Department of Facility planning and management, School of architecture and engineering technology, Florida Agricultural and Mechanical University, USA.
World Journal of Advanced Research and Reviews, 2025, 27(01), 1711-1723
Article DOI: 10.30574/wjarr.2025.27.1.2453
Received on 17 May 2025; revised on 28 June 2025; accepted on 30 June 2025
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.
AEC; Smart construction; Artificial intelligent; Digital; BIM; IoT; Technology; Digital Tools
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Carlos Oshoke Umoru. 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. World Journal of Advanced Research and Reviews, 2025, 27(01), 1711-1723. Article DOI: https://doi.org/10.30574/wjarr.2025.27.1.2453.
Copyright © 2025 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0