Artificial Intelligence Adoption and Its Influence on Working Capital Management in Emerging Economies
TL;DR
It is suggested that AI can enhance working capital practices by improving forecasting, financial information processing, monitoring, and decision support and provide practical recommendations for companies seeking to improve liquidity planning, receivables management, inventory control, and payment decisions through technology-driven management.
Abstract
Artificial intelligence (AI) is increasingly utilized as a valuable tool in financial decision-making; however, its application in working capital management (WCM) remains under explored, particularly in emerging economies. This study examines the relationship between AI adoption and WCM, specifically investigating whether AI-powered forecasting, financial information analysis, automation, monitoring, and decision support are associated with more effective management of short-term financial resources. A quantitative, cross-sectional methodology is employed, with AI adoption measured using five indicators and WCM assessed through six indicators on a five-point Likert scale. The analytical framework incorporates firm size, firm age, profitability, and sales growth as control variables. Descriptive statistics, reliability analysis, Pearson correlation, and multiple linear regression are used to analyze the proposed relationships. The results indicate a positive and statistically significant association between AI adoption and WCM; AI adoption demonstrates the largest standardized effect in the regression model (β = 0.531, p < 0.001), while firm size also exhibits a significant positive relationship (β = 0.102, p = 0.017). In contrast, firm age, profitability, and sales growth do not show statistically significant effects. The model explains approximately 29.9% of the variance in WCM, indicating substantial explanatory power. These findings suggest that AI can enhance working capital practices by improving forecasting, financial information processing, monitoring, and decision support. This study contributes to the literature by establishing a link between AI adoption and WCM and provides practical recommendations for companies seeking to improve liquidity planning, receivables management, inventory control, and payment decisions through technology-driven management. Additionally, the results offer a basis for further empirical research among firms and sectors in emerging markets.