Artificial Intelligence as a Driver of Regional Globalization of the CIS under Conditions of Polycentrism

The purpose of the study is to identify the mechanisms through which artificial intelligence (AI) influences regional globalization processes in the CIS and to substantiate the potential of individual countries of the region to act as flagships in the formation of a macro-regional AI contour. The study proceeds from the hypothesis that AI can strengthen the economic subjectivity of the Commonwealth not by itself, but only if supported by an energy, computing, transport and logistics, human-capital and regulatory base. The empirical basis of the research includes data from the IMF, UNCTAD, the WTO, the World Bank, the International Telecommunication Union, the International Energy Agency, the Government AI Readiness Index 2024, as well as official strategies, concepts and regulatory documents of the countries of the region. The methodological framework combines comparative, systemic and institutional analysis, analytical grouping of countries, and the comparison of quantitative and qualitative indicators of AI readiness. The article shows that the impact of AI on regional globalization is realized through productivity growth, the reduction of transaction and trade costs, the development of digital services, changes in the structure of value added, and the formation of new infrastructural dependencies, primarily in the fields of data, computing and energy supply. Priority areas for AI implementation in the CIS are identified: public administration, transport and logistics, industry, the agro-industrial complex, healthcare, education and energy. A three-level classification of CIS countries according to their AI leadership potential is proposed: systemic flagships – Russia, Kazakhstan and Uzbekistan; specialized flagships – Armenia, Azerbaijan and Belarus; prospective participants – Tajikistan, Kyrgyzstan and Turkmenistan. It is concluded that the formation of a sovereign macro-regional AI contour is possible not through fragmented national projects, but through compatible infrastructure for data, computing, human-capital development and regulation.