What should civil engineers learn about AI first?

Check AI assisted calculations and designs against standards and your own judgment; Use AI to read survey data and reports without trusting it blindly; Know who is accountable when an AI tool contributes to a design. GAGE teaches each of these in its AI literacy program, and the first lesson is free.

AI and your job: Civil engineers

Plans and designs roads, bridges, water systems and other structures, and makes sure they are built safely.

Will AI replace civil engineers?

No published measure says the job disappears. The US Bureau of Labor Statistics projects employment of civil engineers to grow 6.4 percent, from 380,600 jobs in 2025 to 405,100 in 2035. What AI changes first is tasks, not whole jobs: of the 8 core tasks listed for this work, 1 already show up in AI use data. The practical move either way: learn to direct AI on those tasks and check its work.

What to learn first The numbers, with sources Start free: lesson 1

The public measures, side by side

Each one answers a different question. None of them is a prediction that your job disappears, and we do not blend them into one score.

Jobs outlook to 2035
The US Bureau of Labor Statistics projects employment of civil engineers to grow 6.4 percent, from 380,600 jobs in 2025 to 405,100 in 2035, with about 22,700 openings a year as people retire or change jobs.
What it does not mean: it is a ten year projection of total jobs, revised every year. It says nothing about any one employer or person.
How people use AI on this work
In Anthropic's Economic Index, conversations about this job's tasks were about 67 percent people working with the AI (learning, iterating, checking) and 33 percent handing a task over to it.
What it does not mean: it describes how people who already use one AI assistant use it, not how many jobs change.
How much of the work AI can assist
Microsoft Research rates this occupation 0.21 on its AI applicability scale of 0 to 1, from what people actually asked an AI assistant to help with.
What it does not mean: its own authors say applicability is not job loss. A high rating means AI can help with much of the work, which is a reason to learn it.

Where AI already shows up in this work

Core tasks of the job, from O*NET, that appear in real AI use. These are the parts of the day that change first.

Provide technical advice to industrial or managerial personnel regarding design, construction, program modifications, or structural repairs.

What stays with people

Core tasks with no AI use observed in the published data. That measures today, not a promise about tomorrow; these are where judgment, trust and presence carry the work now.

Test soils or materials to determine the adequacy and strength of foundations, concrete, asphalt, or steel.
Inspect project sites to monitor progress and ensure conformance to design specifications and safety or sanitation standards.

How long do I have?

Nobody can honestly name a year. The measured pattern so far is that hiring for junior roles slows first in the most exposed work, while people already in the job take on AI assisted tasks. The BLS projection above runs to 2035 and is revised every year.

Stanford's Digital Economy Lab found no widespread displacement, but employment for young workers in the most AI exposed jobs has fallen 19 percent behind comparable peers (August 2026). Read the study.

The practical answer is the same either way: the person who can direct AI on these tasks, and catch it when it is wrong, is the one a team keeps and hires.

What to learn first

In this order, for this job. Each is taught in GAGE's AI literacy program, Certified AI Practitioner: Workplace Foundations.

1.Check AI assisted calculations and designs against standards and your own judgment
Taught in Module 4, Practical AI Workflow Design and Prompt Engineering; Module 5, Critical Thinking and Context Engineering
2.Use AI to read survey data and reports without trusting it blindly
Taught in Module 5, Critical Thinking and Context Engineering; Module 7, Advanced AI Literacy
3.Know who is accountable when an AI tool contributes to a design
Taught in Module 3, Ethical and Responsible AI and Operational Governance; Module 6, AI in the Workplace and Team Leadership
4.Explain technical findings to non-engineers
Taught in Module 7, Advanced AI Literacy

Start free: lesson 1 See the whole program

Show an employer you can do it

A course certificate says you finished. At GAGE you explain each idea back in your own words and it is graded against the lesson, so your record shows what you understood. An employer can check it with one link.

Related jobs

Questions

Will AI replace civil engineers?: No published measure says the job disappears. The US Bureau of Labor Statistics projects employment of civil engineers to grow 6.4 percent, from 380,600 jobs in 2025 to 405,100 in 2035. What AI changes first is tasks, not whole jobs: of the 8 core tasks listed for this work, 1 already show up in AI use data. The practical move either way: learn to direct AI on those tasks and check its work.
How long do civil engineers have before AI changes the job?: Nobody can honestly name a year. The measured pattern so far is that hiring for junior roles slows first in the most exposed work, while people already in the job take on AI assisted tasks. The BLS projection above runs to 2035 and is revised every year.
What should civil engineers learn about AI first?: Check AI assisted calculations and designs against standards and your own judgment; Use AI to read survey data and reports without trusting it blindly; Know who is accountable when an AI tool contributes to a design. GAGE teaches each of these in its AI literacy program, and the first lesson is free.

Sources

U.S. Bureau of Labor Statistics, Employment Projections program, Employment Projections, Table 1.2: Occupational projections, 2025 to 35, and worker characteristics, 2025, 2025 to 2035 projections (tables page last modified August 27, 2026). The requested 2024 to 2034 set is superseded; the current table is used., Public domain (bls.gov/opub/copyright-information.htm: everything BLS publishes is in the public domain; cite BLS as the source). Read 2026-09-25.
Anthropic, Anthropic Economic Index, sixth release (claude_ai, monthly aggregates), release_2026_06_26 (report: Anthropic Economic Index report: Cadences, 2026-06-26; dataset commit 2ea58ff75e4247d26810c37f10c179edc2466cac). Period read: GLOBAL, 2026-05-01 to 2026-06-01, the latest month in the file., CC BY (release_2026_06_26/data_documentation.md: Data released under CC-BY; the repository README says data CC-BY, code MIT. The Hugging Face card metadata says mit, which covers the code.). Read 2026-09-25.
Microsoft Research (Tomlinson, Jaffe, Wang, Counts, Suri), Working with AI: Measuring the Applicability of Generative AI to Occupations (AI applicability scores), v1.1 (arXiv 2507.07935 revision v6), repository commit c94a07c52fb1d88ca5d221388f06d10e1bd6d2fe of 2025-12-22. Bing Copilot conversations, United States, 2024-01-01 to 2024-09-30., CC BY 4.0 (LICENSE.txt and README: This repository is licensed under CC BY 4.0). Read 2026-09-25.
National Center for O*NET Development, for the U.S. Department of Labor, Employment and Training Administration, O*NET 31.0 Database: Task Statements and Task Ratings, O*NET 31.0 (August 2026, the current production release per onetcenter.org/db_releases.html on 2026-09-25), CC BY 4.0 (onetcenter.org/database.html: licensed under a Creative Commons Attribution 4.0 International License). Read 2026-09-25.
This page includes information from O*NET OnLine by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA), used under the CC BY 4.0 license. O*NET is a trademark of USDOL/ETA. GAGE has modified all or some of this information; USDOL/ETA has not approved, endorsed, or tested these modifications.
Occupation code 17-2051. The skills, task grouping and plain language on this page are GAGE's own.