EU and US Take Sharply Different Paths in Governing Military AI, Study Finds

Artificial intelligence is reshaping the world’s armed forces, but the institutions that decide how the technology is adopted matter just as much as the algorithms themselves. A new comparative study published in the journal Global Public Policy and Governance examines how the European Union and the United States govern AI in the defence sector, and it reaches a striking conclusion: two actors with broadly comparable technological potential have produced profoundly different governance patterns, driven not by technical imperatives but by deeply embedded institutional logics. The research, authored by Emanuele Parisini of the Department of Computer Science at the University of Pisa, was published on 6 June 2025 and offers one of the most detailed institutional comparisons yet of military AI adoption on either side of the Atlantic.

The study integrates two established theoretical frameworks to make sense of the divergence. The first is Fountain’s technology enactment framework, which holds that information technologies are not simply adopted by organizations but are actively shaped, or enacted, by the institutional structures that surround them. The second is Horowitz’s adoption-capacity theory, which argues that a state’s ability to absorb transformative military technology depends on the financial and organizational capital it can marshal. By combining these lenses, Parisini argues that money alone cannot explain why the United States and the European Union have followed such different trajectories, because organizational capital, the accumulated capacity of institutions to absorb and deploy new technology, is the critical determinant of effective AI implementation.

The comparison reveals two distinct governance models. The United States exhibits what the study calls competitive institutional appropriation, a capability-first approach characterized by concentrated investment and a race to translate AI research into operational military advantage. This model is anchored in a dense ecosystem of institutions, from the Department of Defense’s Data, Analytics, and Artificial Intelligence Adoption Strategy, published in 2023 under the banner of accelerating decision advantage, to executive orders from the White House on safe and trustworthy AI development and, later, on removing barriers to American leadership in artificial intelligence. The National Artificial Intelligence Initiative Act of 2020 further institutionalized federal AI spending, and analyses of US government AI budgets show sustained growth in defense-related investment.

The European Union, by contrast, demonstrates fragmented institutional absorption. Rather than a single centralized push, AI adoption in European defence is distributed across member states and a lattice of EU frameworks, including Permanent Structured Cooperation, or PESCO, established by Council Decision in 2017, the European Defence Fund, and the Artificial Intelligence Act of 2024. The study finds that strategic choices within these frameworks have tended to reinforce member state autonomy rather than pool it, meaning that national capitals such as Paris and Berlin continue to chart their own courses. France, for example, has pursued defence AI through a dedicated defence innovation agency and one of Europe’s fastest classified supercomputers for defence applications, while Germany’s approach has been shaped by its own strategic reorientation. The result is a patchwork rather than a unified program.

The financial asymmetry between these two models is stark and consequential. The study highlights significant disparities in financial intensity between US and European defence AI efforts, a gap rooted in decades of divergent defence expenditure across EU countries. That spending gap, the analysis argues, creates technological dependencies, with European armed forces and defence industries relying on American platforms, standards, and infrastructure for critical AI capabilities. This dependency relationship poses profound implications for European strategic autonomy, the long-standing ambition that Europe should be able to act in security matters without critical reliance on external powers. In a domain as sensitive as military AI, where data pipelines, model architectures, and decision-support systems can determine battlefield outcomes, dependence on another bloc’s technology is a strategic vulnerability.

European policymakers are not blind to the problem. The study points to emerging strategic initiatives, most notably the European Commission’s White Paper for European Defence, known as Readiness 2030, published in 2025, as an attempt to close the gap and rearm Europe’s technological base. The White Paper sits alongside continued financing decisions for the European Defence Fund, which channels research and development money into collaborative defence technology projects. Yet the study’s central caution is that these initiatives will not succeed on funding alone. Because organizational capital, the trained personnel, institutional routines, data infrastructure, and decision-making structures that allow organizations to actually use AI, develops slowly, a surge of money without institutional reform risks reproducing the fragmentation that currently limits European absorption capacity.

The theoretical stakes of the finding extend beyond Europe. By showing that divergent implementation pathways reflect institutional logics rather than technological imperatives, the study challenges a common assumption that AI will naturally converge toward similar governance forms everywhere. Institutional theory has long held that organizations in the same field tend to grow alike through isomorphic pressures, yet the EU and US cases show that where those pressures come from, whether competitive markets, regulatory frameworks, or strategic traditions, shapes fundamentally different outcomes. In the American case, governance has been framed around competitive advantage and national security leadership; in the European case, around regulation, ethical safeguards, and the preservation of national sovereignty within a collective framework. Both are responses to the same technology, but they enact it in incompatible ways.

These divergences carry direct consequences for defence cooperation between the allies. The study suggests that successful transatlantic collaboration on military AI requires attention to both technical and institutional compatibility, while actively mitigating dependency risks. Interoperability between an American capability-first ecosystem and a fragmented European one is not merely a question of common data standards or shared interfaces; it requires aligning institutional logics that currently pull in different directions. The research also situates the issue in a broader geopolitical context, noting that the United States’ dominance of global arms exports has grown while Russian exports have fallen, and that Ukraine has become the world’s biggest arms importer, trends that raise the stakes of who controls the next generation of defence technology.

The methodological approach is a comparative case study, a design suited to tracing how institutional structures and organizational factors shape technology adoption in complex political settings. By examining documentary evidence ranging from the US Department of Defense’s AI adoption strategy and White House executive orders to the European AI Act, the Readiness 2030 White Paper, and national defence AI strategies from France and Germany, the study builds a picture of two governance systems operating at different speeds and with different centers of gravity. The author reports no competing interests, and the article appears in Volume 5 of Global Public Policy and Governance, pages 114 to 138.

For readers tracking the future of military technology, the study’s message is clear: the AI race in defence will not be won by algorithms alone. Governance structures mediate which technologies get adopted, how quickly, and under whose control, and the gulf between American competitive appropriation and European fragmented absorption is widening into a structural dependency that money alone cannot close. Whether initiatives like Readiness 2030 can build the organizational capital Europe needs, and whether transatlantic institutions can find enough common ground to cooperate on the most consequential technology of the era, are questions that will define European strategic autonomy for decades to come.

Subject of Research: Comparative governance of artificial intelligence adoption in the EU and US defence sectors

Article Title: Governing artificial intelligence in the defence sector: a comparative analysis of EU and US institutions

Article References: Parisini, E. (2025). Governing artificial intelligence in the defence sector: a comparative analysis of EU and US institutions. Global Public Policy and Governance, 5(2), 114-138. https://doi.org/10.1007/s43508-025-00115-x

Image Credits: AI Generated

DOI: 10.1007/s43508-025-00115-x

Keywords: artificial intelligence, defence policy, European Union, United States, AI governance, military technology, strategic autonomy, institutional theory, European Defence Fund, AI Act, defence innovation, transatlantic cooperation