The impact of artificial intelligence in supply chain risk management: a targeted literature review
DOI:
https://doi.org/10.26439/ddee2026.n008.8777Keywords:
artificial intelligence , supply chain risk management , machine learning , predictive analyticsAbstract
Global supply chains have become increasingly complex and volatile, intensifying the need for robust risk management strategies that leverage emerging Industry 5.0 technologies. Artificial intelligence (AI) has emerged as a transformative tool in mitigating risks by enhancing predictive analytics, improving decision-making, and strengthening organizational resilience within supply networks. This study conducts a targeted literature review based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to assess the impact of AI on supply chain risk management (SCRM). The review synthesizes key findings from recent research, categorizing AI applications into supply network management knowledge areas. The results indicate that AI-driven technologies, including machine learning, natural language processing, and predictive analytics, significantly enhance risk visibility, improve forecasting accuracy, and reduce disruption response times. Nevertheless, challenges such as data quality, ethical considerations, algorithmic transparency, and implementation costs remain critical barriers to adoption. The study concludes by offering recommendations for future research and outlining practical implications for organizations seeking to integrate AI into their SCRM strategies.
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