National artificial intelligence (AI) strategies increasingly shape university research priorities, creating complex tensions around academic openness and institutional autonomy. This analysis examines how universities navigate competing demands between international collaboration and national security requirements in AI research and development. It explores institutional responses as universities adapt to heightened scrutiny while striving to maintain their core academic mission and international engagement amid geopolitical tensions in a multipolar world.

Research universities are navigating a complex and evolving landscape of international collaboration, increasingly shaped by national artificial intelligence (AI) and technology security policies. Between 2020 and 2024, many countries launched or updated national AI strategies, explicitly tasking universities with specific roles in advancing national AI capabilities. This surge in AI-focused policies represents the latest chapter in the evolving relationship between universities and national strategic priorities—from Cold War research restrictions to post–September 11th security measures. However, the scale and scope of AI regulatory frameworks mark a distinctive shift in how governments view university research as central to national competitiveness and security.

While AI research faces the most direct scrutiny through directives like the Memorandum on Advancing the United States’ Leadership in Artificial Intelligence, new security frameworks affect collaborations across fields from climate science to public health. University leaders must now systematically evaluate international partnerships against multiple risk factors—from data sensitivity to technology transfer concerns. This marks an intensification from previous decades where international academic exchange, while never entirely unrestricted, operated with greater autonomy and less formal oversight.

Research Openness and National Security

The most immediate challenge facing research universities stems from the growing tension between academic openness and national security concerns. While export controls and other regulations have existed previously, the current geopolitical environment has intensified scrutiny of international partnerships, particularly in Europe and North America. Universities are adapting to these pressures. The Massachusetts Institute of Technology, for instance, has restructured its international research protocols, requiring additional review for collaborations involving AI algorithms and large language models.

Tensions are particularly pronounced in US–China research collaborations. The United States’ China Initiative, along with evolving export controls targeting advanced computing and semiconductor technologies, has created barriers to joint projects and scholarly exchanges. Western governments have increased scrutiny of China’s Digital Silk Road initiative, raising concerns about potential dual-use applications of technologies, data security, and intellectual property issues, particularly regarding projects involving companies like Huawei and ZTE in 5G network development and smart city projects.

Similar trends are evident globally. Australian universities have revised research security frameworks to align with government guidelines concerning foreign interference. Japan’s increased focus on cybersecurity and the establishment of specialized offices to monitor sensitive research partnerships underscore these global shifts. These measures signal change in how universities manage international collaboration, moving toward greater risk assessment and more formalized security protocols. This evolving landscape reflects greater emphasis on navigating both the benefits and the emerging risks of international research collaboration.

Universities are adopting “managed openness” approaches to balance research collaboration with security requirements. These frameworks typically involve screening partnerships, establishing transparent data-sharing agreements, and conducting regular security audits. Data governance has emerged as a particular challenge as institutions navigate diverse regional requirements—from the European Union’s GDPR (General Data Protection Regulation) compliance to varying national frameworks. Successful responses generally require robust governance structures, clear evaluation protocols for international partnerships, and enhanced compliance capabilities.

Institutional Autonomy Under Pressure

The relationship between public AI funding and institutional autonomy presents a growing challenge for universities worldwide. As national governments increase their investment in AI research, they often attach conditions that align research agendas with strategic objectives, creating tension with traditional academic independence. This dynamic manifests differently across major regions, reflecting varying approaches to university governance and national priorities.

In Asia, government influence on research priorities is particularly direct. China’s “New Generation Artificial Intelligence Development Plan” exemplifies this approach, with research universities operating under explicit national directives. In India, the National AI Strategy promotes the development and application of AI across various sectors, aiming to position the country as a leader in the field; however, Institutes of Technology must balance ambitious national AI targets with growing international partnerships.

The Western approach generally preserves more institutional independence. Universities in the United States maintain significant autonomy, though federal funding requirements can indirectly influence research directions. European institutions navigate a multilayered system: while the EU’s Horizon Europe program provides substantial funding, universities must comply with both European Union-wide regulations (such as GDPR and ethical AI guidelines) and member state policies, creating a complex environment for cross-border collaboration.

