Аңдатпа
The relevance of this study is driven by the accelerating pace of digital transformation in the Republic of Kazakhstan and the large-scale processing of personal data within digital services, online platforms, digital identification systems, as well as AI-based technologies. Although the circulation of personal data is defined in legislation through a clear conceptual framework, digital services and online platforms increasingly generate new forms and risks of unlawful collection and/or dissemination of personal data, including the specific features of committing such acts in the digital environment. In particular, alongside unlawful practices such as breaches of personal data security, unauthorized access, and unlawful dissemination of data, the active use of profiling-enabling the formation of evaluative inferences about an individual through automated processing-necessitates a reassessment of the effectiveness of criminal-law protection of personal data. The purpose of the study is to identify the pressing issues of criminal-law protection of personal data in the context of digital transformation in the Republic of Kazakhstan and to develop recommendations aimed at improving law-enforcement practice. The research employed a systems approach and a set of general scientific and specialized legal methods, a review of national regulatory legal acts, international standards, and academic literature was conducted. The research findings may be used in the work of law enforcement agencies, in harmonizing law-enforcement practice, and in providing a scholarly basis for proposals to improve criminal law provisions. This research was funded by the Committee of Science of the Ministry of Science and Higher Education of the Republic of Kazakhstan within the framework of the program-targeted financing project BR27101389 «The introduction of artificial intelligence tools into the legislative process of the Republic of Kazakhstan to optimize and improve the efficiency and transparency of legislation». Keywords: personal data, artificial intelligence, digital transformation, information security, deepfake, digital identification.