This study examines the impact of artificial intelligence (AI) on financial management, focusing on its role in financial decision-making, risk management, and customer experience. The research uses a systematic literature review approach to analyze the effects of AI in financial management, highlighting both its benefits and challenges. AI technology is increasingly being used in financial management to improve operational efficiency, predictive analysis, and decision-making processes. It enables faster and more accurate financial decisions, enhances customer service through chatbots and virtual assistants, and improves risk management by detecting fraudulent activities and analyzing transaction patterns. However, the implementation of AI in financial management also raises ethical concerns, data security risks, and adoption challenges. The study emphasizes the need for regulatory frameworks that support AI development while ensuring ethical and secure practices. It also identifies the importance of addressing these challenges to ensure the responsible and effective integration of AI in financial management. The research concludes that AI has the potential to transform financial management by improving efficiency, accuracy, and customer satisfaction, but it requires careful consideration of ethical, security, and regulatory issues to ensure its successful implementation. The study provides insights into the current state of AI in financial management and highlights the need for further research to address the gaps in understanding the ethical and practical implications of AI in this field.This study examines the impact of artificial intelligence (AI) on financial management, focusing on its role in financial decision-making, risk management, and customer experience. The research uses a systematic literature review approach to analyze the effects of AI in financial management, highlighting both its benefits and challenges. AI technology is increasingly being used in financial management to improve operational efficiency, predictive analysis, and decision-making processes. It enables faster and more accurate financial decisions, enhances customer service through chatbots and virtual assistants, and improves risk management by detecting fraudulent activities and analyzing transaction patterns. However, the implementation of AI in financial management also raises ethical concerns, data security risks, and adoption challenges. The study emphasizes the need for regulatory frameworks that support AI development while ensuring ethical and secure practices. It also identifies the importance of addressing these challenges to ensure the responsible and effective integration of AI in financial management. The research concludes that AI has the potential to transform financial management by improving efficiency, accuracy, and customer satisfaction, but it requires careful consideration of ethical, security, and regulatory issues to ensure its successful implementation. The study provides insights into the current state of AI in financial management and highlights the need for further research to address the gaps in understanding the ethical and practical implications of AI in this field.