Governance Infrastructure for Autonomous Systems under the EU AI Act

Autonomous systems are increasingly evolving from isolated deterministic machines toward continuously operating, adaptive and distributed runtime infrastructures. This paper explores the structural governance implications of this transition under the EU AI Act and introduces the concept of Governance Infrastructure as a foundational layer for scalable autonomous systems. The paper develops several conceptual frameworks including: the Governability Gap, Continuous Runtime Governance, Runtime Legitimacy, Certification Continuity, Governance Persistence, and Governability-by-Architecture. Rather than treating governance exclusively as a static compliance activity, the paper argues that future autonomous systems may increasingly require continuously relevant governability during runtime operation. The analysis further positions the EU AI Act not merely as a regulatory framework, but as an early indicator of a broader infrastructural transition toward continuously governed autonomous systems. The paper intentionally remains conceptual and infrastructure-oriented. It does not prescribe specific implementation mechanisms, runtime enforcement architectures or technical execution control methods. Related works: A Governance Architecture for Safe and Bounded Autonomous Systems Non-Bypassable Execution Control in Autonomous Systems Runtime Legitimacy Architecture for Autonomous Fleets Architectural Governance of Autonomous Systems under the EU AI Act Capability Lifecycle Governance in Autonomous Systems

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-05-22
DOI
https://doi.org/10.5281/zenodo.20346615
Primary Topic
Ethics and Social Impacts of AI
Type
preprint
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Governance Infrastructure for Autonomous Systems under the EU AI Act

Andreas Blumer
Zenodo (CERN European Organization for Nuclear Research)
Ethics and Social Impacts of AI
preprint

Governance Infrastructure for Autonomous Systems under the EU AI Act

Andreas Blumer
preprint en

Abstract

Autonomous systems are increasingly evolving from isolated deterministic machines toward continuously operating, adaptive and distributed runtime infrastructures. This paper explores the structural governance implications of this transition under the EU AI Act and introduces the concept of Governance Infrastructure as a foundational layer for scalable autonomous systems. The paper develops several conceptual frameworks including: the Governability Gap, Continuous Runtime Governance, Runtime Legitimacy, Certification Continuity, Governance Persistence, and Governability-by-Architecture. Rather than treating governance exclusively as a static compliance activity, the paper argues that future autonomous systems may increasingly require continuously relevant governability during runtime operation. The analysis further positions the EU AI Act not merely as a regulatory framework, but as an early indicator of a broader infrastructural transition toward continuously governed autonomous systems. The paper intentionally remains conceptual and infrastructure-oriented. It does not prescribe specific implementation mechanisms, runtime enforcement architectures or technical execution control methods. Related works: A Governance Architecture for Safe and Bounded Autonomous Systems Non-Bypassable Execution Control in Autonomous Systems Runtime Legitimacy Architecture for Autonomous Fleets Architectural Governance of Autonomous Systems under the EU AI Act Capability Lifecycle Governance in Autonomous Systems

Zenodo (CERN European Organization for Nuclear Research)
Industry, innovation and infrastructure
Ethics and Social Impacts of AI
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Governance Infrastructure for Autonomous Systems under the EU AI Act — Andreas Blumer · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS