Navigating the Divide: Balancing AI’s Optimal Solution with the Appropriate Solution in Chinese Construction Management
Year: 2025
Type: article
Abstract: While Artificial Intelligence (AI) offers powerful tools for optimizing construction processes, its effective integration hinges on navigating the gap between algorithmic “optimality” and practical “appropriateness”. Focusing on China’s construction industry, a critical context for AI deployment, this research explores the managerial decision-making processes involved in balancing these two facets. Through a qualitative methodology involving 15 expert interviews across diverse organizational types (SOEs, private, consultancy) and thematic analysis incorporating constant comparison, this study elucidates the complex interplay between AI recommendations and human judgment. Key findings identify five interconnected themes influencing this balance: Decision Balance & Human Adjustment, Data & Technology Challenges, Human-AI Collaboration and Trust, External Constraints & Contextual Factors, and Sector-Specific Dynamics. The research highlights the proactive role of managers as “adaptive integrators” rather than passive users. Extending existing literature, this study contributes theoretically by challenging simplistic views of optimality, refining human-AI interaction concepts, and proposing an empirically grounded Adaptive Human-AI Interaction Framework that explicitly incorporates contextual modulators and managerial interpretation. The findings hold significant practical implications for developing more effective AI tools, targeted training programs, supportive organizational cultures, and nuanced policy guidelines to foster responsible and productive AI integration in construction and analogous operational fields.
Authors: Qi Wu, Menghao Xue, Bowen Lu
Institution: University of Malaya
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4410110192