<![CDATA[The rapid advancement of artificial intelligence (AI) has fundamentally disrupted traditional financial management practices. This study examines the transformative impact of AI-driven technologies including machine learning, predictive analytics, robotic process automation (RPA), and natural language processing (NLP) on the core domains of corporate financial management: financial planning and analysis, risk management, capital structure decisions, and working capital optimization. Employing a systematic literature review (SLR) methodology guided by the PRISMA protocol, this research synthesizes findings from 47 peer-reviewed articles published between 2018 and 2025 and indexed in Scopus and Web of Science. The findings reveal that AI adoption significantly enhances decision-making accuracy, reduces operational costs by an average of 30–40%, and strengthens early warning capabilities against financial distress. However, firms in developing countries face unique implementation barriers, including digital infrastructure gaps, limited AI-literate human capital, and regulatory ambiguity. This study contributes a conceptual framework the AI-Integrated Financial Management (AIFM) Model that maps AI technology adoption to specific financial management functions and delineates strategic priorities for organizations in emerging market contexts.]]>
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