ARTIFICIAL INTELLIGENCE IN MANAGERIAL DECISION-MAKING

Artificial intelligence is no longer a peripheral concern for business administrationit sits at the center of how organizations sense their environments, allocate resources, and make consequential choices.Despite the volume of commentary on AI and management, the scholarly literature has struggled to move beyond domain-specific applications toward a theoretical account of what AI does to the decision-making process itself.This paper addresses that challenge.Drawing on bounded rationality theory, agency theory, the resource-based view, and dynamic capabilities theory, it develops an integrative conceptual modelthe AI-Augmented Decision Architecture (AADA) that maps how AI capabilities interact with organizational structures, human judgment, and governance mechanisms to shape decision outcomes across strategic, tactical, and operational levels of management.The paper argues that AI neither replaces managerial judgment nor simply speeds it up; rather, it restructures the cognitive and institutional conditions under which decisions are made.Realizing the benefits of this restructuring depends critically on how organizations design human-AI interfaces, govern algorithmic authority, and manage the cultural dimensions of AI adoption.The paper concludes by identifying open questions for future empirical and theoretical research.