Artificial intelligence (AI) is accelerating the global competition for highly skilled human capital, fundamentally reshaping the economic function of universities and redefining the strategic purpose of higher education internationalization. In this context, internationalization is no longer limited to cross-border student mobility but operates as a structural mechanism influencing national AI capacity, innovation performance, and long-term competitiveness. This article investigates how universities function as institutional platforms for AI talent formation, attraction, circulation, and retention, and how different internationalization models affect national outcomes in the emerging AI-driven economy. The study employs a qualitative comparative case study design, drawing on policy frameworks, higher education governance structures, research investment patterns, and international partnership strategies in selected Nordic countries and Romania. The comparative analysis enables the identification of structural differences in talent governance regimes and their measurable implications for innovation capacity and knowledge retention. The empirical findings demonstrate that coordinated higher education systems characterized by sustained public investment in research infrastructure, policy coherence, and strategically embedded international partnerships are significantly more effective in converting global AI talent mobility into domestic innovation output and long-term economic value creation. By contrast, fragmented governance arrangements and reactive internationalization strategies are associated with persistent outward mobility of AI-skilled graduates, weaker institutional research ecosystems, and limited returns on public investment in advanced digital education. Building on these findings, the article conceptualizes internationalization as a strategic instrument of AI talent governance within national innovation systems. It contributes to the economics of innovation and higher education by linking university internationalization strategies to AI competitiveness and offers policy-relevant guidance for countries seeking to strengthen their position in the global AI landscape.
Marja-Liisa Tenhunen (Mon,) studied this question.