AI LITERACY AS A FACTOR OF HUMAN CAPITAL COMPETITIVENESS IN THE DIGITAL INTERNATIONAL ECONOMY

Abstract

The rapid diffusion of generative artificial intelligence is changing the conditions under which human capital is formed, valued and compared across national labour markets. The relevance of the topic is determined by the growing integration of AI into business processes, knowledge-intensive services, education and cross-border digital work, while access to the same technological tools does not automatically produce equal productivity gains. The article addresses AI literacy as a multidimensional competence that should be distinguished from both elementary use of ready-made AI applications and advanced technical AI skills required for developing or configuring models. The discussion focuses on the conceptual relationship between AI literacy, digital skills and human capital, as well as on the ways in which AI changes the demand for professional, analytical, managerial and complementary human skills. Particular attention is paid to the international dimension of the problem: differences in occupational exposure to AI, unequal institutional and educational readiness, digital infrastructure gaps, cross-border mobility of knowledge workers and the increasing importance of regulatory awareness when AI is used across jurisdictions. The paper considers the role of conceptual understanding of AI, task formulation and practical interaction, critical verification of generated outputs, ethical and regulatory judgement, and adaptive human-AI complementarity. It also discusses how universities can move from a narrow policy of permitting or prohibiting generative AI towards competence-based integration of AI literacy into curricula. For programmes in international economics, the relevant educational issues include the use of AI in market analysis, international trade and finance, research, multilingual communication and business decision-making, together with systematic source verification and responsibility for final conclusions. The article further outlines possible approaches to measuring AI literacy through self-assessment, scenario-based tasks and performance indicators, creating a methodological basis for future empirical studies of its relationship with productivity, employability, mobility and the resilience of human capital in an AI-intensive economy.