Factors of Managerial Decision-Making in the Age of Artificial Intelligence

Abstract

Managerial decision-making has long been a central concern in management research due to its critical influence on organizational performance and competitive advantage. The rapid advancement of Artificial Intelligence (AI) has fundamentally transformed traditional decision-making processes by enabling data-driven, automated, and predictive capabilities that augment managerial judgment. This study examines the key factors influencing managerial decision-making in the age of Artificial Intelligence, drawing on classical, behavioral, and contemporary management theories. Through an extensive review of literature indexed in Scopus, Web of Science, and TCI databases, the study identifies and categorizes influencing factors at the individual, organizational, technological, and environmental levels. Individual factors include managerial experience, cognitive style, risk tolerance, and ethical values, while organizational factors encompass culture, structure, power dynamics, and information systems. Technological factors such as data quality, algorithm transparency, and levels of automation, along with external environmental factors including market competition, technological change, and regulatory pressures, are also examined. The findings highlight that managerial decision-making in the AI era is best understood as a socio-technical process shaped by dynamic interactions between human judgment and machine intelligence. The study contributes to the growing body of knowledge on AI-enabled management by providing an integrative framework for understanding decision-making complexity and offers practical insights for managers seeking to balance analytical rigor with ethical responsibility and strategic oversight in AI-driven organizational contexts.