This assignment critically examines the role of artificial intelligence in trans-
forming supply chain management within the retail industry. As organizations increas-
ingly adopt machine learning and predictive analytics to forecast demand, optimize in-
ventory, and reduce operational costs, the need for a structured evaluation of both the
benefits and the limitations of these technologies becomes essential. Drawing on re-
cent academic literature, industry case studies, and publicly available company data,
this paper explores how AI-driven decision-making affects efficiency, resilience, and
sustainability across the supply chain. It also considers the ethical and practical chal-
lenges that arise, including data privacy, algorithmic bias, and workforce displacement,
which remain central concerns for managers and policymakers alike. The analysis is
organized into four main sections: a review of the relevant literature, an evaluation of
current industry applications, a discussion of key challenges and risks, and a conclud-
ing set of recommendations. Ultimately, the assignment aims to provide a balanced and
evidence-based assessment of whether artificial intelligence represents a genuine
strategic advantage for retailers or merely an incremental improvement over tradi-
tional supply chain practices.
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