An internal survey of the AI4Gov-X project reveals a varying accreditation landscape of AI and public governance education programs in the EU, identifies opportunities for extra-project outreach for AI-education capacity building and marks training gaps and resource disparities as challenges to the project. Artificial intelligence, education, digital transformation, public governance ∗Corresponding author. †These authors contributed equally.
The AI4Gov Accelerate project (AI4Gov-X) unites educators and experts from over 20 EU countries to
foster talent and share best practices of AI-specific digital transition in public governance [
The project intends to extend its geographic boundaries beyond the countries that the consortium represents, but also beyond the EU. The survey inquired as to which countries could each partner cover for training provision, stakeholder engagement, or strategic outreach, considering linguistic and
CEUR Workshop
ISSN1613-0073 regional proximity and institutional relations. The results illustrate a consortium with the capacity to reach into a variety of administrative cultures, legal traditions, and public governance contexts.
While the relevant teaching portfolio is strong in general, the survey identified some gaps in the oferings. Interdisciplinary trainings that integrate legal, ethical and technical aspects, are scarce. Training programs are mostly academic, there are few options that focus on practice. There is a lack of programs that target the professional further education of civil servants and legal practitioners. A regional disparity is identified: Western European nations are better served by relevant program than their Eastern European counterparts. The survey uncovered a strong interest of the project partners in developing tools and programs that address these gaps.
The survey identified unequal access to research datasets, public sector AI case studies, and proprietary learning platforms, as a recurring issue, potentially limiting institutions’ participation in content co-creation. To ensure balanced participation, the consortium should develop shared access arrangements for key datasets, promote the use of open-access resources, and consider centralizing specific infrastructure components.
The information, documentation and figures in this poster publication are written by the AI4Gov-X consortium under EC grant agreement number 101190043. Views and opinions expressed are however those of the authors only and do not necessarily reflect those of the European Union or of the European Health and Digital Executive Agency (HADEA). Neither the EU nor the granting authority can be held responsible for them. The project is co-funded by the FFG (https://www.fg.at).
The authors have not employed any Generative AI tools.