Artificial Intelligence-Driven Digital Transformation of Investment Project Management in Large Industrial Enterprises: Evidence from Almalyk Mining and Metallurgical Complex (Uzbekistan)

The rapid development of digital technologies and artificial intelligence (AI) has fundamentally transformed project management practices across industrial sectors. Large mining and metallurgical enterprises, characterized by complex investment portfolios, significant capital expenditures, and long implementation cycles, require advanced digital management systems capable of improving planning accuracy, reducing operational risks, and supporting strategic decision-making. Traditional project management approaches often rely on fragmented information systems, manual reporting, and delayed managerial responses, resulting in schedule overruns, budget deviations, and inefficient allocation of resources. This study proposes an artificial intelligence-driven framework for investment project management based on the experience of Almalyk Mining and Metallurgical Complex (AMMC), one of the largest industrial enterprises in Central Asia. The research integrates digital workflow technologies, Directum RX electronic document management, Primavera P6 scheduling, and AI-based analytical modules into a unified project management architecture. The proposed framework enables predictive risk assessment, intelligent decision support, automated project monitoring, and continuous performance evaluation throughout the project life cycle. The research applies case study analysis, comparative assessment, business process modeling, and expert evaluation methods. The findings demonstrate that AI technologies significantly improve project transparency, accelerate management decisions, optimize resource utilization, and reduce administrative delays. Furthermore, the proposed framework establishes an integrated digital ecosystem capable of enhancing organizational efficiency while supporting sustainable industrial development. The scientific contribution of this research lies in developing an integrated AI-driven investment project management model applicable to large industrial enterprises operating under conditions of digital transformation.