The rapid development of digital technologies presents both a challenge and an opportunity for strengthening sustainability in construction project management. Within the broader digitalization agenda, Building Information Modelling (BIM) and Artificial Intelligence (AI) have emerged as key tools for improving environmental and economic performance through resource optimization. While traditional methods for optimizing resources, costs, and time remain relevant, the integration of BIM and AI introduces innovative capabilities that support decision-making, process automation, and data-driven sustainability strategies. The aim of this research is to analyze the extent to which BIM and AI are used for sustainable resource optimization in construction and to quantify their potential impact on the optimization of costs, resources, and time in the sector. A cross-sectional survey was conducted among construction companies operating in three European markets, Slovakia, Slovenia, and Croatia. The collected data were analyzed using descriptive statistics, correlation and regression analysis, and statistical hypothesis testing to assess the significance of relationships between technology adoption and sustainability outcomes. The results confirm that BIM adoption is positively correlated with improved sustainability management and optimization practices, with usage levels varying by company size and project scale. In contrast, AI adoption remains at a low level, indicating untapped potential for broader application. These findings contribute to understanding the role of digital tools in driving sustainable transformation in the construction sector and highlight areas for further research and practical deployment. BIM demonstrates particularly strong correlations with cost planning (r = 0.983), resource planning (r = 0.964), and schedule planning (r = 0.867), while AI shows robust associations with cost planning (r = 0.925), schedule planning (r = 0.865), and resource planning (r = 0.809). The findings indicate that maximum effectiveness is achieved when BIM and AI are deployed in a complementary manner under skilled human oversight.
Marovic et al. (2026) studied this question.