Artificial Intelligence as a Driver of Predictive Organizational Resilience: A Synthesis of Current Research and Future Directions

This article examines the role of artificial intelligence (AI) in shaping predictive resilience in contemporary organizations, aiming to synthesize existing research on how AI enables anticipatory and adaptive organizational capabilities under increasing uncertainty and complexity. A critical literature review approach is applied, drawing on interdisciplinary studies from management, information systems, cybersecurity, and organizational theory. The findings show that predictive resilience is increasingly understood as a proactive, data-driven capability supported by AI-based sensing, forecasting, decision support, and automation mechanisms, with major applications in supply chains, cybersecurity, finance, and organizational management. However, the literature also highlights key challenges, including data quality limitations, technological complexity, overreliance on AI systems, and ethical concerns related to bias, privacy, and transparency. The study concludes that although AI significantly strengthens organizational resilience, the field remains fragmented and requires further conceptual, theoretical, and empirical integration, particularly within socio-technical and governance perspectives.