Abstract
The present study aimed at identifying the status of previous studies related to the subject of the impact of artificial intelligence on the quality of decision-making in organizations, and providing a critical review of it. In fact, this study attempted to fill several gaps related to the recent studies in this field, which are considered few from the researchers' point of view. Moreover, it dealt with the most important findings and recommendations reached by those studies in relation to the impact of the use of artificial intelligence on the quality of decision-making in various types of organizations, the types of decisions that can be supported by artificial intelligence techniques. in addition, it identified the most important algorithms, methods, techniques and models of artificial intelligence revealed by these studies that could help providing an accurate decision-making. In order to achieve these goals, this study used the descriptive, analytical, documentary approach. Its results showed that the use of artificial intelligence techniques positively affects the accuracy and quality of decision-making in different forms of these organizations no matter what structure of these organizations is. The study also found that the most important popular techniques and algorithms of artificial intelligence that can be used to improve the quality of decision-making are Support Vector Machine, Artificial Neural Networks, Back-propagation neural networks, Bayesian networks, Adaptive networks, Fuzzy inference system, Random Forest, Decision Tree, Logistic Regression, and K-Nearest Neighbor. The study recommended the necessity of conducting more experimental and exploratory studies on the impact of applying artificial intelligence on the quality of decision-making within organizations. Furthermore, it recommended designing models and action plans regarding employing artificial intelligence in decision-making in order to facilitate their implementation use, understanding, and the analysis of their results.