Enhancing Organizational Decision-Making through Explainable AI (XAI) Capabilities: A Systematic Literature Review

The Rise of AI in various aspects of organizational decision-making has raised concerns related to transparency, accountability and the safeguarding of human judgment, especially in strategy making. Explainable artificial intelligence (XAI) has been suggested as an important answer to these challenges, but current work is fragmented and predominantly focuses on technical explainability or trust at individual level. To address this research gap, the present study systematically reviews 28 peer-reviewed studies published from 2020 to 2025 by synthesizing how XAI is conceptualized and adopted in organizational decision-making of organizations which have obtained XAI systems and what human-centric considerations arise with its utilization. Based on the PRISMA framework and thematic analysis, our findings show how XAI is mainly framed as a type of transparency-and explanation-oriented mechanism that enables human sensemaking instead of autonomous decision-making. The majority of such literature considers decisions at the managerial level, and little is known in strategic and board contexts, as well as issues related to accountability and governance. This paper reconceptualizes XAI as a diagnostic tool which enables organizations to make organizational decisions rather than offering normative and governance based solutions.