The Role of Artificial Intelligence in Shaping Privacy Laws: A Comparative Analysis of Global Regulatory Frameworks

Any Farida

doi:10.54783/influencejournal.v8i3.376

Authors

Any Farida Universitas Darul Ulum Islamic Centre Sudirman, Semarang, Indonesia

DOI:

https://doi.org/10.54783/influencejournal.v8i3.376

Keywords:

Artificial Intelligence, Privacy Law, AI Governance, Data Protection, Comparative Law.

Abstract

The rapid advancement of Artificial Intelligence has significantly transformed the processing and utilization of personal data, creating increasingly complex privacy challenges that extend beyond the scope of conventional data protection frameworks. Existing privacy laws in many jurisdictions have struggled to keep pace with the evolving capabilities of AI technologies, particularly regarding automated decision-making, algorithmic processing, cross-border data transfers, and large-scale data analytics. These developments have prompted governments and international organizations to reform legal frameworks in order to establish effective AI governance while maintaining the protection of fundamental rights and supporting technological innovation. This study aims to comparatively analyze privacy law frameworks governing Artificial Intelligence across major jurisdictions and to examine the regulatory gaps and future directions for AI-oriented privacy law reform. This research employs normative legal research using statutory, comparative, and conceptual approaches by analyzing international legal instruments, national legislation, and relevant scholarly literature concerning privacy protection and Artificial Intelligence governance. The findings demonstrate that the European Union, the United States, China, and Indonesia have adopted distinct regulatory approaches reflecting different legal traditions, governance priorities, and policy objectives, resulting in varying levels of protection, accountability, enforcement, and AI oversight. The study further identifies fragmented regulations, jurisdictional conflicts, cross-border data transfer issues, algorithmic accountability, transparency concerns, and enforcement limitations as the principal legal challenges that continue to hinder the effectiveness of global AI governance. Accordingly, future privacy law reform should prioritize adaptive and risk-based regulation, strengthen international regulatory harmonization, integrate privacy by design and human oversight into AI governance, and promote global cooperation to establish a balanced legal framework capable of safeguarding privacy while supporting responsible Artificial Intelligence innovation.

References

Abdalla, H. B. (2022). A brief survey on big data: technologies, terminologies and data-intensive applications. Journal of Big Data, 9(1), 107.

Alkatheiri, M. S. (2022). Artificial intelligence assisted improved human-computer interactions for computer systems. Computers and Electrical Engineering, 101, 107950.

Aubert-Hassouni, C., & Cloarec, J. (2022). Privacy regulation in the age of artificial intelligence. Digital Marketing, 544.

Calzada, I. (2022). Citizens’ data privacy in China: The state of the art of the Personal Information Protection Law (PIPL). Smart Cities, 5(3), 1129-1150.

Currie, W. L., Leimeister, J. M., Schlagwein, D., & Willcocks, L. (2025). Rethinking technology regulation in the age of AI risks. Journal of Information Technology, 40(3), 236-245.

Egbert, S., & Ulbricht, L. (2024). Data integration and analysis platforms as digital platforms: A conceptual proposal. Information, Communication & Society, 1-22.

Gstrein, O. J., & Beaulieu, A. (2022). How to protect privacy in a datafied society? A presentation of multiple legal and conceptual approaches. Philosophy & Technology, 35(1), 3.

Guo, Z., Hao, J., & Kennedy, L. (2024). Protection path of personal data and privacy in China: Moving from monism to dualism in civil law and then in criminal law. Computer Law & Security Review, 52, 105928.

Jaboob, A., Durrah, O., & Chakir, A. (2024). Artificial intelligence: An overview. Engineering applications of artificial intelligence, 3-22.

Lv, B., Deng, Y., Meng, W., Wang, Z., & Tang, T. (2024). Research on digital intelligence business model based on artificial intelligence in post-epidemic era. Management Decision, 62(9), 2937-2957.

Mettler, T. (2024). The connected workplace: Characteristics and social consequences of work surveillance in the age of datification, sensorization, and artificial intelligence. Journal of Information Technology, 39(3), 547-567.

Mustafa, G., Rafiq, W., Jhamat, N., Arshad, Z., & Rana, F. A. (2025). Blockchain-based governance models in e-government: a comprehensive framework for legal, technical, ethical and security considerations. International Journal of Law and Management, 67(1), 37-55.

Orhan, Z., Orhan, M., Lund, B. D., Mannuru, N. R., Bevara, R. V. K., & Porter, B. (2025). Artificial intelligence standards in conflict: Local challenges and global ambitions. Standards, 5(4), 27.

Peck Pinheiro, P., & Batista Battaglini, H. (2022). Artificial intelligence and data protection: a comparative analysis of AI regulation through the lens of data protection in the EU and Brazil. GRUR International, 71(10), 924-932.

Qureshi, R., & Koo, I. (2026). A comprehensive survey of cybersecurity threats and data privacy issues in healthcare systems. Applied Sciences, 16(3), 1511.

Radanliev, P. (2025). Cyber diplomacy: defining the opportunities for cybersecurity and risks from Artificial Intelligence, IoT, Blockchains, and Quantum Computing. Journal of Cyber Security Technology, 9(1), 28-78.

Radanliev, P. (2025). Frontier AI regulation: What form should it take?. Frontiers in Political Science, 7, 1561776.

Rizkia, N. D., & Fardiansyah, H. (2023). Metode penelitian hukum (normatif dan empiris). Penerbit Widina.

Rong, K., Ling, Y., Yang, T., & Huang, C. (2025). Cross-border data transfer: patterns and discrepancies. Journal of International Business Policy, 8(1), 10-32.

Sharma, A. K., & Sharma, R. (2024). Comparative analysis of data protection laws and AI privacy risks in BRICS nations: A comprehensive examination. Global Journal of Comparative Law, 13(1), 56-85.

Tang, M. (2022). The challenge of the cloud: Between transnational capitalism and data sovereignty. Information, Communication & Society, 25(16), 2397-2411.

Theodorakopoulos, L., & Theodoropoulou, A. (2024). Leveraging big data analytics for understanding consumer behavior in digital marketing: A systematic review. Human behavior and emerging technologies, 2024(1), 3641502.

Walter, Y. (2024). Managing the race to the moon: Global policy and governance in Artificial Intelligence regulation—A contemporary overview and an analysis of socioeconomic consequences. Discover Artificial Intelligence, 4(1), 14.

Wang, X., & Xie, F. (2025). Global artificial intelligence governance research in the digital and intelligent era: advances, trends and countermeasures. Journal of Knowledge Management.

Ye, X., Yan, Y., Li, J., & Jiang, B. (2024). Privacy and personal data risk governance for generative artificial intelligence: A Chinese perspective. Telecommunications Policy, 48(10), 102851.