Strategic Impacts of Generative Artificial Intelligence Adoption in Public Administration: An Empirical Analysis

In recent years, the diffusion of Generative Artificial Intelligence (GenAI) has been profoundly transforming decision-making processes, organizational models, and knowledge creation practices in both the private and public sectors. However, the existing literature has primarily focused on specific technological applications, devoting less attention to understanding the strategic implications associated with its adoption within Public Administration (PA). In light of this gap, the present study aims to identify and prioritize the strategic impacts related to the adoption of GenAI in PA, while also analysing the differences across various public sectors. The research adopts a two-phase approach. First, a systematic literature review was conducted to identify the main strategic dimensions associated with GenAI adoption. Subsequently, these dimensions were analysed through the Analytic Hierarchy Process (AHP) using a survey administered to 80 public employees across two sectors: local government and healthcare. The results highlight that psychological barrier represent the most significant factor influencing the adoption of GenAI, followed by work performance and dimensions related to privacy and security. Moreover, the sectoral analysis reveals significant differences in the priorities assigned to the various factors. This study contributes to the literature by offering a comparative perspective on the strategic impacts of GenAI in the public sector and provides useful insights to guide the implementation strategies and innovation management within PAs.