Exploring public sector workforce attitudes toward AI competence and its impact on AI competence self-assessment

Abstract

This study addresses the growing importance of AI competence in the public sector, particularly in Latvia, where AI adoption is increasingly relevant for improving workplace efficiency and decision-making. The research explores self-assessed AI competence among public sector employees, focusing on the impact of workplace training and trust in AI-generated information. AI competence was evaluated using 10 sub-competencies based on AI functionalities, assessed on a 7-point Likert scale. A total of 1557 participants contributed to the study, which was analysed using descriptive statistics, Cronbach's alpha, Spearman rank correlation, network analysis, and the Kruskal-Wallis H test. The results show that only three AI sub-competencies scored close to the scale's mean value, indicating the limited use of advanced AI functions. Employees who received AI training rated their overall competence significantly higher than those without training. Additionally, more than half of the respondents expressed limited trust in AI-generated information, with only seven participants fully trusting AI. These findings underscore the need for targeted AI training to enhance competence and trust, highlighting the importance of integrating AI tools effectively in the public sector. The data that support the findings of this study are available on request from the corresponding author.