2025, Vol. 8, Issue 2

This study examines the role of Generative Artificial Intelligence (GenAI) in optimizing working capital management within Indian manufacturing firms, a sector that is highly capital-intensive and often challenged by delayed receivables, inefficient inventory, and constrained liquidity. Using data from 70 Indian manufacturing firms, the study analyzes the impact of GenAI adoption on key working capital components—Days Sales Outstanding (DSO), Days Inventory Outstanding (DIO), Days Payable Outstanding (DPO), and the Cash Conversion Cycle (CCC). A quantitative research design was employed, combining descriptive statistics, independent samples t-tests, and regression analysis with sector and firm size controls. The results reveal that GenAI adopters experience significantly lower DSO and shorter CCC, indicating faster cash conversion and improved financial efficiency. While DIO and DPO show favorable trends, their effects are not statistically significant. The regression findings confirm that GenAI adoption is a strong predictor of working capital efficiency and profitability. The study contributes to literature by providing empirical evidence of GenAI’s financial impact in an emerging market context, addressing the AI productivity paradox, and extending the understanding of AI-enabled financial transformation. It also offers managerial insights and identifies challenges, limitations, and future research directions. Overall, the study concludes that Generative AI serves as a strategic enabler of working capital optimization and sustainable growth in manufacturing firms.