Reframing Organizational Decision-Making in the Age of Artificial Intelligence: A Conceptual Review of Human–AI Augmentation
Dr. Pratik B. Upase
Assistant Professor
Department of Commerce
Vidya Bharati Mahavidyalaya, Amravati
Abstract
The increasing integration of artificial intelligence (AI) into organizational decision-making has fundamentally reshaped how managers analyze information, evaluate alternatives, and exercise judgment. Traditional decision-making theories emphasize human cognition, experience, and intuition, yet extensive research demonstrates that human judgment is constrained by bounded rationality, cognitive biases, and information-processing limitations. In parallel, advances in algorithmic intelligence have enabled organizations to augment human decision-making through data-driven insights, predictive analytics, and automated reasoning systems. Despite growing adoption, existing research on AI-driven decision-making remains fragmented and often framed through substitution-oriented narratives that position AI as a replacement for human judgment.
This study presents a conceptual meta-analysis of interdisciplinary literature on AI-augmented decision-making in organizations. By synthesizing research from decision sciences, management, and information systems, the paper traces the evolution of organizational decision-making from human-centric models to hybrid human–AI systems. Building on this synthesis, the study develops an integrative conceptual framework that explains how human judgment, algorithmic intelligence, and organizational context interact to shape decision quality and organizational outcomes.
The paper contributes to theory by reframing AI as an augmentation mechanism rather than a substitute for managerial judgment and by extending organizational decision theory to account for socio-technical decision systems. It further identifies key research gaps and proposes a future research agenda focused on human–AI interaction, organizational governance, and ethical accountability. From a practical perspective, the study highlights the importance of designing decision systems that leverage AI’s analytical strengths while preserving human oversight, responsibility, and strategic sense-making.
Keywords: AI-augmented decision-making; human judgment; algorithmic intelligence; organizational decision-making; conceptual meta-analysis
