Closing the AI Skills Gap in the Public Sector: A Review of Upskilling and Reskilling Programmes, Pedagogical Modalities, and Essential Requirements

As Artificial Intelligence (AI) becomes a structural driver of change in public administration, a critical gap persists between the rapid deployment of algorithmic systems and the institutional capacity to govern them responsibly. This paper addresses this tension through a comparative analysis of 70 continuing education programmes in Europe aimed at upskilling and reskilling public sector professionals in AI. It proposes a functional competency framework, grounded in regulatory, technical, and academic sources, which identifies five distinct public sector profiles and maps them across operational, governance, and meta levels. The study uses this framework to evaluate programme coverage, pedagogical modalities, and structural features supporting institutional transformation. Results reveal a widespread focus on digital transformation and regulatory compliance, while competencies in strategic foresight, ethical reasoning, and participatory design remain significantly underrepresented. Programmes combining modular design, blended learning, and competency-based certification show the highest transformative potential. The paper concludes by outlining the principles of a strategic and replicable model for public sector AI training, arguing that effective upskilling requires curricular innovation and sustained organisational infrastructures to translate individual learning into systemic democratic capacity.