Digital Transformation in Sustainable Building Design: User Perspectives on Architectural Tools and Applications

Digital transformation is increasingly reshaping sustainable building design by enhancing innovation, accuracy, and productivity through advanced digital tools. This study investigates how users’ self-reported familiarity with perceptions and use of modeling, simulation, and artificial intelligence (AI) applications contribute to sustainability-oriented design practices. A quantitative cross-sectional survey design was adopted, informed by a narrative review of the literature. The survey targeted students, academics, and recent graduates in architectural engineering. Quantitative data were analyzed using descriptive statistics, ranking analysis, and Multiple Factor Analysis (MFA) to examine digital competency patterns and tool evaluation criteria. The results reveal a common dimension of self-reported digital familiarity and proficiency across modeling, simulation, and AI applications, highlighting the importance of hybrid digital skillsets in sustainability-oriented workflows. Modeling, simulation, and AI applications collectively contribute to a unified competency dimension, highlighting the importance of hybrid digital skillsets. While traditional modeling tools demonstrate stable and widely shared perceptions regarding accuracy and productivity, AI-based tools exhibit more heterogeneous perceptions across functional categories. The second MFA dimension was more strongly associated with modeling than with simulation or AI, without establishing distinct specialization pathways. This study emphasizes the need for integrated digital workflows and competency-based education to support sustainable design. It contributes empirical evidence to the understanding of digital transformation in architectural practice and highlights emerging challenges and opportunities associated with AI integration.