This paper investigates the adoption of artificial intelligence (AI) in public governance and its impact on socioeconomic welfare, focusing on Slovenian Social Work Centres (SWCs). The objectives are to assess how AI applications align with governance models such as (Neo)Weberian Bureaucracy, New Public Management (NPM), and Good Governance, and to evaluate their effectiveness in promoting socioeconomic welfare. Furthermore, the study aims to identify opportunities and risks associated with AI in public governance and to provide policy recommendations for the ethical and effective integration of AI. A mixed-methods approach is adopted, comprising a comprehensive literature review to develop a theoretical framework, a cross-tabulation analysis of the European Commission's dataset of 686 AI use cases in 27 EU Member States, and a case study of AI implementation in Slovenian SWCs. This includes the analysis of administrative data from 2018–2022 on the e-Welfare platform and analysis of reports from Slovenian oversight bodies such as the Court of Audit, the Administrative Inspection, and the Human Rights Ombudsman. The results show that AI significantly improves administrative efficiency, particularly in the areas of resource management, cost-effectiveness, and service quality, which closely align with NPM principles. However, challenges remain in terms of transparency and accountability, as AI systems are often not transparent, making oversight difficult and jeopardising public trust, especially in the area of social welfare. The study concludes that while AI has significant potential to improve public governance, appropriate regulation and human oversight are essential to mitigate risks and ensure compliance with governance principles. The study provides valuable insights into the role of AI in administrative efficiency and is therefore relevant to policymakers, public officials, and researchers aiming to leverage AI's benefits while ensuring ethical governance and equitable socioeconomic outcomes.
Read full abstract