Administrative Burden in AI-Mediated Public Service Portals

Abstract

Background: The expansion of policy activity around administrative burden has exposed a potential gap between formal design and day-to-day implementation, particularly in relation to AI portals.

Objective: We evaluated the administrative operation of policy concerning administrative burden, emphasizing transparency, practical implementation conditions, and AI portals.

Methods: The study combined documentary, administrative, and where relevant stakeholder or practitioner evidence from 9 jurisdictions and 17 institutions. Materials were coded using a standardized framework, and descriptive plus multivariable analyses were used to examine implementation differences and institutional correlates.

Results: Only 37% of institutions met the predefined standard for consistent procedures around administrative burden. Settings with stronger coordination performed 22% better on the principal measure. The recurring constraints were insufficient capacity and uncertainty over institutional responsibility.

Conclusion: The study suggests that variation in outcomes related to administrative burden is driven substantially by how institutions organize implementation and oversight. This means that public-sector AI rules are unlikely to be effective without operational capacity, transparent oversight, and clearly assigned responsibility.

Study design: citizen user study.

Publication history: Originally published in print on 15 June 2026, Volume 6, Article 19. Online abstract record added on 16 September 2026. Full-text PDF will be added when the digital galley is ready.