Technological, organizational and environmental determinants influencing the intention to adopt GEN-AI of public sector organizations: a cross-country comparative analysis

Purpose This study investigates the technological, organizational and environmental determinants influencing public sector organizations' adoption intentions of Generative Artificial Intelligence (GEN-AI). It further explores the similarities and differences in adoption intentions across Italy and Spain, providing valuable insights from a cross-country comparative perspective. Design/methodology/approach The research integrates Technology–Organization–Environment (TOE) and Technology Acceptance Model (TAM) framework. Data were collected via an online survey of 1060 public sector employees (687 from Italy and 373 from Spain). Structural equation modeling tested the hypotheses and validated the theoretical model. Findings Results indicate significant effects of perceived usefulness, perceived ease of use, relative advantage, compatibility and top management support on GEN-AI adoption intentions. Technological and organizational determinants are predominant in Italy, whereas environmental factors, particularly citizen expectations, strongly influence adoption in Spain, highlighting important contextual differences. Research limitations/implications The study underscores the significance of national contexts in technology adoption theories, illustrating that the same determinants can differ in influence between countries. For managers, results emphasize leadership, ethics and stakeholder expectations in fostering successful GEN-AI integration. However, limited comparative studies restrict generalizability beyond Italy and Spain. Originality/value The study contributes novel empirical evidence on GEN-AI adoption within public administrations, integrating TOE and TAM frameworks. By uniquely examining national context as a moderating variable, it provides valuable cross-country comparative insights into technology acceptance determinants in the public sector.