The study addresses the integration of Management Information Systems (MIS) and artificial intelligence into management processes. It has been stated that businesses and institutions need information systems to make effective decisions, and it has been emphasized that MIS supports managerial processes by meeting this need. It has been stated that with the development of artificial intelligence in recent years, MIS has made decision-making processes more efficient and has provided significant advantages in terms of speed, cost and accuracy in businesses. The importance of the study is that MIS supported by artificial intelligence and machine learning provides competitive advantage in businesses and improves strategic decision-making processes. It has been emphasized that the opportunities offered by MIS in areas such as data analysis, risk management, customer relations and forecasting are discussed, and that it offers managers the opportunity to make more accurate and faster decisions. The aim of the study is to contribute to the literature by examining the effectiveness of artificial intelligence-supported MIS applications. In this context, the basic features of MIS, its integration with artificial intelligence and machine learning methods are discussed in detail. Within the scope of machine learning, the contributions of methods such as Naive Bayes, Logistic Regression, Decision Trees and K-Nearest Neighbor algorithms to managers in decision-making processes have been evaluated. As a result, it has been revealed that AI-supported AIS applications increase the efficiency of businesses, minimize erroneous decisions and improve strategic management processes. With the development of artificial intelligence, the importance of AIS is increasing and it is becoming an indispensable tool in the digital transformation process of businesses.