A Conceptual Model for Intelligent Knowledge Management in the Big Data Era: Synergizing Artificial Intelligence and Business Analytics

In the era of big data, organizations face increasing challenges in managing and leveraging knowledge effectively. This study proposes a conceptual model for Intelligent Knowledge Management (IKM) by synergizing Artificial Intelligence (AI) and Business Analytics (BA) within integrated information systems in the steel industry. Drawing on empirical insights and theoretical foundations, the model aims to enhance organizational decision-making, knowledge sharing, and strategic agility. The steel industry, characterized by complex operations and rich data generation, serves as a highly relevant case study for validating the model. Empirical application of the framework demonstrated improvements in decision-making efficiency and more effective knowledge dissemination across organizational units. Key components of the proposed framework include intelligent data processing, contextual knowledge extraction, and analytics-driven feedback loops. The study contributes to both academic and practical domains by offering a structured approach to embedding intelligent knowledge practices in data-intensive industries.

کلیدواژه ها:

Intelligent Knowledge ، Big Data ، Artificial Intelligence (AI) ، Business Analytics ، Intelligent Knowledge Management