This chapter explores the transformative impact of data-driven automation and artificial intelligence (AI) and machine learning (ML) on financial decision-making. With the increasing complexity and volume of data in the financial sector, traditional decision-making processes are becoming less efficient and effective. The integration of AI and ML algorithms enables financial institutions to harness vast amounts of structured and unstructured data, automate routine tasks, and make real-time, data-driven decisions. This chapter delves into key AI/ML techniques, such as predictive analytics, anomaly detection, and natural language processing, and their applications in areas like risk assessment, fraud detection, algorithmic trading, and customer service. It also examines the challenges and ethical considerations surrounding the use of AI in finance, including data privacy, model transparency, and regulatory compliance. By highlighting case studies and emerging trends, this chapter provides a comprehensive overview of how data-driven automation is revolutionizing financial decision-making, offering new opportunities for efficiency, accuracy, and innovation in the industry.