Artificial Intelligence and Bounded Rationality in Managerial Decisions: Evidence from Smart Organizations in Digital Economies

Abstract

Artificial intelligence (AI) has emerged as a defining force in managerial decision-making within digital economies, fundamentally altering how organizations process information, evaluate strategic alternatives, and respond to environmental uncertainty. Drawing on Herbert Simon’s theory of bounded rationality, this study examines how AI-enabled decision systems interact with managerial cognition, organizational structures, and digital infrastructures in smart organizations. The paper develops a comparative conceptual framework that integrates behavioral decision theory, management science, and digital governance to analyze how AI both alleviates traditional cognitive constraints and introduces new forms of bounded rationality. By synthesizing interdisciplinary literature, the study demonstrates that while AI enhances analytical capacity, reduces information asymmetry, and supports predictive foresight, it simultaneously generates challenges related to algorithmic opacity, automation bias, data dependency, and accountability displacement. The findings suggest that managerial rationality in digital economies is no longer purely human or machine-driven but emerges as a hybrid construct shaped by the interaction between AI capabilities, human judgment, organizational routines, and governance mechanisms. The paper contributes to management and digital strategy literature by articulating a structured model explaining when AI augments managerial rationality and when it creates new decision limitations in smart organizations.