Governance theory emphasizes that networks are pivotal to societal governance and related steering mechanisms. One important means of steering is legislation, the evidence base of which is built on the interaction between social actors and the expert hearings related to the legislative process. This research uses network analysis to examine the construction of a legislative knowledge base and the information resilience displayed in the related networks. The data are derived from experts (n=440) appearing in committee hearings on five proposed acts of parliament. The results show that the expert consultations behind the legislation are official-oriented and illuminate the limited information produced by the private sector and a narrow view of scientific expertise. The network reveals epistemic authorities – mainly representing the security cluster – acting as gatekeepers. A more systemic approach is needed to build an evidence base encompassing the views on societal phenomena derived from different disciplines.

In today's rapidly evolving society, there is a pressing need for a transformed role of public governance to address modern challenges. The European Union has prioritised the digital and green transition, with a special emphasis on artificial intelligence (AI), a defining technology of the 21st century. The surge in AI developments owes to advanced computing, the accessibility of big data, and novel algorithms. The public sector produces vast data, making AI highly applicable. Properly integrated AI can enhance public service quality, foster trust, streamline operations, and drive public value creation. A European Commission survey revealed over 600 AI applications within the EU public sectors.

AI's potential implications for public governance are extensive. Governments can act in two roles regarding AI: as enablers, by investing in AI technology and infrastructure and as users, by utilising AI to boost service delivery and efficiency. While AI has broad societal consequences, its integration in the public sector has been less studied, especially its role in influencing socioeconomic welfare. Previous research in digital governance has been insufficient in covering AI's unique potential and risks. The role of public governance must evolve from a reactive to a co-creative approach to ensuring socioeconomic welfare.

The doctoral dissertation aims to explore the interrelation between AI, public governance and socioeconomic welfare. There's a lack of academic agreement regarding this relationship and its impact. By reviewing theoretical models, this study will pinpoint key components for a framework to analyse the connection between AI, public governance and socioeconomic welfare. Three main research questions are outlined: (1) Understanding the theory behind the relationship between AI, public governance and socioeconomic welfare, (2) Assessing the impact of public administration, as an enabler of AI, on socioeconomic welfare on the national level and (3) Determining the impact of public organisations, as AI users, on socioeconomic welfare on the local level. The dissertation's unique contribution lies in its in-depth literature analysis, creating a framework to measure AI's role in public governance and empirically studying the relationship between AI, public governance and socioeconomic welfare.