The financial sector has experienced significant transformation with the adoption of Artificial Intelligence (AI) technology, particularly in improving business decision-making. This study aims to analyze the impact of AI on decision-making quality, focusing on risk analysis and portfolio management in Indonesia's financial sector. A mixed-method approach was utilized, combining quantitative and qualitative data to provide a comprehensive view of AI’s role in financial decision-making processes. Quantitative data were gathered through surveys of 50 respondents from various financial institutions, while qualitative data were obtained from semi-structured interviews with industry executives. The findings indicate that AI significantly enhances risk analysis accuracy by 25%, optimizes portfolio management, accelerates decision-making processes, and improves operational efficiency by automating manual tasks and reducing human errors. Despite these benefits, the study also identifies challenges such as data quality issues and high implementation costs, which hinder the broader adoption of AI in the financial sector. The study concludes that AI offers substantial potential to improve decision-making in the financial industry, but addressing data infrastructure and training needs is critical for achieving optimal outcomes
