The rise of AI in organizational practice has significantly transformed the way managers and employees handle information and make decisions. Although there has been significant progress by AI, organizations still struggle with integrating technology into decision-making, especially when AI systems are developed without considering human factors. In this conceptual paper, This conceptual paper investigates the relationships between the usage of AI for decision support and user-centered approaches by exploring relevant theories and concepts presented in modern management and information systems literature, as well as the field of human-computer interaction. Key aspects of interest include the automation-augmentation paradox, the importance of transparency and explainability in gaining user trust, cognitive and psychological features of human-AI interaction, and organizational features facilitating the effective use of AI. As such, this paper suggests that the value of AI is derived from human-centered decision-making, where managers maintain their discretion, retain cognitive engagement, and account for biases and accountability issues. Implications of this review include guidelines for designing AI-based decisions in an appropriate manner. Future studies could explore empirical connections among personal, organizational, and technological factors in shaping human-AI decision making in a number of different industries.
Ayshan Ahmadova (2026) studied this question.