Elevating Organizational Competitiveness: Deconstruction of Information System Management Models and Concepts Using Machine Learning

Abstract

This article discusses the role of machine learning in addressing the challenges of Information System (IS) management in today's business environment. It highlights the importance of data analytics, predictive maintenance, and security threat identification in overcoming the complexity of IS management. The article presents a custom framework that modifies paradigms for IS management, including data collection, continuous monitoring, machine learning model selection, and seamless integration. This approach is proven effective in solving problems and boosting competitiveness. The article provides risk mitigation techniques, realistic implementation methodologies, and case studies to help organizations embrace this innovative journey. The article concludes by highlighting the importance of implementing this novel paradigm as a necessary first step towards a data-driven, globally competitive future