Rethinking AI-Era Transformation of Architecture, Engineering and Construction Education: A Multi-Stakeholder Perspective

Abstract

Artificial intelligence (AI) is reshaping the architecture, engineering and construction (AEC) sector. However, AEC education remains rooted within traditional disciplinary boundaries and a technology-centric training model, creating a widening mismatch between graduates’ capabilities and the cognitive, collaborative, and interdisciplinary demands of AI-enabled practice. Situated within the Chinese higher education context, this study bridges this gap through a multi-stakeholder survey (n = 352) noting perspectives from academia, industry and research. One-way ANOVA and Tukey’s HSD test were used to examine differences across stakeholder groups and disciplines, while a Bayesian Network was developed to model competency pathways, simulate intervention scenarios and identify key leverage points for curriculum reform. The analysis reveals that meaningful AI integration requires a reconstruction of competency, rather than the mere addition of standalone technical or software courses; it calls for fundamental changes in professional formation, curricula and pedagogy. Four core competencies emerged from the data: professional expertise, systems thinking, interdisciplinary collaboration and AI-enabled problem-solving. Bayesian Network simulations further indicated that curriculum expansion alone improved AI knowledge acquisition by 39.6%, but yielded only modest gains in practical skills (13.9%) and application competencies (4.5%). By contrast, integrated interventions that combined teacher development, university–industry collaboration and project-based practice produced substantial improvements in AI application competencies (37.9%), employment adaptability (29.3%) and industry satisfaction (14.1%). These divergent findings highlight the necessity of coordinated educational interventions to reconcile stakeholder expectations and foster AI-oriented competency development. Based on this evidence, the study proposes a competency-oriented framework and a phased curriculum transformation pathway, providing an empirical foundation for AI-driven curriculum reform and competency reconstruction in AEC education.