All occupations
Export

Structural Engineers

Construction, Maintenance & Repair
Projected change 2024–34: +5%
Median annual wage (2024): $99,590
Employment (2024): 369K

United States · BLS Employment Projections 2024–34 (figures for SOC 17-2051 occupational group)

AI exposure in published research

Figures below are reproduced from external datasets without modification. Where a dataset does not cover this occupation, the value is shown as — rather than as zero.

Data provider: OpenAI · "GPTs are GPTs"

Time basis: 2023 baselineex-ante estimate

Scored against GPT-4-generation capability.

Human rater basis
48.9%
GPT-4 rater basis
50.0%

β = direct exposure (E1) + 0.5 × exposure when tools are available (E2), per the source repository's definition.

26 rated tasks · 25 tasks with β ≥ 0.5 (96.2%)

Version:
gh-main-0471612
License:
MIT License · Copyright (c) 2024 OpenAI

Data provider: Anthropic Economic Index

Time basis: Published 2026-03-05composite index

Observed exposure
0.8%

Theoretical exposure index weighted by measured Claude usage, per the original report's definition.

38 tasks · usage observed in 2 · mean 4.2%

Data: Anthropic Economic Index — labor_market_impacts, CC-BY, https://huggingface.co/datasets/Anthropic/EconomicIndex

AI Changing Work uses Anthropic Economic Index data under CC-BY; Anthropic does not endorse or sponsor this site or its analyses.

Version:
hf-lmi-2026-03
License:
CC BY 4.0
Observation period:
(not applicable to this release)
Model:
(not stated by the source)

2023 prediction vs observation-based index published 2026-03-05

One card (GPTs are GPTs) is a 2023 estimate of what AI could theoretically do; the other (Anthropic Economic Index) is built from observed usage and was published on 2026-03-05 — that is its publication date, not the period it observed. They measure different things, so the two figures cannot be added, averaged, or ranked against each other. The older figure is kept here as a baseline for comparison rather than removed.

Caution: the Anthropic figures — observed exposure and task penetration — take the Eloundou β as one of their inputs. The two sides resembling each other is therefore not evidence that the earlier prediction came true; reading it that way is circular reasoning.

The Anthropic figures are measured on Claude users, who are not the whole economy and not the whole workforce.

The mapping of O*NET tasks and occupation codes was performed by AI Changing Work. The source figures themselves were not modified.

These indices are not forecasts. Which point in time each one belongs to is stated on the badge on its card.

Task Breakdown

  • Perform structural analysis and calculations
  • Create structural design documents
  • Inspect construction sites for compliance

About This Occupation

If you work as a Structural Engineers, AI is augmenting your role. Risk 31/100, exposure 41%.

ISCO-08 classification

Unit group 2142ILO official

Civil Engineers

Definition

ILO original text (English)

Civil engineers conduct research, advise on, design, and direct construction; manage the operation and maintenance of civil engineering structures; or study and advise on technological aspects of particular materials.

Definition & vocabulary source

Source: International Labour Organization (ILO) — ISCO-08 Structure

License: ILO CC BY 4.0

View original

Official occupational information

  • ONET17-2051.00

    Civil Engineers

    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.

    View original
  • ONET17-2051.01

    Transportation Engineers

    Develop plans for surface transportation projects, according to established engineering standards and state or federal construction policy. Prepare designs, specifications, or estimates for transportation facilities. Plan modifications of existing streets, highways, or freeways to improve traffic flow.

    View original

Source: O*NET 30.2, U.S. DOL/ETA

License: CC BY 4.0

View original

Frequently Asked Questions

The Anthropic Economic Index puts observed exposure at 0.8%. The OpenAI "GPTs are GPTs" rubric puts occupation-level β at 48.9% under human raters. Both figures are reproduced from published research without modification.

They come from two published datasets: the Anthropic Economic Index (labor_market_impacts, CC BY 4.0) and the OpenAI "GPTs are GPTs" exposure rubric (MIT License, Copyright (c) 2024 OpenAI). AI Changing Work maps them onto O*NET occupation and task codes and does not calculate exposure scores of its own. AI Changing Work uses Anthropic Economic Index data under CC-BY; Anthropic does not endorse or sponsor this site or its analyses.

No. They are a diagnosis of exposure as measured at the time each source dataset was published. AI Changing Work publishes no prediction of future automation or job displacement for this occupation.

Recent Changes Affecting This Occupation

Mar 2026: Evergreen blog post published analyzing AI impact on structural engineering

[Source: AI Changing Work Blog]