping stations, pipelines, force mains, or sewers for the collection of wastewater.
decision support — AI models process systems; engineer validates feasibility
Design industrial processing systems.
#16347 · Core · 45% automatable
Design water distribution systems for potable or non-potable water.
decision support — AI models process systems; engineer validates feasibility
Design industrial processing systems.
#16331 · Core · 55% automatable
Conduct water quality studies to identify and characterize water pollutant sources.
data analysis — Impact assessment aided; site-specific data human
Investigate the environmental impact of projects.
#16343 · Core · 68% automatable
Analyze and recommend chemical, biological, or other wastewater treatment methods to prepare water for industrial or domestic use.
decision support — Proposes design changes; human validates feasibility
Recommend technical design or process changes to improve efficiency, quality, or performance.
#16328 · Core · 60% automatable
Identify design alternatives for the development of new water resources.
text generation — AI drafts technical methods; expert validates feasibility
Develop technical methods or processes.
#16345 · Core · 50% automatable
Design water runoff collection networks, water supply channels, or water supply system networks.
decision support — AI drafts civil designs; licensed engineer verifies and stamps
Design civil structures or systems.
#16346 · Core · 50% automatable
Design water or wastewater lift stations, including water wells.
decision support — AI drafts civil designs; licensed engineer verifies and stamps
Design civil structures or systems.
#16339 · Core · 70% automatable
Conduct cost-benefit analyses for the construction of water supply systems, runoff collection networks, water and wastewater treatment plants, or wastewater collection systems.
data analysis — Cost-benefit analysis from given inputs; human reviews
Analyze costs and benefits of proposed designs or projects.
#16326 · Core · 70% automatable
Provide technical support on water resource or treatment issues to government agencies.
information retrieval — Green practice advice is largely informational
Advise others regarding green practices or environmental concerns.
#16337 · Core · 40% automatable
Conduct feasibility studies for the construction of facilities, such as water supply systems, runoff collection networks, water and wastewater treatment plants, or wastewater collection systems.
data analysis — Design analysis aided; simulation and build human
Research advanced engineering designs or applications.
#16341 · Core · 65% automatable
Analyze storm water or floodplain drainage systems to control erosion, stabilize river banks, repair channel streams, or design bridges.
data analysis — Analyzes survey/physical data; human checks quality
Analyze physical, survey, or geographic data.
#16335 · Core · 25% automatable
Oversee the construction of decentralized or on-site wastewater treatment systems, including reclaimed water facilities.
decision support — Environmental development direction needs field accountability
Direct environmental development activities.
#16329 · Core · 72% automatable
Develop plans for new water resources or water efficiency programs.
text generation — Detailed work plans drafted from specifications
Prepare detailed work plans.
#16333 · Core · 60% automatable
Perform hydrological analyses, using three-dimensional simulation software, to model the movement of water or forecast the dispersion of chemical pollutants in the water supply.
data analysis — AI builds computational models; engineer validates assumptions
Create models of engineering designs or methods.
#16334 · Core · 72% automatable
Perform hydraulic analyses of water supply systems or water distribution networks to model flow characteristics, test for pressure losses, or to identify opportunities to mitigate risks and improve operational efficiency.
data analysis — Evaluates operations from data; human owns conclusions
Analyze operational data to evaluate operations, processes or products.
#16324 · Core · 75% automatable
Write technical reports or publications related to water resources development or water use efficiency.
text generation — Operational reports drafted from data
Prepare technical or operational reports.
#16344 · Core · 50% automatable
Design water storage tanks or other water storage facilities.
decision support — AI assists structural design; engineer accountable for safety
Design structures or facilities.
#16342 · Core · 70% automatable
Analyze and recommend sludge treatment or disposal methods.
information retrieval — Green practice advice is largely informational
Advise others regarding green practices or environmental concerns.
#16348 · Core · 50% automatable
Design sludge treatment plants.
decision support — AI drafts civil designs; licensed engineer verifies and stamps
Design civil structures or systems.
#16336 · Core · 40% automatable
Gather and analyze water use data to forecast water demand.
data analysis — Design analysis aided; simulation and build human
Research advanced engineering designs or applications.
#16338 · Core · 55% automatable
Conduct environmental impact studies related to water and wastewater collection, treatment, or distribution.
data analysis — Impact assessment aided; site-specific data human
Investigate the environmental impact of projects.
#16340 · Core · 72% automatable
Analyze the efficiency of water delivery structures, such as dams, tainter gates, canals, pipes, penstocks, or cofferdams.
data analysis — Evaluates operations from data; human owns conclusions
Analyze operational data to evaluate operations, processes or products.
#16332 · Supplemental · 60% automatable
Perform mathematical modeling of underground or surface water resources, such as floodplains, ocean coastlines, streams, rivers, or wetlands.
data analysis — AI builds computational models; engineer validates assumptions
Create models of engineering designs or methods.
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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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