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AI and Predictive Analytics in Performance Monitoring

Deepak GuptaInstitute of Technology and Management, Gwalior, IndiaPardaev JamshidTermez University of Economics and Service, Termez, UzbekistanAnorgul AshirovaDepartment of General Professional Sciences, Mamun University, Khiva, UzbekistanRakhimjon Rajapboyevich RakhimovDepartment of Electrical Engineering and Energy, Urgench State University, Urgench, UzbekistanBabaeva AsalMinistry of Development of Digital Technologies and Communications, UzbekistanBegimov O‘ktam IbrogimovichAlfraganus UniversityNita Jayesh MahaleD.Y. Patil College of Engineering, India
2026ng
ABI

Аннотация

Artificial intelligence (AI) and predictive analytics have revolutionized supply chain performance monitoring by enabling real-time visibility, proactive risk management, and data-driven decision-making. This chapter examines the integration of AI technologies—including machine learning, deep learning, and advanced analytics—into supply chain performance measurement systems. It explores how predictive models enhance forecasting accuracy, optimize resource allocation, and improve sustainability outcomes while maintaining compliance standards. Through systematic analysis of current research and practical applications, the chapter demonstrates how organizations transition from reactive compliance monitoring to proactive competitive advantage through intelligent performance systems.

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