Artificial Intelligence in Strategic Decision‐Making: How Fairness Risk, Trust, and Technical Capabilities Shape Organizational Performance

ABSTRACT Artificial intelligence (AI) is increasingly integrated into organizational decision‐making, yet performance effects remain uneven across firms. This study examines how AI technical capabilities translate into AI‐based organizational performance through strategic decision quality while accounting for perceived AI fairness risk and trust in AI systems. Drawing on a socio‐technical perspective, the study tests a process‐oriented model using survey data from 161 organizational decision‐makers across multiple industries in Kosovo and analyzes the data with partial least squares structural equation modeling (PLS‐SEM). The results reveal a central contradiction: perceived AI fairness risk negatively affects trust in AI systems, but trust in AI systems does not significantly influence strategic decision quality. At the same time, AI technical capabilities positively influence strategic decision quality, and strategic decision quality positively affects AI‐based organizational performance. However, strategic decision quality does not mediate the relationship between AI technical capabilities and organizational performance. These findings challenge trust‐centric assumptions in AI research and suggest that improved decision quality may be insufficient to generate performance gains without complementary organizational conditions. The study contributes to the literature by offering a socio‐technical explanation of AI‐driven value creation that emphasizes decision processes, fairness perceptions, and the limits of mediation‐based mechanisms in AI‐enabled strategic decision‐making.