The EU Artificial Intelligence Act establishes

The gap

Evidence profile

Sourced from the stated research gap and limitations and synthesized of the source papers, classified as general, drawn from work published between 2024 and 2026, spanning 5 journals. Those papers have been cited 96 times in total.

Supporting evidence — 5 representative gaps

• Consensus and legitimation in global AI regulations: a sociosemiotic perspective (2026) · International Journal of Law in Context · cited 4× · doi

  The current global AI regulatory landscape is characterized by fragmentation and a lack of binding consensus. Previous international normative outputs have focused predominantly on ethical guidelines, policy documents, and technical standards, which typically lack binding consensus. The study aims to address the gap in understanding how normative consensus and legitimacy are constructed in global AI governance discourse.

  generalstated research gap
  Keywords: current global regulatory landscape characterized fragmentation lack binding
• ARTIFICIAL INTELLIGENCE AND ETHICS: A GLOBAL PERSPECTIVE (2026) · Çukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi · doi

  This study is limited to a selected set of international AI ethics reports published between 2019 and 2023 by major intergovernmental and regional organizations. National-level policies, sector-specific regulations, and corporate AI ethics frameworks fall outside the scope of the analysis. For instance, national frameworks such as Singapore's Model AI Governance Framework, China's New Generation AI Development Plan, or Brazil's AI Strategy reflect region-specific cultural values, economic priorities, and regulatory traditions that may differ substantially from the international frameworks analyzed here. Similarly, sector-specific guidelines developed by professional associations (e.g., medical AI ethics by healthcare regulatory bodies) or corporate AI principles (e.g., Microsoft's Responsible AI Standards, Google's AI Principles) embody organizational and industry- specific interpretations of ethical commitments that are not captured in this study. As a result, certain contextual variations in how AI governance is interpreted and implemented at national, sectoral, or organizational levels may not be fully captured. Moreover, these documents precede several significant regulatory developments, most notably the adoption of the European Union Artificial Intelligence Act in 2024, which marks a transition from predominantly voluntary ethical guidance toward legally binding regulatory obligations. Nevertheless, the analytical contribution of the present study does not lie in assessing the effectiveness of these newer regulatory instruments, but in systematically examining how foundational ethical principles were initially articulated and embedded within distinct institutional and governance logics.

  generallimitationsevidence 5/5
  Keywords: regulatory specific ethics national frameworks governance principles ethical international sector corporate organizational captured limited selected
• Global AI governance: barriers and pathways forward (2024) · International Affairs · cited 92× · doi

  While existing literature maps the nascent landscape of international AI governance institutions and identifies a governance deficit, there is no systematic analysis of how middle powers—nations with significant AI capabilities but limited institutional influence in Western-led bodies—can effectively shape or participate in emerging multilateral AI governance mechanisms, particularly given the rise of alternative institutional designs like WAICO that explicitly challenge incumbent Western-led governance structures.

  generalsynthesizedevidence 5/5
  Keywords: existing literature maps nascent landscape international governance institutions
• Racing Ahead, Governing Behind: An Institutional Analysis of AI Governance Readiness in Global Capability Centres (2026) · International Journal of Applied Information Systems · doi

  Existing research identifies that AI governance readiness varies significantly across organizations and regions, but does not address how middle powers—particularly those with emerging AI sectors in Global Capability Centres—can develop institutional capacity and governance maturity to participate effectively in global AI governance negotiations and standard-setting processes.

  generalsynthesizedevidence 5/5
  Keywords: existing research identifies governance readiness varies significantly across
• Regulatory research priorities for AI use in the medicine lifecycle: a European perspective with global relevance (2026) · Zenodo (CERN European Organization for Nuclear Research) · doi

  The EU Artificial Intelligence Act establishes a horizontal legal framework for AI systems but does not define how AI-generated evidence should be evaluated in the context of medicines regulation. There is a need to identify and prioritize regulatory research needs related to the use of artificial intelligence in the medicines lifecycle.

  generalstated research gapevidence 5/5
  Keywords: artificial intelligence act establishes horizontal legal framework systems

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