Artificial Intelligence (AI) is a transformative technology that enables machines and software systems to replicate human intelligence, learn from experience, and make data-driven decisions. Its applications span multiple sectors, from personalized services in digital platforms to predictive analytics in healthcare, demonstrating its potential to enhance efficiency, innovation, and strategic decision-making. However, the widespread use of AI raises critical concerns regarding data privacy. AI systems depend on extensive datasets, often containing sensitive personal information, which exposes individuals to potential misuse, unauthorized access, and breaches of confidentiality. This study examines the intersection of AI and data privacy, analyzing both the technological mechanisms and legal frameworks designed to safeguard personal information. It explores methods such as encryption, anonymization, differential privacy, and secure data storage, alongside regulatory approaches including national privacy laws, international standards, and sector-specific compliance requirements. The paper highlights the challenges of aligning AI development with privacy protections, emphasizing the tension between maximizing AI capabilities and ensuring ethical, secure handling of personal data. By integrating legal and technological perspectives, the study provides a comprehensive assessment of how stakeholders—developers, policymakers, and users—can navigate the evolving landscape of AI while minimizing privacy risks. The findings underscore the importance of robust governance, transparency in AI operations, and continuous monitoring of emerging privacy threats. Ultimately, balancing innovation with ethical responsibility is essential to foster public trust, ensure compliance, and promote the sustainable adoption of AI technologies.