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AI4Capacity: Capacity Building and Training for Public Sector Using Artificial Intelligence

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BSB00708

AI4Capacity: Capacity Building and Training for Public Sector Using Artificial Intelligence

Lead partner:

  • Democritus University of Thrace – School of Engineering – Special Account for Research Funds (DUTH) – Greece

Partners:

  • Union of Bulgarian Black Sea Local Authorities (UBBSLA) – Bulgaria
  • Municipality of Topeiros – Greece
  • Catalca District Governorate – Türkiye

 Funded: (Interreg VI-B) NEXT Black Sea Basin Programme; Programme priority: Competent and Resilient Region; ISO6.3: Building up mutual trust, in particular by encouraging people-to-people actions

Duration: 18 months

Total budget: 544.110,00 EUR

Common Challenge

The AI4Capacity project addresses key territorial challenges within the Black Sea region – specifically, disparities in administrative capacity, digital underutilization, and lack of standardized practices through innovative approaches that integrate advanced technology and proven governance frameworks. The project’s solutions are designed to not only tackle these challenges but to also significantly enhance the administrative efficacy and cooperation across participating countries and beyond.

The primary objective of AI4Capacity is to promote and implement capacity-building tools such as the Common Assessment Framework (CAF) and Management by Objectives (MbO) system within small and medium public organizations. By integrating an AI Suite, designed to support these frameworks, the project aims to modernize administrative processes, improve decision-making, and enhance the overall efficiency of public service delivery. The expected change is a significant improvement in the administrative capacities of local authorities, leading to more effective governance, increased transparency, and better service outcomes for the communities they serve.

Main outcomes:

  • AI Suite: A tailored AI Suite will be developed to support the implementation of CAF and MbO. This tool will streamline administrative tasks, provide data-driven insights, and facilitate more efficient resource management.
  • Training: A comprehensive training package will be created and delivered to 32 partners’ staff members. This training will equip them with the skills needed to implement CAF and MbO effectively.
  • Pilot Implementations: The project will conduct pilot implementations of CAF and MbO in four organizations, providing real-world testing and refinement opportunities.
  • Assessment and Refinement: Post-pilot assessments will be conducted to refine the AI Suite based on user feedback and performance data.
  • Expansion and Capitalization: The project will promote the reuse of knowledge and tools developed through regional demonstration events, training courses for 240 public servants, and individualized support for 40 public entities.
  • EduLab Platform: An “EduLab” platform will be established, combining an Open Educational Resource (OER) with a Living Lab to support ongoing education and innovation in public administration.
  • AI4Capacity Network: A transnational network will be created to ensure the durability and transferability of the project’s outputs and results.

Target groups:

  • Local/regional/national public authority
  • Higher education and research organisations
  • General public

AI4Capacity employs a collaborative approach, bringing together partners from GR, BG, and TR to develop, implement, and refine the project’s tools and methodologies. Transnational cooperation is essential for several reasons:

  • Shared Expertise: Partners bring diverse experiences and expertise, enhancing the quality and relevance of the project’s outputs.
  • Cross-Border Challenges: The administrative challenges faced by local authorities in the Black Sea region are similar across borders, necessitating a unified approach.
  • Resource Efficiency: Collaborative efforts allow for the pooling of resources and knowledge, reducing duplication and increasing the project’s impact.

The project’s innovative approach lies in its integration of AI technologies to support traditional management frameworks like CAF and MbO. By leveraging AI, the project introduces advanced data analytics and automation into public administration, a relatively new concept in the region. The creation of the EduLab platform and the establishment of the AI4Capacity Network are also novel, providing sustainable avenues for ongoing education, collaboration, and the dissemination of best practices.

After all the above, it is clear that this project is a significantly efficient investment in the project area organisations. Developed and recognized by the EU, it is considered as the European quality tool for good governance and excellence in the public sector, with a focus on digitalisation, agility, sustainability, diversity and innovation.

(*) CAF is a unique management tool for self-assessment and performance evaluation for public

(**) MbO is a strategic management model that aims to improve the performance of an organization by clearly defining objectives that are agreed to by both management and employees.