The Cloud Security Alliance AI Model Risk Management Framework is a publication that provides guidance on managing risks associated with machine learning models. Released in July 2024 by the CSA AI Safety Working Group, the framework addresses financial losses, regulatory issues, and reputational harm that can result from unaddressed model risks. The framework consists of four core components that work together to identify and mitigate risks: AI model cards, data sheets, risk cards, and scenario planning. These components enable organizations to document model characteristics, data provenance, potential risks, and future scenarios in a structured manner. The publication targets AI/ML engineers, data scientists, risk management professionals, compliance officers, auditors, business leaders, executives, project managers, and communications professionals. It discusses how model risk management contributes to responsible AI development and deployment. Key topics covered include the benefits of comprehensive AI risk management frameworks such as enhanced transparency, informed decision-making processes, and robust model validation. The framework also explores the elements, benefits, and limitations of each core component and provides guidance on combining them into a comprehensive risk management approach. The framework supports continuous feedback loops to improve model development and addresses concerns related to predictive maintenance, smart supply chain management, and other ML applications.