Women entrepreneurs in developing economies face persisting barriers in accessing financial services due to institutional constraints, limited credit history, and broader structural inequalities. While financial inclusion is widely recognized as a driver of women’s empowerment and sustainable economic development, existing financial systems often fall short in addressing gender-specific barriers [1]. Artificial intelligence has the potential to bridge this gap by offering data-driven solutions that facilitate access to credit, savings, and financial services [2]. However, most current AI applications in finance lack gender-sensitive data, increasing the risk of algorithmic bias and further marginalization [2]. This study explores the potential of AI to enhance access to finance for women entrepreneurs through the use of machine learning for alternative credit scoring, predictive analytics for financial planning, and blockchain technologies for secure transactions [3]. Based on a mixed-methods approach combining literature review and empirical data analysis, we assess how AI can enhance financial inclusion for women entrepreneurs by facilitating access to funding, improving decision-making, and expanding digital financial literacy via chatbots and virtual tools [4]. However, algorithmic fairness, ethical considerations, and regulation remain key challenges [5, 14]. We recommend strengthening gender disaggregated data systems, refining artificial intelligence algorithms to reduce bias, and fostering collaboration between financial institutions, fintech companies, and policymakers [6]. These steps will ensure a more inclusive, transparent, and equitable financial ecosystem for women [6, 17].