Regression Analysis of Digitalization in Kazakhstan: Mathematical Modeling of Information Space Dynamics

Abstract

This study aims to comprehensively analyze the multifaceted process of digital transformation in Kazakhstan, with a particular emphasis on identifying potential risks and opportunities for societal development. An empirical approach using inferential statistical methods was employed, with a sample of 200 participants, including information technology (IT) professionals engaged in educational IT programs. Data were collected through questionnaires, in-depth interviews, and documentation analysis. The study identified key operational risks such as information system failures, business continuity disruptions, and data migration errors. Security risks, such as cybersecurity threats, confidential data leaks, and unauthorized access, were also highlighted. Additionally, human resource risks were noted, such as insufficient staff qualifications, resistance to change, and difficulties in adapting to new technologies. Promising areas of innovative development were identified, including the acceleration of new product development, improved business process efficiency, and the creation of new business models. The economic benefits of digital transformation include reduced operating costs, increased labor productivity, and expanded market opportunities. Social effects include enhanced service accessibility, improved digital competencies among the population, and an overall better quality of life. Based on the study’s findings, it is recommended that comprehensive security measures be implemented, including the installation of modern security systems, multi-factor authentication, and regular security audits. Prioritizing human capital development through training programs, motivation systems, and fostering a digital transformation culture is also essential. Kazakhstan’s digital transformation is a complex yet promising process, with its success relying on a systematic approach that integrates technological, organizational, and human factors to maximize benefits while minimizing risks.