The discourse surrounding technological sovereignty is frequently misconstrued. It is often presented as a choice between 'European' artificial intelligence models and those of American or Chinese origin. This is merely the surface. The fundamental question is distinct: who controls the entire stack upon which all else rests. This encompasses not only the models, but the chips, data centres, cloud infrastructure, training data, deployment tools, distribution channels, and recommendation systems. Sovereignty is not determined at the visible apex, but within the foundations that remain largely unexamined.
The Stanford AI Index estimates that almost 90% of the relevant AI models of 2024 originated from industry, not from academia or the public sector. That year, the United States produced forty of those models, China fifteen, and Europe three. In the cloud, the concentration is even more distinct: the European Parliament itself notes that three American companies account for approximately 65% of the European cloud services market, and on a global scale, those same three account for around two-thirds of the infrastructure. Compute—the processing capacity that trains and operates AI—is, according to specialised literature, the most concentrated bottleneck of all: detectable, quantifiable, and controllable by a few. The European gap is not merely regulatory. It is one of material capacity.
Europe has responded with an action plan for AI, public computing factories and 'gigafactories', a Data Act in force since September 2025 which seeks to facilitate the switching of cloud providers, and a cloud sovereignty framework that decomposes the term into evaluable criteria. Such measures are commendable. Yet, none of these initiatives are equivalent to sovereignty: they are infrastructures in deployment, procurement frameworks, and strategies in progress. The Gaia-X case serves as a cautionary tale: in an attempt to address dependency on major providers, it ultimately incorporated them, resulting in a form of sovereignty that was weaker and more pragmatic than promised. Declaring an AI 'European' is insufficient; what is significant is the reduction of actual dependency—the capacity to migrate, audit, execute, train, and safeguard data without becoming constrained by a foreign provider, jurisdiction, or business model.
Si quien ordena la atención —las plataformas, los modelos, los algoritmos de recomendación— está en pocas manos, entonces esas pocas manos condicionan qué lenguajes, qué obras, qué memorias y qué formas de creación circulan, se recomiendan o quedan enterradas. La literatura reciente lo formula con prudencia: los sistemas algorítmicos son agentes de mediación cultural, jerarquizan contenidos y producen visibilidad bajo lógicas de predicción y de atención; las métricas —vistas, “me gusta”, seguidores— funcionan como una nueva forma de capital, que desplaza parte de la autoridad desde las credenciales hacia el rendimiento algorítmico. No afirmo que los algoritmos sepulten toda creación minoritaria: eso sería una ley que las fuentes no sostienen. Afirmo que existe un riesgo real de invisibilización y de homogeneización, y que su forma depende de quién diseña la arquitectura.
Architecture is not neutral. It is not necessary for anyone to censor for some things to be seen and others not. It suffices that the infrastructure—technical, economic, algorithmic—quietly favours certain formats, certain tempos, and certain signals of success over others. Technological sovereignty, viewed from the perspective of culture, is also sovereignty of visibility: the capacity for that which is created in a language, on a margin, or at a small scale, not to depend entirely upon systems designed elsewhere and with a different logic.
The first step, when faced with an architecture that presents itself as air, is to perceive it. To name the three hands that hold the cloud, to distinguish infrastructure in deployment from achieved sovereignty, and not to confuse possessing an open model with controlling the stack that makes it function. That which is seen can be debated, regulated, and diversified. That which is assumed to be neutral cannot. And in culture, as in almost everything, freedom begins with knowing upon which foundations one is standing.
On the open conversation
This text continues the series regarding digital and cultural infrastructures that I have been publishing in this notebook: the material and energy cost of AI, the geographical distribution of computing power, and now architecture as a layer that decides without being seen. The texts share a fundamental thesis: in contemporary systems, the decisive factor is not individual conduct but infrastructural design, and that which presents itself as neutral is almost never so. If anyone wishes to intervene from the perspectives of AI governance, the political economy of technology, digital sovereignty, or cultural practice, this notebook remains open.
Sources
Stanford HAI. AI Index Report 2025.
European Parliamentary Research Service. Briefing on the Cloud and AI Development Act. 2025.
Synergy Research Group / Statista. Global cloud infrastructure market shares (Q1 2026).
Sastry, G.; Heim, L.; Belfield, H. et al. Computing Power and the Governance of Artificial Intelligence. arXiv:2402.08797, 2024.
European Commission. AI Continent Action Plan (2025); Cloud Sovereignty Framework (2025); Data Act (applicable from 12 September 2025).
Baur, A. Analysis of Gaia-X and European digital sovereignty. Information, Communication & Society, 2025/2026. DOI: 10.1080/1369118X.2025.2516545.
Sánchez-Vera, F. (2025); Valiati, L. and Möller, C. (2025); Wong, K. (2025), regarding algorithmic mediation and cultural visibility.