African universities exhibit a diversity of approaches, with some prioritizing partnerships with Western institutions, others engaging more closely with China, and still others pursuing pan-African collaborations through initiatives like the Partnership for Applied Sciences. Through initiatives like the Latin American AI Research Network, Latin American institutions are developing collaborative models that promote regional capacity building while safeguarding institutional independence. These varied approaches highlight how institutional autonomy intersects with local contexts and development priorities.

Talent Mobility and Recruitment Challenges

The intensifying global competition for AI talent presents significant recruitment and retention challenges for universities. Major research universities face difficulties maintaining international research teams due to factors like visa restrictions, security clearance requirements, and competition from industry. In some countries, national security frameworks necessitate citizenship or permanent residency for specific AI research positions, further restricting the talent pool.

These factors are reshaping global talent flows in complex ways across regions. While China invests heavily in domestic AI education, India has launched initiatives like “AI for All” and partnerships between its institutes of technology and global tech firms to build capacity. Brazil and other emerging economies are developing regional AI talent networks through initiatives like the Latin American AI Research Network. European institutions leverage programs like the European AI Fellowships, while ASEAN frameworks promote talent sharing across Southeast Asia.

However, many institutions in the Global South face persistent challenges around infrastructure, funding, and brain drain despite these regional efforts. The computing power and data infrastructure required for advanced AI research threatens to widen the divide between well-resourced universities and those in emerging economies. As revealed in UNESCO IESALC’s comparative policy review, less developed countries are increasingly forced to trade market access and data resources to gain access to essential AI capabilities, potentially deepening traditional center–periphery relationships in international higher education.

The geopolitical landscape has also impacted traditional academic mobility patterns. Many leading Asian universities are focusing on building robust domestic talent pipelines through enhanced graduate programs and industry partnerships. European institutions, promoting the European Union’s focus on “trustworthy AI” and ethical frameworks, aim to attract researchers who prioritize research integrity and ethical considerations.

Navigating the Complexities of “Responsible Internationalization”

The current shift toward “responsible internationalization” in research presents universities with a fundamental challenge: balancing the imperative for open scientific exchange with mounting pressure for security-conscious oversight. This tension echoes broader changes in international higher education, where the traditional emphasis on global collaboration increasingly competes with national security priorities. While the European Union’s principle of “as open as possible, as closed as necessary” offers one framework, questions remain about who defines these boundaries and how they affect global knowledge production.

The implications demand concrete action from university leadership and the broader higher education community. First, university leaders and administrators, in consultation with faculty and international partners, must develop clear protocols for evaluating security risks while protecting academic freedom—moving beyond compliance to proactive governance. Second, universities should strengthen regional research networks to maintain vibrant international collaboration even as bilateral partnerships face restrictions. Third, institutions must advocate for security frameworks that address legitimate concerns without undermining essential academic values or widening global inequalities in AI research access.

Most critically, universities need to actively shape the emerging discourse around “responsible internationalization” rather than simply reacting to it. This requires coordinated advocacy through international university networks, engagement with policy makers, and development of shared principles that balance security needs with the university’s fundamental mission of global knowledge creation and exchange. Without such leadership from the academic community, security considerations risk overwhelming the international character of university research that has proven essential for addressing global challenges.

Chris R. Glass is professor of the practice at the Lynch School of Education and Human Development, Boston College, United States. E-mail: [email protected].

Sevgi Kaya-Kaşıkcı is a postdoctoral researcher at the Middle East Technical University, Ankara, Türkiye. E-mail: [email protected].

Eglis Chacon Camero is doctoral candidate at the department of educational leadership and higher education of Boston College. E-mail: [email protected].

Ekaterina Minaeva is doctoral candidate at the department of educational leadership and higher education of Boston College. E-mail: [email protected].