Public-Sector Readiness for the EU Artificial Intelligence Act

Abstract

Background: Differences in how institutions address the EU AI Act raise important questions about accountability, administrative consistency, and effective implementation.

Objective: The research compared approaches to the EU AI Act and explored which governance features were most closely associated with outcomes involving the public sector.

Methods: The study surveyed 571 relevant officials, professionals, service users, or regulated actors. Questionnaire items covered implementation quality, capacity, procedural clarity, transparency, and perceived effectiveness; associations with implementation outcomes were assessed descriptively and with multivariable regression.

Results: In the EU AI Act analysis, 547 cases were complete: 60% reflected consistent practice and 20% involved important procedural or capacity obstacles. Multivariable modelling showed independent positive associations for role clarity, staff capability, and access to formal guidance after accounting for organization size and jurisdiction.

Conclusion: These findings place institutional capacity at the centre of effective governance relating to the EU AI Act. Accordingly, public-sector AI rules are unlikely to be effective without operational capacity, transparent oversight, and clearly assigned responsibility.

Study design: organizational readiness survey.

Publication history: Originally published in print on 15 June 2024, Volume 4, Article 1. Online abstract record added on 16 September 2026. Full-text PDF will be added when the digital galley is ready.