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This study investigates the efficacy of training initiatives in Greek public administration through a dual lens: an original empirical survey of 450 civil servants analysed with non-parametric tests, and a comparative synthesis with reforms and statistical data from 2020 to 2026. The empirical component revealed statistically significant improvements in job security, efficiency, adaptability, professional recognition, and digital competence, consistent with Kirkpatrick's evaluation framework and Bandura's social learning theory. However, the analysis also highlighted heterogeneity by educational background and ceiling effects in intrinsic motivation. By contrast, recent post-2020 reforms have scaled training to thousands of employees, embedded learning into legislative frameworks, raised salaries, and integrated artificial intelligence tools such as mAigov into daily administrative practice. High satisfaction levels and rapid digital platform adoption indicate that micro-level survey insights align with broader modernization efforts. The article contextualizes this relationship not as a static divide, but as a dynamic interaction where individual learning readiness provides the absorptive capacity for macro-level administrative reforms in the AI-enabled era.
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Papadimitriou et al. (2026) studied this question.
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