Abstract
The construction industry, despite its significant contribution to global economic development, continues to experience persistent productivity stagnation, cost overruns, schedule delays, and elevated operational risks. Traditional construction management approaches largely based on deterministic planning models and experience-driven decision-making have proven insufficient in addressing the increasing complexity and uncertainty of modern project environments. In this context, the integration of Artificial Intelligence (AI) represents a transformative opportunity to enhance strategic performance and risk governance in construction businesses.
This study investigates the strategic impacts of AI adoption on productivity improvement and risk mitigation within construction enterprises. Drawing upon the Resource-Based View, digital transformation theory, and technology adoption frameworks, the research conceptualizes AI as a dynamic organizational capability rather than a standalone technological tool. The paper examines key AI applications, including predictive scheduling, cost forecasting, computer vision-based safety monitoring, supply chain optimization, and intelligent resource allocation.this research contributes to the literature by integrating engineering-focused AI applications with strategic management theory, offering a holistic framework for intelligent construction transformation. The study concludes that AI adoption is not merely a technological upgrade but a structural shift toward predictive, data-driven, and resilient construction business ecosystems.