Harnessing Artificial Intelligence to Boost Supply Chain Efficiency in Manufacturing: A Model with Accounting Automation's Influence

This study investigates the interplay between artificial intelligence (AI) adoption and supply chain performance within manufacturing contexts, focusing on the moderating roles of accounting automation and supply chain complexity. Employing a mixed-methods approach, quantitative data from 342 professionals across 12 industries were analysed using structural equation modelling (SEM), complemented by qualitative insights from 25 executive interviews. Results indicate that AI implementation significantly enhances operational efficiency <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$(\beta=0.45, \mathrm{p}&lt;0.001)$</tex>, with accounting automation amplifying this relationship <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$(\beta=0.28, \mathrm{p}&lt;0.001)$</tex>. Notably, organisations with high supply chain complexity achieved disproportionate efficiency gains (38% improvement, <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\beta=0.52$</tex>, p <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$&lt;0.001)$</tex>, aligning with the resource-based view (RBV) theory. These findings advance strategic frameworks for digital transformation in complex operational environments.