An AI-Enabled Theoretical Framework for Reframing Sustainability Literacy as a Decision Capability in Circular and Socially Sustainable Construction Planning

Sustainability literacy is increasingly invoked in construction and planning research, yet it is most often framed as an educational construct concerned with awareness, knowledge, and attitudes. This framing provides limited explanatory power for understanding how sustainability values are translated into in real-world planning decisions, particularly under conditions of uncertainty and value conflict. In parallel, artificial intelligence (AI) has been introduced into planning practice largely as an optimization-driven analytical tool, reinforcing instrumental conceptions of rationality. This study reconceptualizes sustainability literacy as a decision capability and develops an AI-enabled theoretical framework that positions AI as a cognitive partner in sustainability-oriented construction planning. Methodologically, the study adopts a conceptual research design grounded in a systematic interdisciplinary literature synthesis spanning planning theory, circular economy, social sustainability, and AI-enabled decision support, combined with theory-building and framework development procedures. The proposed framework clarifies how human judgment can be cognitively augmented through AI-supported interpretation, trade-off exploration, and value-informed deliberation, thereby reframing sustainability as an internal driver of planning judgment rather than an external performance criterion. By conceptualizing human–AI collaboration as an iterative, reflective process, the study establishes a coherent theoretical basis for context-sensitive sustainability planning in the built environment, with implications for decision-support system design, planning practice, and professional education.