Artificial Intelligence (AI) in working capital management: Practices and future potential

Stanley Chidozie Umeorah 1, *, Adesola Oluwatosin Adelaja 2, Oluwatoyin Funmilayo Ayodele 2 and Bibitayo Ebunlomo Abikoye 3

1 University of Michigan, Stephen M. Ross School of Business, Ann Arbor, MI, USA.
2 University of Virginia Darden School of Business, Charlottesville, VA, USA.
3 Central Bank of Nigeria, Banking Supervision Department, Abuja, Nigeria.
 
Review Article
World Journal of Advanced Research and Reviews, 2024, 23(01), 1436–1451
Article DOI: 10.30574/wjarr.2024.23.1.2141
 
Publication history: 
Received on 08 June 2024; revised on 15 July 2024; accepted on 17 July 2024
 
Abstract: 
This study delves into how artificial intelligence (AI) transforms working capital management by addressing the limitations of traditional methods. The focus is to critically review research publications, case studies and industry reports using qualitative research methodology to examine how AI improves operational efficiency and decision-making in this area. The study demonstrates the practical application of advanced machine learning algorithms and big data analytics in optimizing inventory management, enhancing demand forecasting and improving cash flow predictions. A thorough review of recent research and case studies reveals additional benefits, including automated reconciliations, debtor risk analysis, accelerated cash inflows, invoice processing and proactive working capital management. Despite challenges in integrating AI with legacy systems, the potential for substantial improvements in financial health and operational efficiency is significant. The study also suggests future research directions, such as developing comprehensive AI-driven applications for broader working capital considerations, creating empirical validation frameworks for model performance and addressing ethical considerations to fully harness AI's potential in optimizing working capital management.
 
Keywords: 
Financial Management; Artificial Intelligence; Machine Learning; Working Capital; Accounting Innovation; Automation; Technology Integration
 
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