Welcome to Francis Academic Press

Academic Journal of Computing & Information Science, 2025, 8(3); doi: 10.25236/AJCIS.2025.080311.

Data Risk and Data Compliance Governance for Generative Artificial Intelligence

Author(s)

Zhuoran Li 

Corresponding Author:
Zhuoran Li
Affiliation(s)

School of Economics, Nanjing University of Finance and Economics, Nanjing, Jiangsu, 210023, China

Abstract

Generative Artificial Intelligence (Generative AI), being a revolutionary technology, has exhibited varied uses across industries. However, its rapid development has also brought with it high data risks, including leakage of privacy, unauthorized access to data, improper processing of data, abuse of data, infringement of intellectual property rights, and creation of counterfeit information. This paper systematically reviews such risks and explores the current status of generative AI in global and Chinese data compliance regulation. Clarifying existing regulations and highlighting the main challenges, this study presents solutions for enhancing awareness of data privacy protection, enhancing data usage authorization management, enhancing data storage and security functions, and strengthening international cooperation and standardization. The findings suggest the necessity of sound data compliance governance towards the long-term evolution of generative AI and emphasize the need for multidimensional data governance that brings technology, law, and ethics into harmonious alignment.

Keywords

Generative AI; data risk; compliance governance; privacy protection; legal regulation

Cite This Paper

Zhuoran Li. Data Risk and Data Compliance Governance for Generative Artificial Intelligence. Academic Journal of Computing & Information Science(2025), Vol. 8, Issue 3: 79-86. https://doi.org/10.25236/AJCIS.2025.080311.

References

[1] Grzegorz Mazurek, & Karolina Małagocka (2019). Perception of privacy and data protection in the context of the development of artificial intelligence. Journal of Management Analytics, 6 (4), 344-364. https://doi.org/10.1080/23270012.2019.1671243)

[2] Abel Monfort,Mariano Méndez Suárez & Nuria Villagra.(2025).Artificial intelligence misconduct and ESG risk ratings.Review of Managerial Science. https://doi.org/10.1007/s11846-025-00850-9

[3] Mohammad Gouse Galety,Jimbo Henri Claver,A. V. Sriharsha,Narasimha Rao Vajjhala & Arul Kumar Natarajan.(2024).Data Analytics and AI for Quantitative Risk Assessment and Financial Computation. https://doi:10.4018/979-8-3693-6215-0.

[4] Sasi Kumar Murakonda, & Reza Shokri (2020). ML Privacy Meter: Aiding Regulatory Compliance by Quantifying the Privacy Risks of Machine Learning.. arXiv (Cornell University).

[5] Alissa Brauneck,Louisa Schmalhorst,Mohammad Mahdi Kazemi Majdabadi,Mohammad Bakhtiari, Uwe Völker,Jan Baumbach,Linda Baumbach, & Gabriele Buchholtz (2023). Federated Machine Learning, Privacy-Enhancing Technologies, and Data Protection Laws in Medical Research: Scoping Review. Journal of Medical Internet Research, 25 (0), e41588. https://doi.org/10.2196/41588

[6] Paraskevi Christodoulou, & Konstantinos Limniotis (2024). Data Protection Issues in Automated Decision-Making Systems Based on Machine Learning: Research Challenges. Network, 4 (1), 91-113. https://doi.org/10.3390/network4010005.

[7] Amit Arora,Michael Barrett,Euisin Lee,Eivor Oborn, & Karl Prince (2023). Risk and the future of AI: Algorithmic bias, data colonialism, and marginalization. Information and Organization, 33 (3), 100478. https://doi.org/10.1016/j.infoandorg.2023.100478

[8] Kashif Naseer Qureshi,Hanaa Nafea, & Pyoung Won Kim (2024). Advancing healthcare systems: A tri‐tier architecture by using data communication, AI data generative and regulation and compliance standards. Expert Systems. https://doi.org/10.1111/exsy.13742

[9] Niklas Kruse & Julius Schöning.(2024).Legal conform data sets for yard tractors and robots: AI-based law compliance check on the right to one’s image. Computers and Electronics in Agriculture. https://doi.org/10.1016/j.compag.2024.109106.

[10] Amanda Heidt.(2024).Intellectual property and data privacy: the hidden risks of AI..Nature. https://doi.org/10.1038/d41586-024-02838-z