Skip to main navigation Skip to search Skip to main content

From policy to action: a cross-regulatory conceptual framework to address data and AI regulations

Research output: Contribution to journalArticlepeer-review

Abstract

Organisations operating in data- and AI-intensive environments face an increasingly fragmented and overlapping EU regulatory landscape, including the GDPR, AI Act, etc. Existing research largely addresses these regimes in isolation, offering limited guidance on integrated organisational compliance. This study develops a cross-regulatory integration framework that translates multi-regulatory obligations into structured organisational capabilities, explicitly assigning clear actors and responsibilities. Drawing on Actor-Network Theory (ANT) and a Strategic-Tactical-Operational (STO) decision-layer model, this study conceptualises compliance as a networked and multi-level governance process. The framework supports organisations in aligning ethical criteria, technical controls, and governance responsibilities across regulatory domains, advancing enterprise-wide digital governance and compliance management through both operational and functional processes.

Original languageEnglish
Article number2669329
Pages (from-to)1-10
Number of pages10
JournalJournal of Decision Systems
Volume35
Issue number1
DOIs
Publication statusPublished - 17 May 2026

Keywords

  • Actor-Network Theory
  • AI ACT
  • Cross-regulatory compliance
  • GDPR
  • [CUBS]

Fingerprint

Dive into the research topics of 'From policy to action: a cross-regulatory conceptual framework to address data and AI regulations'. Together they form a unique fingerprint.

Cite this