This paper examines the transformative role of artificial intelligence (AI) and machine learning (ML) in risk management within financial institutions. Traditional risk management methods are becoming insufficient due to the increasing complexity of financial products, the rapid pace of transactions, and evolving regulatory demands. The concept of “creative destruction” is applied to risk management, highlighting how AI and ML technologies can disrupt and enhance risk identification, analysis, and mitigation processes. The study employs a mixed-methods approach, combining quantitative surveys and qualitative interviews, to assess the impact of these technologies. Findings indicate that AI and ML significantly improve risk mitigation, providing real-time, accurate risk assessments (Wu et al (2016) in Expert Syst Appl 185, 2016). However, successful integration requires addressing ethical considerations, regulatory compliance, and fostering an organizational culture supportive of innovation. The research underscores the need for financial institutions to balance technology adoption with responsible governance to manage risks effectively (Lam (2013) Enterprise Risk Management: From Incentives to Controls (3rd ed). Wiley).