Abstract : The review explores the evolving relationship between cybersecurity, privacy, and regulations, with a particular focus on the impact of GDPR practices in the USA and Europe. While significant strides have been made in data protection and privacy standards, several gaps remain, particularly in harmonizing regulatory frameworks across regions and ensuring compliance among small to medium-sized enterprises (SMEs). The primary objective of this study is to investigate the extent of GDPR's influence on cybersecurity practices, identify challenges faced by organizations in compliance, and highlight the integration of deep learning technologies in enhancing privacy, integrity and security within AI-driven cybersecurity solutions. This paper offers a novel contribution by synthesizing findings across various sectors, including healthcare, banking, and emerging technologies, such as extended reality and IoT. The review used a systematic approach to analyze recent peer-reviewed sources on cybersecurity and privacy issues. Sources were selected based on criteria including empirical analysis of GDPR compliance, AI applications, and privacy laws in sectors like SMEs, healthcare, and banking. Data was extracted, synthesized, and analyzed thematically to identify patterns in regulatory compliance, technological innovations, and industry-specific insights, ensuring a comprehensive and unbiased review. The literature review on cybersecurity and privacy reveals key themes, including the evolving role of technology in data protection. A prominent finding is the significant impact of AI and deep learning, particularly in enhancing threat detection and safeguarding privacy across sectors. In healthcare, innovations like extended reality (XR) introduce new challenges in securing patient data, requiring robust cybersecurity measures. The Internet of Things (IoT) presents both opportunities and risks, emphasizing the need for advanced security protocols. Economic considerations highlight the adoption of cost-efficient solutions like cloud-based platforms, which improve security while reducing operational expenses. The review also identifies conflicting evidence regarding regulatory frameworks, with varying levels of effectiveness globally. Notably, there is a lack of empirical data on the long-term impact of AI-driven solutions and an absence of global standardization in cybersecurity regulations. The findings conclude that while GDPR has significantly bolstered data protection, challenges persist in small business compliance, and the integration of AI continues to be vital for advancing security measures. The review also discusses the broader implications of these findings, including the potential for GDPR-like frameworks in non-European countries and the role of emerging technologies in shaping privacy standards. Limitations of this study include a lack of comprehensive data from all sectors, especially in developing countries, and the need for further research into the specific effectiveness of AI applications across industries. Future research could focus on the long-term effects of GDPR on organizational behavior, privacy awareness and on the potential for global standardization of cybersecurity laws to further secure digital ecosystems.