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AI has proven to be a transformative tool in detecting and preventing data breaches, surpassing traditional cybersecurity measures. This research highlights the effectiveness of advanced machine learning (ML) models, including Multilayer Perceptron with 85% accuracy, in identifying subtle security threats and addressing zero-day attacks. Industries like finance, healthcare, and e-commerce have enhanced their security frameworks through AI’s real-time analysis and predictive capabilities. Despite challenges like data privacy and implementation costs, AI’s adaptability and precision position it as an essential component of modern cybersecurity. Future advancements, including integration with blockchain and microservices, will further strengthen its role, provided ethical practices and regulatory compliance are maintained. This supports my hypothesis that AI-driven systems, leveraging advanced ML models, are more reliable and effective than traditional methods in enhancing organizational cybersecurity.