A REVIEW OF THE CURRENT STATE OF ARTIFICIAL INTELLIGENCE ADOPTION IN SOUTH AFRICAN CONSTRUCTION PROJECT MANAGEMENT

Abstract Artificial Intelligence (AI) is increasingly transforming the global construction industry through enhanced automation, predictive analytics, and data-driven decision-making. In construction project management, AI technologies such as machine learning, computer vision, and Building Information Modelling (BIM) integration are improving project planning, cost estimation, safety management, and resource optimization. This paper reviews the current state of AI adoption in construction project management practices in South Africa. The study examines existing literature on global AI developments and evaluates how these technologies are being integrated within the South African construction sector. The review reveals that AI adoption in South Africa remains at an emerging stage, with implementation largely concentrated among large construction firms, multinational companies, and infrastructure megaprojects. Current applications include predictive analytics for cost and risk management, AI-enabled scheduling systems, BIM-integrated machine learning tools, and drone-based site monitoring technologies. Despite growing awareness of AI’s potential benefits, several barriers continue to hinder widespread adoption. These include high implementation costs, inadequate digital infrastructure, shortage of skilled professionals, fragmented project data, resistance to organizational change, and limited regulatory support. Furthermore, small and medium-sized enterprises (SMEs), which constitute a large portion of the South African construction industry, often lack the financial and technological capacity to adopt AI systems effectively. The study concludes that although AI adoption is still limited, the increasing advancement of digital technologies, growing industry awareness, and ongoing development of supportive innovation frameworks present significant opportunities for future AI integration in South African construction project management practices.