Assessing Artificial Intelligence Readiness in Slovenian State Administration: Between Strategic Ambition and Operational Capacity

Purpose: This article examines perceived artificial intelligence (AI) readiness in Slovenian state administration bodies, moving beyond aggregate national scores to provide a systematic assessment at the organisational level. It aims to assess current readiness and identify potential structural imbalances among the readiness dimensions that determine the successof AI adoption.Design/Methodology/Approach: The study employed a survey-based design with a complementary qualitative component. Data were collected through an online questionnaire sent to 201 senior managers in Slovenian state administration bodies between May and July 2025. The final analytical sample comprised 85 valid responses. The quantitative analysis assessed AI readiness across seven dimensions and examined differences among four organisational types using descriptive statistics, Cronbach’s alpha, and Kruskal–Wallis tests, with post-hoc comparisons where appropriate. The qualitative phase analysed responses to an open-ended question about barriers to AI readiness using thematic coding.Findings: The findings indicate a moderately favourable but uneven pattern of perceived organisational AI readiness. Assessments were strongest for Organisational Culture and Legal and Ethical Considerations, whereas Technology was the dimension with the lowest perceived readiness, and People also showed comparatively limited readiness. Although Processes and Data had the highest mean score, its weak internal consistency means that findings for this dimension should be treated as exploratory and interpreted with caution. No statistically significant differences in the Overall AI Readiness index were found across organisational types although one significant between-group difference emerged for Processes and Data. This pattern is more consistent with the possibility of shared system-level constraints than with pronounced, generalised differences across organisational types. The most frequently reported barriers were Human Skills and Attitudes, Technological Resources, Legal and Ethical Constraints, and Strategic Direction and Governance. Overall, senior managers’ assessments suggest that strategic orientation in Slovenianstate administration is perceived to be more developed than the operational capacities required for implementation.Practical Implications: The article suggests that improving AI readiness in Slovenian state administration requires a coordinated organisational response that prioritises operational enablers alongside strategic commitment. Senior managers’ assessments highlight the need for greater technological capacity, targeted human resource development, clearer governance arrangements, and more practical legal and ethical guidance for implementation. As the identified barriers are largely shared across organisational types, policy responses should emphasise system-wide capacity building rather than fragmented, institution-specific interventions.Originality/Value: This study presents one of the first empirical assessments of AI readiness at the organisational level across Slovenian state administration bodies. Its value lies in applying a multidimensional AI readiness framework to state administration and demonstrating that strategic support for AI does not necessarily translate into operational preparedness. By combining AI readiness profiles with an analysis of barriers, the study provides an empirically grounded assessment of where readiness is strongest, where it remains limited, and which organisational constraints most need to be addressed.