International Journal of Technology | 2026
Authors: Glukhov V.; Babkin A.; Shkarupeta E.; Belyatskaya T.; Kozukov M.; Mambetjanov K.
DOI: 10.14716/ijtech.v17i3.8340
Journal: International Journal of Technology
Year: 2026
Publisher: Faculty of Engineering, Universitas Indonesia
Document Type: Article
Open Access: All Open Access; Gold Open Access
Cited by: 1
This study introduces the AI Regional Asymmetry (AIRA) methodology—a comprehensive framework for assessing and mitigating disparities in artificial intelligence (AI) development across countries and regions. Building on economic theories of inequality and resource complementarity, AIRA comprises four interlinked stages: (1) construction of a synthetic AI asymmetry index based on 23 indicators consolidated into four key dimensions — computational chasm, talent gravity, data monopolization, and capital cycle; (2) quantification of asymmetry using economic inequality metrics such as quantile gaps, Gini, and Theil indices; (3) identification of complementary country profiles to form strategic alliances — vertical, horizontal, or multilateral — aimed at resource exchange and imbalance reduction; and (4) scenario modeling to simulate the dynamic impacts of such alliances on global AI market structures. Applied to Belarus as a case study, the methodology reveals potential partnership configurations within the CIS region, with leading economies such as the United States and China, and with developing countries, thereby illustrating opportunities for regional strengthening and global asymmetry reduction. The framework offers policymakers quantitative tools for fostering equitable AI ecosystems, underscoring international cooperation as a strategic pathway to narrow digital divides and promote sustainable, inclusive growth in AI-driven markets. © 2026 Faculty of Engineering, Universitas Indonesia. All rights reserved.
AI asymmetry; AI governance; AI regional asymmetry; Digital divide; Economic sustainability