University Positioning in AI Policies: Comparative Insights From National Policies and Non-State Actor Influences in China, the European Union, India, Russia, and the United States


KAYA KAŞIKCI S., Glass C. R., Camero E. C., Minaeva E.

HIGHER EDUCATION QUARTERLY, vol.79, no.4, 2025 (ESCI, Scopus) identifier identifier

  • Publication Type: Article / Article
  • Volume: 79 Issue: 4
  • Publication Date: 2025
  • Doi Number: 10.1111/hequ.70062
  • Journal Name: HIGHER EDUCATION QUARTERLY
  • Journal Indexes: Emerging Sources Citation Index (ESCI), Scopus, Periodicals Index Online, Education Abstracts, Educational research abstracts (ERA), ERIC (Education Resources Information Center), MLA - Modern Language Association Database, Political Science Complete
  • Middle East Technical University Affiliated: No

Abstract

This paper introduces a novel four-dimensional analytical framework to examine how universities are positioned within national artificial intelligence strategies amid intensifying geopolitical competition. Through systematic document analysis of policy frameworks across eight major global actors-the United Kingdom, Russia, India, the European Union, China, the United States, BigTech, and UNESCO-we identify distinct governance typologies that determine higher education's role in artificial intelligence ecosystems. Our findings quantify significant variations in how universities are instrumentalized across governance contexts-from talent pipelines in market-led systems to state-directed innovation hubs in centralised approaches. We document the emergence of value-aligned 'strategic education blocs' replacing universal academic networks, with India demonstrating unexpected leadership in education-specific policy provisions. This research advances the theoretical understanding of "technological statecraft" in higher education, demonstrating how the interplay between sovereignty concerns, regulatory philosophies, value systems, and public-private dynamics creates systematically different operating environments for universities across geopolitical contexts. These findings provide critical benchmarks for understanding institutional positioning in the global artificial intelligence landscape and challenge conventional internationalisation frameworks in an era of technological nationalism.