Optimizing sustainable timber projects and asset management through AI-powered circular economy systems

Abstract

Purpose – The circular economy (CE) model can help the construction sector to meet the UN’s sustainable development goals (SDGs). Although artificial intelligence (AI) has enhanced CE practices in various construction contexts, its integration within timber reuse and recycling remains underexplored. This study proposes a theoretical model of an AI-powered CE system to improve sustainability in timber projects and asset management. Design/methodology/approach – A mixed-methods approach was adopted. Ten AI experts from Australian construction firms were interviewed using semi-structured questions to gain qualitative insights into how AI could optimize timber reuse. Of these participants, seven had extensive experience in AI applications for CE purposes in construction, while three were moderately familiar. Subsequently, an online survey collected quantitative data on system requirements from 102 industry professionals. These professionals included project managers, civil engineers and architects, providing broader perspectives on feasibility and adoption factors for AI in timber construction. Findings – Analysis revealed 23 AI-driven functions that would facilitate circular design optimization, material management and real-time monitoring of building performance. These functions underscore AI’s potential to reduce timber waste, prolong asset lifespans and streamline project workflows. Originality/value – This study advances current knowledge by providing empirical evidence (qualitative and quantitative) on AI-driven circularity in timber construction. The study demonstrates how AI can improve project execution, asset reuse and overall sustainability in the built environment. Practical recommendations are offered to guide the development and implementation of AI-powered CE systems for timber projects.