Conference Agenda

a. Research Question

Generative artificial intelligence has intensified regulatory activity across communications policy, data protection, competition law, cybersecurity, and digital economy governance. Governments are advancing digital sovereignty strategies and proposing AI-specific regulatory frameworks. While AI governance scholarship has expanded rapidly since the late 2010s, limited research examines how AI governance research itself is structured across geopolitical systems and funding regimes. Funding architectures shape which research agendas are prioritized, which normative frameworks gain institutional traction, and which countries develop regulatory expertise. This study asks three questions:
(1) How is AI governance research distributed across national and geopolitical contexts from 2017–2024?
(2) How do funding patterns vary across countries and geopolitical blocs?
(3) To what extent does research funding function as technopolitical capacity shaping global AI governance discourse?

By analyzing authorship and funding patterns, the paper investigates how knowledge production becomes embedded within structures of digital sovereignty, state competition, and regulatory power.

b. Research Methodology

We analyze 2,125 English-language AI governance publications indexed in Web of Science between 2017 and 2024, covering 99 countries. AI governance is conceptualized in two dimensions: governance of AI (regulatory frameworks and oversight mechanisms) and governance through AI (governmental adoption of AI systems to enhance administrative capacity). Methods include descriptive bibliometric analysis to assess publication concentration; co-authorship network mapping to identify collaboration clusters; systematic coding of funding acknowledgments to distinguish public and private sources; and regression modeling to estimate the association between national affiliation and likelihood of funded publication. This quantitative design enables structural analysis of epistemic production and funding intensity.

c. Disciplinary Fields

The study integrates communications and Internet policy, political economy of technology, science and technology studies, and international political economy. Theoretically, it combines world-systems analysis (Wallerstein, 1974), technopolitics (Hecht, 1998), cultural imperialism (Tomlinson, 1991), and glocalization (Robertson, 1995) to interpret AI governance research as a strategic domain within global knowledge hierarchies.

d. Novelty and Relevance to Contemporary Communications Policy

Focusing on the theme of Artificial Intelligence Policy and Geopolitics and Digital Sovereignty, this paper argues that AI governance research constitutes part of regulatory infrastructure. Existing scholarship documents AI’s societal impacts (Haenlein & Kaplan, 2019) and the rapid proliferation of AI regulation (Maslej et al., 2024), as well as platform governance and digital power structures (Gillespie, 2018; van Dijck, Poell, & de Waal, 2018). However, limited attention has been paid to the funding infrastructures that shape the research ecosystem underlying policy debates. Drawing on world-systems theory, the study evaluates whether AI governance reproduces core–periphery hierarchies. Building on technopolitics, it conceptualizes public funding as a strategic instrument through which states steer innovation and cultivate regulatory expertise. Cultural imperialism and glocalization perspectives illuminate how dominant ethical frameworks circulate globally while being adapted within national governance models.

e. Expected Results and Conclusions

Initial analysis demonstrates three results. First, AI governance research remains highly concentrated: the United States, United Kingdom, and China dominate authorship, followed by Germany and Canada. While East Asian participation has increased, Global South representation remains limited, indicating diversification without redistribution of epistemic power.

Second, funding patterns diverge from publication hierarchies. Countries such as China, Korea, Taiwan, Finland, and Spain show significantly higher probabilities of reporting public funding than the United States or United Kingdom. China’s centralized funding regime has become a major driver of AI governance research growth. Funding intensity reflects technopolitical strategy rather than productivity alone.

Third, the field exhibits emerging bipolar tendencies centered on the United States and China within a still asymmetric system. Funding regimes function as mechanisms of regulatory capacity and geopolitical positioning. AI governance research is shaping and being shaped not only by formal regulation, but by the institutional architecture that produces policy-relevant knowledge.

References

Gillespie, T. (2018). Custodians of the internet. Yale University Press.
Haenlein, M., & Kaplan, A. (2019). A Brief History of Artificial Intelligence: On the Past, Present, and Future of Artificial Intelligence. California Management Review, 61(4), 5-14. https://doi.org/10.1177/0008125619864925
Hecht, G. (1998). The radiance of France. MIT Press.
Maslej, N., et al. (2024). AI index report 2024. Stanford University.
Robertson, R. (1995). Glocalization. In M. Featherstone et al. (Eds.), Global modernities (pp. 25–44). Sage.
Tomlinson, J. (1991). Cultural imperialism. Johns Hopkins University Press.
van Dijck, J., Poell, T., & de Waal, M. (2018). The platform society. Oxford University Press.
Wallerstein, I. (1974). The modern world-system. Academic Press.