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AI Automation Index
Will AI Replace Civil Engineers?
Task-level automation exposure for Civil Engineers: 16 O*NET tasks scored against their work activities, plus the simulator.
E-E-A-T Verified
Developed & audited by Gini Loh Automation Exposure
49%
weighted task index
16 of 16 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 49%
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 45%
Share in analysis, decisions, teaching, directing, advising, or caring for others.
Routine administration 6%
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 43/100
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
16 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) 44%
6 tasks
Medium exposure (≥ 35%) 28%
6 tasks
Low exposure (below 35%) 27%
4 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 05/2025 · AI/SME
Use drone technology for site surveying, inspection, and monitoring of infrastructure projects.
Constituent Tasks
#19610 · Core · 62% automatable
Direct engineering activities, ensuring compliance with environmental, safety, or other governmental regulations.
decision support — Compliance coordination needs human accountability and site action
Coordinate safety or regulatory compliance activities.
#20490 · Core · 18% automatable
Manage and direct the construction, operations, or maintenance activities at project site.
physical manipulation — Construction direction requires on-site presence and authority
Direct construction activities.
#148 · Core · 22% automatable
Inspect project sites to monitor progress and ensure conformance to design specifications and safety or sanitation standards.
visual inspection — Physical site verification against specs is human
Inspect facilities or sites to determine if they meet specifications or standards.
#147 · Core · 68% automatable
Compute load and grade requirements, water flow rates, or material stress factors to determine design specifications.
data analysis — Estimates from specs; human validates assumptions and risk
Estimate technical or resource requirements for development or production projects.
#20491 · Core · 45% automatable
Plan and design transportation or hydraulic systems or structures, using computer-assisted design or drawing tools.
text generation — Civil drawings need licensed engineering judgment
Create graphical representations of civil structures.
#20489 · Core · 68% automatable
Provide technical advice to industrial or managerial personnel regarding design, construction, program modifications, or structural repairs.
decision support — Proposes design changes; human validates feasibility
Recommend technical design or process changes to improve efficiency, quality, or performance.
#20492 · Core · 62% automatable
Analyze survey reports, maps, drawings, blueprints, aerial photography, or other topographical or geologic data.
data analysis — Evaluates technical data impact; engineer owns design
Evaluate technical data to determine effect on designs or plans.
#150 · Core · 18% automatable
Direct or participate in surveying to lay out installations or establish reference points, grades, or elevations to guide construction.
situated mobility — Field survey of land/water bodies
Survey land or bodies of water to measure or determine features.
#151 · Core · 68% automatable
Estimate quantities and cost of materials, equipment, or labor to determine project feasibility.
data analysis — Operational cost estimation from data
Estimate operational costs.
#152 · Core · 62% automatable
Prepare or present public reports on topics such as bid proposals, deeds, environmental impact statements, or property and right-of-way descriptions.
text generation — Assemble proposal documents from provided content
Prepare proposal documents. Explain project details to the general public.
#19607 · Core · 55% automatable
Design energy-efficient or environmentally sound civil structures.
decision support — AI proposes green features; engineer owns design decisions
Incorporate green features into the design of structures or facilities.
#153 · Supplemental · 25% automatable
Test soils or materials to determine the adequacy and strength of foundations, concrete, asphalt, or steel.
physical manipulation — Material characteristic testing needs physical instruments
Test characteristics of materials or structures.
#19611 · Supplemental · 57% automatable
Identify environmental risks and develop risk management strategies for civil engineering projects.
text generation — AI drafts technical methods; expert validates feasibility
Investigate the environmental impact of projects. Develop technical methods or processes.
#155 · Supplemental · 55% automatable
Conduct studies of traffic patterns or environmental conditions to identify engineering problems and assess potential project impact.
data analysis — Impact assessment aided; site-specific data human
Investigate the environmental impact of projects.
#19609 · Supplemental · 50% automatable
Develop or implement engineering solutions to clean up industrial accidents or other contaminated sites.
text generation — AI drafts technical methods; expert validates feasibility
Implement design or process improvements. Develop technical methods or processes.
#19608 · Supplemental · 38% automatable
Design or engineer systems to efficiently dispose of chemical, biological, or other toxic wastes.
decision support — AI aids emission system design; engineering validation human
Design systems to reduce harmful emissions.
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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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