Applying Artificial Intelligence to Improve Supply Chain Financial Performance

Abstract

The ongoing digital transformation of supply chains is increasingly leveraging artificial intelligence (AI) to enhance financial performance across supply-chain networks. This paper investigates how AI technologies—including machine learning, predictive analytics, and automation—can be applied to improve financial outcomes such as cost reductions, working capital efficiency, risk mitigation, and revenue growth in supply chains. Using a mixed-method approach combining literature review, empirical case data, and numerical modelling, we reveal that AI adoption can reduce total supply chain costs by 20-30% and optimize working capital needs by similar margins. We also identify key enablers (data integration, process redesign, cross-functional alignment) and barriers (data quality, legacy systems, change management). The study contributes a conceptual framework linking AI interventions to financial performance metrics and provides quantitative illustrations of financial gains. Finally, we discuss implications for practice and future research directions.