In 2023, phone and cyber scams cost Americans over $12.5 billion, with fraudsters increasingly using AI to create sophisticated scams like phishing emails, counterfeit websites, and deepfake videos. To combat these advanced fraud tactics, businesses are employing AI fraud detection strategies, which include machine learning, natural language processing, and graph neural networks to quickly and accurately spot fraudulent activities. Unlike traditional methods that rely on fixed rules and human oversight, AI systems adapt and learn from new data, offering a modern approach to enhance cybersecurity and prevent fraud. These systems are trained on vast datasets to recognize patterns, verify identities, and detect anomalies in real-time, making them more effective than traditional methods. However, challenges remain, such as the need for high-quality data, continuous monitoring, and keeping pace with rapidly evolving fraud tactics. Businesses can further bolster their defenses with device intelligence techniques like browser fingerprinting, which enhances fraud detection by identifying unique device characteristics and spotting suspicious behavior. As AI continues to improve, it offers a significant advantage in predicting new fraud trends and enabling organizations to implement proactive security measures.