AI-Driven Transformation of the Construction Industry: A State-of-the- Art Review

Abstract

The construction industry has been dealing with constant challenges of cost overruns, schedule delays, low productivity, and safety risks mainly due to the environmental factors of project complexity, dynamic site conditions, and high rate of uncertainty. Recent progress in artificial intelligence (AI) has opened up new opportunities for data-driven, predictive and adaptive decision making in construction management. This paper discusses a comprehensive review of applications of AI technologies, including machine learning, deep learning, computer vision and natural language processing, in the major construction management functions. The article examines how the use of AI is helping in project planning by better cost estimation and design optimization, scheduling through delay prediction and productivity forecasting, and project control through monitoring progress in real-time, risk and performance identification, and project performance evaluation. Key implementation barriers are also analyzed, including data availability and quality, lack of model transparency, integration issues with existing platforms such as Building Information Modeling (BIM) and organizational readiness. Taking a lifecycle- oriented perspective, this study shows how AI systems can help informed decision-making during planning, execution and control phases. The paper has added a value to the literature on construction engineering and construction management by providing a structured synthesis of existing applications with the identification of future research directions for the explainable, scalable, and industry-ready AI solutions.