With the acceleration of digitalization, the increasing volume of data, complex organizational structures, and uncertainty-laden decision environments have led managers to turn toward analytical and learning-based systems. In this context, artificial intelligence emerges as a strategic technology that strengthens decision-making, forecasting, planning, and knowledge management processes through machine learning, deep learning, and artificial neural networks.

This study aims to examine artificial intelligence technologies from a management science perspective by addressing their conceptual foundations, prominent technological approaches, and managerial application areas within a holistic framework. Accordingly, the historical development of artificial intelligence and the phases of transformation in management are first outlined; the concepts of machine learning, deep learning, and big data are explained; and subsequently, algorithmic decision-making processes and the main artificial intelligence technologies used in the field of management are evaluated based on the literature.

In addition, the differences between artificial intelligence and traditional information systems are discussed, and the contributions of artificial intelligence to managerial decision-making processes are examined. In conclusion, this chapter demonstrates that the value of artificial intelligence in management science lies in its integration into organizations’ decision-making and learning processes through a holistic approach that encompasses not only technical aspects but also organizational and ethical dimensions.