AI4Gov-X Co-Creation Activities
Co-Creation Activities in AI4Gov-X
Summary of Internal Deliverable MS2
The AI4Gov-X project places co-creation at the centre of its educational design strategy. The internal MS2 report documents how the consortium refined and validated the AI4Gov-X Competence Framework through a structured, participatory process involving public-sector practitioners, students, alumni, civil-society representatives, and domain experts.
Although the full report is restricted, this public summary outlines the main outcomes and methodological approach.
A Participatory Approach to Competence Development
The co-creation process ensured that the competence framework reflects:
- Real needs of public administrations
- Emerging roles in AI-enabled governance
- Practical expectations from professionals
- European reference frameworks and taxonomies
The work combined analytical evidence from WP1 with hands-on validation activities across Europe.
Four Complementary Phases
The refinement process unfolded in four stages:
- Benchmarking and literature review
Identification of gaps in existing training programmes and competence models. - Expansion using European frameworks
Integration of ESCO, DigComp, EntreComp, UNESCO AI competencies, and other sources. - Co-creation sessions and interviews
Workshops in Krems and Brussels, plus targeted interviews with public-sector professionals. - Expert validation
Final consolidation to ensure conceptual coherence and pedagogical feasibility.
A Consolidated Competence Framework
The resulting framework includes:
- 3 domains: Digital Governance, AI & Data, Human-Centric Design
- 16 core competences
- 18 vertical competences grouped into 6 specialisation areas
- 4 levels of autonomy, aligned with EQF descriptors
- A unified structure combining knowledge, abilities, and attitudes
From Competences to Training Architecture
The co-creation work also produced:
- A 60-ECTS training architecture
- A modular structure combining core and specialisation modules
- A progression model supporting multi-level learning
- Delivery scenarios for scalable implementation
These outputs form the foundation for WP3, where the full training programme will be developed.
The AI4Gov-X Competence Framework
The AI4Gov-X Competence Framework is the backbone of the project’s educational programme. It defines the capabilities required for public-sector professionals to navigate AI-enabled transformation responsibly and effectively.
Three Domains of Competence
The framework is organised into three interconnected domains:
- Digital Governance & Transformation
Strategic, organisational, and policy-oriented capabilities. - AI & Data
Technical, analytical, and ethical competencies for AI-driven systems. - Human-Centric Design & Innovation
Skills for participatory design, service innovation, and socio-technical understanding.
Core and Vertical Competences
- 16 core competences form the shared foundation for all learners.
- 18 vertical competences allow specialisation in six thematic areas.
Each competence integrates:
- Knowledge (know-what)
- Abilities (know-how)
- Attitudes (know-why)
Levels of Autonomy
Competences are articulated across four levels of autonomy, aligned with the European Qualifications Framework (EQF). This ensures:
- Clear progression
- Transparent expectations
- Consistency across modules
A Framework Built Through Co-Creation
The framework was shaped through:
- Benchmarking of 70+ programmes
- Computational mapping of ESCO competences
- Co-creation workshops
- Expert validation
It is both academically rigorous and grounded in real public-sector needs.
Methodology Behind the Framework
How the AI4Gov-X Competence Framework Was Built
The framework is the result of a multi-layered methodology combining research, computational analysis, and participatory validation.
- Evidence from Benchmarking
WP1 identified:
- Fragmented training offers
- Limited interdisciplinarity
- Gaps in foresight, ethics, design, and organisational transformation
These insights guided the initial structure.
- Computational Competence Mapping
Using ESCO:
- Thousands of competences were analysed
- Semantic similarity techniques identified relevant clusters
- Network visualisation distinguished core vs. specialised areas
- Participatory Validation
Two co-creation workshops:
- Krems (Sept 2025)
- Brussels (Nov 2025)
Plus interviews with public-sector professionals.
Participants assessed:
- Relevance
- Clarity
- Completeness
- Progression logic
- Expert Review
A final consolidation ensured:
- Conceptual coherence
- Pedagogical feasibility
- Alignment with European frameworks
AI4Gov-X Training Programme Architecture
Training Programme Architecture
The co-creation process produced a structured proposal for the AI4Gov-X training programme.
A 60-ECTS Modular Structure
The programme includes:
- 30 ECTS of core modules
- 15 ECTS of specialisation modules
- 15 ECTS for thesis, transversal activities, and internships
Two Layers of Learning
- Core Layer
Ensures a shared foundation across all domains. - Specialisation Layer
Allows learners to deepen expertise in one of six areas.
Pedagogical Foundations
The programme is designed to:
- Support multi-level progression
- Integrate knowledge, abilities, and attitudes
- Enable flexible delivery formats
- Align with micro-credentialing and ISO 21001 requirements
Delivery Scenarios
The structure supports:
- A unified Master’s programme with specialisations
- Multiple domain-specific Master’s programmes
- Stand-alone modules and micro-credentials
Co-Creation Workshops
Two major co-creation sessions played a central role in validating the competence framework.
Workshop 1 — Krems (3 September 2025)
Participants:
- Public-sector professionals
- Academics
- AI4Gov alumni
Focus:
- Reviewing competence definitions
- Assessing clarity and relevance
- Identifying missing elements
Workshop 2 — Brussels (14 November 2025)
Participants:
- AI4Gov alumni
- Students
- Public-sector representatives
Focus:
- Testing the framework through practical exercises
- Validating autonomy levels
- Refining specialisation areas
Outcomes
The workshops:
- Confirmed the framework’s relevance
- Highlighted areas for refinement
- Strengthened alignment with real-world needs
Stakeholder Interviews
Interviews with public-sector professionals provided grounded insights into:
- Competence gaps
- Organisational challenges
- Training needs
- Expectations for AI-enabled transformation
Key Themes Identified
- Need for anticipatory governance
- Importance of socio-technical understanding
- Demand for practical, applied learning
- Relevance of ethical and regulatory competences
These insights directly shaped the final competence catalogue.
Internal Mapping of Partners’ Training Offers
Mapping of Partners’ Training Offers
The consortium conducted an internal survey to assess:
- Existing training modules
- Coverage of the competence framework
- Delivery formats and languages
- Readiness for micro-credential integration
Findings
- Strong coverage in AI and data
- Gaps in design, foresight, and organisational transformation
- High potential for modular integration
- Opportunities for shared delivery models
This mapping supports WP3 implementation and long-term sustainability.