AI-Driven Decision-Making and Managerial Effectiveness in Modern Organizations

Abstract

As AI tools become more prevalent in managerial tasks, there is a growing interest in the potential to improve managerial effectiveness with the use of AI in making managerial decisions. The relationship between AI-based decision making and the effectiveness of managers and supervisory personnel in service and technology-based organizations was explored in this study by adopting a quantitative, cross section design. A total of 210 managers and supervisory workers were selected through stratified sampling to ensure that the sample included workers of different levels of managerial responsibility, and were asked to answer a structured questionnaire that included several items measuring the extent of the use of AI tools, the quality of managerial decision making, the speed of decision making, the coordination of employees, and managerial effectiveness. To summarize the characteristics of the respondents and the distribution of the study variables, descriptive statistics were used, and correlation analysis was then used to examine the bivariate relationships among the study variables. Finally, multiple regression analysis was used to determine to what extent the use of AI for decision-making predicted managerial effectiveness. The managerial effectiveness was positively and significantly associated with each of the downstream process variables of AI adoption, decision quality, decision-making speed, and employee coordination, and the regression model showed that when these variables were controlled for, the decision quality and employee coordination were most strongly and significantly associated with managerial effectiveness, followed by the decision-making speed, while the AI adoption was only indirectly associated with managerial effectiveness. This study advances the application of AI in managerial decision making and its effectiveness benefits by showing that the benefits of AI-driven decision making are significantly, but not exclusively, mediated through increases in decision quality, speed, and coordination, affecting the design and assessment of managerial support systems that are based on AI.