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This chapter is excerpted from 'Artificial Intelligence Design and Solution for Risk and Security'. Various risks, security issues, and disasters have occurred environmentally and in the corporate world (Peters 2018; Gheuens et al 2019). Mitigation can be used for risks and security occurrences if using an appropriate approach. There must be a specific approach to mitigate the situation and further recommend mitigation strategies. Experts are required to identify the associated risks and securities early enough to safeguard the situation and minimize the impact. Risk and security management plays a major role in situations of uncertainty. The following are some relevant questions to risk and security management: How can this situation be forecasted and taken care of early in similar situations? Can these occurrences be captured historically? Can such patterns of occurrences be identified? Can the data relating to the occurrences be captured? Can the data be used to predict future occurrences? Can the relevance of the data be an important factor? Is security important? What happens if the data are manipulated? How are the data manipulated? How can the data be protected and secured? Security is the driving factor in risk management and plays an important role in the data. Various types of risk and security apply to various industries, business functions, roles, and responsibilities. This book intends to illustrate top business cases and use cases that apply to respective industries by suggesting ways to define, analyze, monitor, control, and mitigate risk (Morosan and DeFranco 2019; Aydos et al 2019). This approach mitigates risk using data and by putting corrective action in place. Such analysis takes time because humans cannot quickly analyze huge amounts of data. People can use data science, data analytics, and machine learning (ML) algorithms to speed the process. Artificial Intelligence (AI) enables machines to learn from previous human experiences through continuous learning from new sets of input data. The development of mathematical algorithms has led to the marked creation of ML and to the AI revolution today. In this book, AI will be used to mitigate risks through various case studies that the reader will understand and benefit from. AI produces effective and dramatic results in business. Many organizations desire to understand and improve risk management skills to improve their chances of handling risk. Risk and security has become important everywhere because of the large volume of data, different velocity, and variety of data. These aspects of life appear to be growing larger and more frequent and are often accompanied by negative impacts. People can use an undetermined amount of risk to strengthen their position. The range and breadth of risk and security creates havoc everywhere in the world, and on a variety of projects. Risk and security management is important in an organization because without it, the organization may have trouble defining its objectives. The most important reason for strategy implementation is fear of financial loss. This book focuses on problem statements with appropriate use cases and proposes AI solutions using data science and ML approaches. In this book, we hope to provide concrete answers to the crucial questions facing so many organizations: Where are these risks and security issues and what can be done to lower their impacts? Is AI part of the answers to the risk and security mitigations?