As of August 2026, Civil Engineer has an AI-exposure score of 46/100 (Moderate exposure) on the AI-Safe Careers index. This is an estimate of task exposure, not a prediction of job loss.
Score inputs for this role: AI-Safe Careers curated modeled estimate. This curated role has no matched O*NET SOC or empirical occupation signal. Treat it as a lower-confidence directional estimate. BLS labor-market figures are separate context, not score inputs.

AI Exposure Score for

Civil Engineer

46/100
Moderate exposure
LowModerateElevatedHighVery High

More exposed than 20% of the roles we track. Median pay ~US$89,940.

Pay & demand figures are US medians (in USD; curated approximation (not refreshed from BLS; 2022–32 framing)) - your local figures will differ. Your exposure score applies broadly.

Will AI replace Civil Engineer?

No exposure score can predict whether AI will replace this role. The 46/100 score means our current model estimates moderate task exposure from the sources listed on this page. It does not predict an employer decision, headcount, or an individual outcome. The task map below shows the work assessed and where human judgment remains important.

Early-career context (study ages 22-25)

This role is in our Moderate exposure band, not our highest-exposure bands. The study's 16% finding should not be applied directly to this role.

The November 2025 revision reports a 16% relative employment decline for workers ages 22-25 in the most AI-exposed U.S. occupations, after firm-level controls, relative to workers in less-exposed fields and more experienced workers in the same occupations.

Use the task map to identify durable work and the skills worth building early.

Stanford Digital Economy Lab, Canaries in the Coal Mine - November 2025 revision

This is group-level U.S. payroll evidence, not a personal forecast. The authors do not claim that AI alone caused the change, and this context does not alter the exposure score.

Data sources, not endorsements: O*NET and curated role data; empirical AI signals where matched; BLS employment, pay, and demand as separate context.Methodology Data sources
Role snapshot

What this role usually involves

O*NET 29.1 title match

Perform engineering duties in planning, designing, and overseeing construction and maintenance of building structures and facilities, such as roads, railroads, airports, bridges, harbors, channels, dams, irrigation projects, pipelines, power plants, and water and sewage systems.

Common titles
Civil EngineerDesign EngineerProject EngineerStructural EngineerCity EngineerCounty Engineer
O*NET job-zone preparation
Job Zone 4 · Considerable Preparation Needed Most of these occupations require a four-year bachelor's degree, but some do not. A considerable amount of work-related skill, knowledge, or experience is needed for these occupations.

Broad guidance for this preparation level; exact requirements vary by role and employer.

Skills and knowledge
Structural analysisCADProject mgmtDesignEngineering and TechnologyBuilding and Construction
Work context
Indoor controlled settingFrequent contact with othersDecision latitudeConsequence of errorRepeating tasks

Source: O*NET 29.1 title match - Civil Engineers, SOC 17-2051.00. Context describes the role; the AI-exposure score remains a separate task-exposure estimate.

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Civil Engineer tasks, by AI exposure

Automatable

No automatable tasks identified for this role - its individually-assessed tasks split 55% durable / 45% augmentable.

Augmentable
  • Produce drawings and calculations
  • Run simulations and analysis
7 more augmentable tasks locked in the report.
Durable
  • Design infrastructure solutions
  • Coordinate stakeholders and sign off
9 more durable tasks locked in the report.

We analyzed all 20 Civil Engineer tasks - 9 augmentable and 11 durable. The full task map - every task with exactly what to do about each - is in your Career Report.

Your report unlocks three concrete artifacts

Full task map

Every task scored with what to automate, augment, or protect.

Adjacent path comparison

Related roles with exposure deltas, salary, demand, and reachability. Lower-exposure options appear only when the data supports them.

30/60/90 plan + PDF

A keepable roadmap plus resume and LinkedIn repositioning.

Grounded in O*NET-linked or curated role data, with Penn, Anthropic Economic Index, and AIOE signals where matched. BLS labor-market context is separate - not generic advice.

Adjacent career paths

This role is already among lower-exposure work. The adjacent paths below are shown for opportunity and skill transfer, not as lower-exposure alternatives.

Construction Manager
82% skills overlap; 5 points lower - similar exposure within the 5-point model resolution; Moderate band; ~US$101,480
View path
41
7 more adjacent paths with exposure deltas, salary, demand, and reachability in your Career Report.
Agent Reality Check (on-site workflow preview)

Produce drawings and calculations

Check what deployed AI agents can attempt on tasks like this using dated capability evidence. You review the real task before any analysis runs.
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Your AI-Safe Career Report

Every task scored with what to do about it; adjacent paths with honest exposure deltas, salary, demand, and reachability; a skill-gap map; a 30/60/90-day roadmap; Agent Reality Check; plus a résumé and LinkedIn rewrite and professional PDF.
Grounded in O*NET-linked or curated role data, with Penn, Anthropic Economic Index, and AIOE signals where matched. BLS labor-market context is separate.

Workers with AI skills earn a roughly 62% wage premium - adapting pays. - PwC Global AI Jobs Barometer, 2026

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Important: This is an estimate of AI exposure, not a prediction that your job will disappear. It is designed to help you understand how your role may change and improve your career resilience.