AI-driven smart construction for U.S. infrastructure modernization– understanding digital technology and it is tools for Architecture, Engineering, Construction (AEC) workflow: Review of literature

The growing integration of novel digital technologies and tools in the Architecture, Engineering, and Construction (AEC) business has resulted in substantial changes to workflow, performance, and project results. This review investigates how fundamental digital technologies, such as Building Information Modeling (BIM), Artificial Intelligence (AI), the Internet of Things (IoT), and Digital Twins, interact with specialized digital tools like Revit, Procore, AutoCAD, and Civil 3D to optimize AEC processes throughout the project lifecycle. The article conducts a methodical analysis of conventional, hybrid, and completely digital processes, evaluating their contribution to improved operational efficiency, data coordination, design correctness, and cost-effectiveness. This study uses literature synthesis, comparative analysis, and practical case references to identify how digital innovations lower error rates, promote sustainability, and transform project delivery models. Furthermore, the assessment identifies adoption benefits, such as worker preparation and fragmented data systems, and recommends collaborative solutions for maximizing digital value. By differentiating and integrating digital technologies and techniques (tools), this study adds to a comprehensive framework for developing smart building and modernizing infrastructure delivery.

Authors

Publication Details

Journal
World Journal of Advanced Research and Reviews
Published
2025-07-21
DOI
https://doi.org/10.30574/wjarr.2025.27.1.2453
Primary Topic
BIM and Construction Integration
Type
article
Field-Weighted Citation Impact
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article

AI-driven smart construction for U.S. infrastructure modernization– understanding digital technology and it is tools for Architecture, Engineering, Construction (AEC) workflow: Review of literature

Carlos Oshoke Umoru
World Journal of Advanced Research and Reviews
BIM and Construction Integration
article

AI-driven smart construction for U.S. infrastructure modernization– understanding digital technology and it is tools for Architecture, Engineering, Construction (AEC) workflow: Review of literature

Carlos Oshoke Umoru
article en

Abstract

The growing integration of novel digital technologies and tools in the Architecture, Engineering, and Construction (AEC) business has resulted in substantial changes to workflow, performance, and project results. This review investigates how fundamental digital technologies, such as Building Information Modeling (BIM), Artificial Intelligence (AI), the Internet of Things (IoT), and Digital Twins, interact with specialized digital tools like Revit, Procore, AutoCAD, and Civil 3D to optimize AEC processes throughout the project lifecycle. The article conducts a methodical analysis of conventional, hybrid, and completely digital processes, evaluating their contribution to improved operational efficiency, data coordination, design correctness, and cost-effectiveness. This study uses literature synthesis, comparative analysis, and practical case references to identify how digital innovations lower error rates, promote sustainability, and transform project delivery models. Furthermore, the assessment identifies adoption benefits, such as worker preparation and fragmented data systems, and recommends collaborative solutions for maximizing digital value. By differentiating and integrating digital technologies and techniques (tools), this study adds to a comprehensive framework for developing smart building and modernizing infrastructure delivery.

World Journal of Advanced Research and ReviewsVol. 27(1)
Openalex Percentile: Top 81%
BIM and Construction Integration
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AI-driven smart construction for U.S. infrastructure modernization– understanding digital technology and it is tools for Architecture, Engineering, Construction (AEC) workflow: Review of literature — Carlos Oshoke Umoru · World Journal of Advanced Research and Reviews (2025) | TGRS Research Map | TGRS