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Artificial intelligence (AI) is reshaping the landscape of fraud, serving both as a tool for prevention and as a mechanism for increasingly sophisticated fraudulent activities. This study examines AI’s dual role, drawing on the distinction between predictive AI—widely used to detect and prevent fraud—and generative AI, which introduces new risks by enabling large-scale, automated deception. Predictive AI has long been integrated into fraud prevention across sectors such as finance, healthcare, and e-commerce, leveraging pattern recognition, real-time monitoring, and risk profiling to identify irregular activities. In contrast, generative AI—capable of creating hyper-realistic text, images, audio, and video—amplifies fraud risks by automating deception with unprecedented sophistication, scale, and accessibility. This study focuses primarily on the key capabilities of generative AI that make it particularly attractive for fraudsters, as well as the conditions that shape the complexity of fraud—examining when and how generative AI might be exploited. It also evaluates existing countermeasures, arguing that traditional human-centric interventions, such as awareness training, are increasingly inadequate against AI-generated fraud. Instead, the study advocates for AI-driven detection tools, broader regulatory measures, and cross-sector collaboration, highlighting the need for a proactive, technology-driven approach to addressing the evolving challenges of AI-enabled fraud.