Technology Category
Philosophy and Ethics of AI: AI & EpistemologyHumans and AI: Brain-Sensing and AnalysisData Mining & Knowledge Management: Linked Open Data, Knowledge Graphs & KB Completion
Owning the Intelligence: Global AI Patents Landscape and Europe's Quest for Technological Sovereignty
🤖 AI Summary
This study addresses the challenge of technological sovereignty in Europe amid U.S.–China bipolar dominance in global AI innovation. Drawing on linked patent and organizational data from WIPO, OECD, and commercial databases (2010–2023), it employs bibliometrics, corporate ownership mapping, citation network analysis, and gravity-model regression. The analysis yields three key empirical contributions: first, Europe does not constitute an independent innovation pole; second, global knowledge diffusion is driven primarily by technical capability—not political integration—highlighting the limited impact of EU membership on intra-regional knowledge flows; third, while China leads in AI patent volume and the U.S. dominates in citation-based influence, European patents exhibit high quality but low market share. Moreover, global AI innovation continues converging toward U.S. technological trajectories, underscoring persistent regional fragmentation.
Technology Category
Application Category
📝 Abstract
Artificial intelligence has become a key arena of global technological competition and a central concern for Europe's quest for technological sovereignty. This paper analyzes global AI patenting from 2010 to 2023 to assess Europe's position in an increasingly bipolar innovation landscape dominated by the United States and China. Using linked patent, firm, ownership, and citation data, we examine the geography, specialization, and international diffusion of AI innovation. We find a highly concentrated patent landscape: China leads in patent volumes, while the United States dominates in citation impact and technological influence. Europe accounts for a limited share of AI patents but exhibits signals of relatively high patent quality. Technological proximity reveals global convergence toward U.S. innovation trajectories, with Europe remaining fragmented rather than forming an autonomous pole. Gravity-model estimates show that cross-border AI knowledge flows are driven primarily by technological capability and specialization, while geographic and institutional factors play a secondary role. EU membership does not significantly enhance intra-European knowledge diffusion, suggesting that technological capacity, rather than political integration, underpins participation in global AI innovation networks.
Problem
Research questions and friction points this paper is trying to address.
Analyzes global AI patent landscape from 2010 to 2023
Assesses Europe's position in US-China dominated AI innovation
Examines factors driving international AI knowledge diffusion
Innovation
Methods, ideas, or system contributions that make the work stand out.
Analyzed global AI patents using linked data
Examined geography, specialization, and knowledge diffusion
Applied gravity models to study cross-border flows
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