From Compliance to Governability: The Emerging Infrastructure Logic of the EU AI Act

Autonomous systems increasingly operate continuously, adapt dynamically, and interact with complex environments throughout their operational lifecycles. This paper introduces the concept of the Regulatory Continuity Challenge and argues that the long-term challenge of autonomous systems may not be achieving compliance at a specific point in time, but preserving the operational relevance and validity of regulatory objectives throughout continuous runtime operation. The paper develops a Governability Requirements Framework consisting of Observability, Traceability, Controllability, Auditability, Accountability Support, Adaptation Visibility, and Predictability. These requirements are proposed as system-level properties necessary for maintaining regulatory continuity over time. Building upon previous work on Governance Infrastructure and Continuous Governability, the paper further introduces the concepts of Governability Failure and Governability Infrastructure as mechanisms for preserving regulatory validity throughout the lifecycle of autonomous systems. The EU AI Act is interpreted not merely as a compliance framework, but as a potential indicator of a broader transition from episodic compliance toward continuous governability. Keywords: Governability, Regulatory Continuity, EU AI Act, Autonomous Systems, Governance Infrastructure, Continuous Governability, AI Governance, Runtime Governance, Regulatory Validity, Autonomous Ecosystems.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-05-31
DOI
https://doi.org/10.5281/zenodo.20478361
Primary Topic
Ethics and Social Impacts of AI
Type
preprint
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From Compliance to Governability: The Emerging Infrastructure Logic of the EU AI Act

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

From Compliance to Governability: The Emerging Infrastructure Logic of the EU AI Act

Andreas Blumer
preprint en

Abstract

Autonomous systems increasingly operate continuously, adapt dynamically, and interact with complex environments throughout their operational lifecycles. This paper introduces the concept of the Regulatory Continuity Challenge and argues that the long-term challenge of autonomous systems may not be achieving compliance at a specific point in time, but preserving the operational relevance and validity of regulatory objectives throughout continuous runtime operation. The paper develops a Governability Requirements Framework consisting of Observability, Traceability, Controllability, Auditability, Accountability Support, Adaptation Visibility, and Predictability. These requirements are proposed as system-level properties necessary for maintaining regulatory continuity over time. Building upon previous work on Governance Infrastructure and Continuous Governability, the paper further introduces the concepts of Governability Failure and Governability Infrastructure as mechanisms for preserving regulatory validity throughout the lifecycle of autonomous systems. The EU AI Act is interpreted not merely as a compliance framework, but as a potential indicator of a broader transition from episodic compliance toward continuous governability. Keywords: Governability, Regulatory Continuity, EU AI Act, Autonomous Systems, Governance Infrastructure, Continuous Governability, AI Governance, Runtime Governance, Regulatory Validity, Autonomous Ecosystems.

Zenodo (CERN European Organization for Nuclear Research)
National Training Service (CO)
Industry, innovation and infrastructure
Ethics and Social Impacts of AI
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From Compliance to Governability: The Emerging Infrastructure Logic of the EU AI Act — Andreas Blumer · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS