Securitizing the algorithm: a quantitative analysis of liberalization and securitization logics in the EU Artificial Intelligence Act

Introduction The EU Artificial Intelligence Act (AI Act) represents a global landmark in digital governance, yet the underlying political rationale structuring its provisions—securitization versus liberalization—remains underexplored. This study examines whether the AI Act constructs AI as an existential threat requiring exceptional measures or embeds it within the Union’s liberal regulatory tradition, while also developing a replicable framework for analyzing securitization in regulatory texts. Methods The study introduces the Securitization–Liberalization Balance Index (SLBI), a quantitative measurement framework that operationalizes securitization theory into structured indicators and applies them systematically to the full text of the AI Act. Results The findings reveal a hybrid regulatory configuration. Securitizing elements are concentrated in high-risk domains and prohibited practices, while liberalizing provisions display a consistent predominance in both average intensity and cumulative weight. At the same time, the SLBI demonstrates high internal consistency and analytical coherence, capturing structured variation across articles and chapters and supporting its robustness as a measurement instrument. Discussion The AI Act reflects a form of regulated and bounded securitization, in which security concerns are normalized through ordinary legal and governance mechanisms rather than emergency politics. This trajectory is further reinforced by recent EU initiatives, such as the “Digital Omnibus,” which emphasize regulatory consolidation and simplification rather than the expansion of securitization dynamics. The study proposes the SLBI as a replicable methodological framework for the empirical assessment of securitization dynamics in regulatory texts, contributing to the debate on the meta-security era.