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Grant Details

Grant Analysis

Purpose & Target

  • Objective: Accelerate the adoption of Generative AI (GenAI) in public administrations by supporting three to four pilot projects that develop and apply European GenAI solutions.
  • Target recipients: Consortia led by public administrations (national, regional, or local level).
  • SECTOR-SPECIFIC
  • Geographic scope: Public administrations in EU Member States, EEA-EFTA countries, and countries associated with the Digital Europe Programme.
  • Key filtering criteria: Focus on GenAI applications, public administration context, mandatory consortium structure, requirement for European-developed GenAI solutions, and co-funding commitment.
  • Grant frequency: Part of the Digital Europe Programme Work Programme 2025-2027, suggesting recurring opportunities within the broader program.

Financial Structure

  • EU Funding range per project: EUR 5,000,000 to EUR 7,000,000.
  • Total EU funding for this specific topic (DIGITAL-2025-AI-08-SUPPLY-AI): EUR 21,000,000.
  • Currency: EUR.
  • Funding rate from the EU: 50.0% of eligible costs.
  • Co-financing requirement: 50% of project costs must be provided by project beneficiaries (public administrations) or other public funding (e.g., from Member States' national or regional authorities).
  • Eligible costs include: procurement for fine-tuning foundation models, development of tailored solutions, integration into existing platforms/systems/operational workflows, technical infrastructure, support for skill development and knowledge, and maintenance/optimisation costs for deployed GenAI solutions.

Eligibility Requirements

Eligible Organization Types
  • Lead applicant: Public administrations at national, regional, or local level.
  • Consortium partners: Can include higher education institutions, research and technology organizations, civil-society organizations, and non-governmental organizations.
  • Consortium is required for application.
Geographic Requirements
  • Participating public administrations must be located in EU Member States, EEA-EFTA countries, or countries associated with the Digital Europe Programme.
Financial Requirements
  • A letter of commitment from the Member States or local/regional authorities of the participating public administrations, undertaking to provide 50% co-funding of the respective project costs.
Technical Requirements
  • Demonstrable capacity to successfully integrate and scale up the proposed GenAI models and solutions.
  • GenAI solutions must be based on European models (i.e., models developed by European AI companies/laboratories).
Exclusion Criteria
  • Entities that are part of a successful consortium are ineligible to participate as suppliers in any procurement processes initiated by the public administrations within that same consortium.

Application Process

Application Timeline
  • Submission session available from: 2025-04-15.
  • Application deadline: 2025-10-02 00:00:00+00.
  • The indicative timeline for evaluation and grant agreement is described in section 4 of the call document (not provided in this excerpt).
Submission Materials
  • A comprehensive project proposal, which must include:
    • An overview of the planned GenAI models and solutions and the specific use cases for deployment.
    • An overview of the expected outcomes and benefits.
    • An outline of the consortium's capacity to successfully integrate and scale up the proposed solutions.
  • A letter of commitment from the Member States or local/regional authorities of the participating public administrations, undertaking to provide the required 50% co-funding.
  • Standard application form (DEP) specific to this call, available in the Submission System.
  • A detailed budget table, available in the Submission System.
  • A completed Ethics Self-Assessment.
  • An Ownership control declaration (if applicable).
Submission Process
  • Applications must be submitted online through the Electronic Submission Service via the Funding & Tenders Portal.
  • The application follows a single-stage submission procedure.
Post-Award Responsibilities
  • Successful public administrations within the consortia will be responsible for procuring, developing, and integrating GenAI solutions.
  • Other consortium entities may support activities such as developing procurement specifications, knowledge sharing, capacity building, change management, best practice documentation, and stakeholder engagement.

Evaluation Criteria

Project Quality and Relevance
  • Overview of planned GenAI models and solutions, and the specific use cases where they will be deployed across participating public administrations.
  • Clarity and feasibility of expected outcomes and benefits of the proposed GenAI models and solutions.
Consortium Capacity and Implementation
  • The consortium's demonstrated capacity to successfully integrate and scale up the proposed GenAI models and solutions.
Strategic Alignment and Impact
  • Evidence of EU-added value (prioritized for funding).
  • Alignment with EU values and rules, particularly concerning data protection, explainability, sustainability, and compliance with the EU AI Act.
  • Effectiveness in mitigating cybersecurity risks and ensuring human oversight in critical decisions.
  • Contribution to strengthening core AI capacities and knowledge in the Union by using European models.
Technical Excellence and Replicability
  • Procurement processes must ensure the use of foundation models and systems that align with EU values and rules.
  • Design of procured GenAI solutions to be compatible with various systems and platforms, enabling easier replication across different public administrations.

Compliance & Special Requirements

Regulatory and Ethical Compliance
  • Projects must comply with EU values and rules, particularly regarding data protection and privacy regulations.
  • Strict adherence to the EU AI Act is required for all GenAI solutions.
  • Solutions must ensure explainability, robustness, sustainability, and transparency.
  • Mitigation of cybersecurity risks is mandatory.
  • Human oversight must be maintained for critical decisions.
  • Ethical standards regarding bias must be addressed.
Technical and Operational Requirements
  • GenAI solutions must be based on European models (developed by European AI companies/laboratories).
  • Procured GenAI solutions must be designed for compatibility with various existing systems and platforms used by different public administrations to facilitate replication.
Special Considerations and Strategic Alignment
  • A key element is the replicability of piloted GenAI solutions across various EU public administrations.
  • Prohibition: Entities that are part of a successful consortium are explicitly excluded from participating as suppliers in procurement processes initiated by the public administrations within that consortium.
  • Projects are expected to establish strong links and build synergies with related initiatives such as the Alliance for Language Technologies, open-source European foundational model fine-tuning, sectoral AI & Robotics Testing and Experimentation Facilities, data spaces, EuroHPC initiatives, AI Act implementation actions (e.g., EU AI Innovation Accelerator, regulatory sandboxes, AI Factories), and the future Multi-Country Project on Innovative and Connected Public Administrations.

Grant Details

ai artificial intelligence generative ai genai public administration public sector innovation digital transformation european models digital europe programme ai act data protection cybersecurity pilot projects ai solutions citizen services policy analysis operational efficiency language technologies machine learning european union ai ethics
Apply AI: GenAI for the public administrations
48152746TOPICSen
Digital Europe Programme
PUBLIC UNIVERSITY NGO OTHER
AT BE BG HR CY CZ DK EE FI FR DE GR HU IE IT LV LT LU MT NL PL PT RO SK SI ES SE IS LI NO
OTHER TECHNOLOGY
DEVELOPMENT EARLY_MARKET
OTHER
SDG9 SDG16 SDG11
FUNDING PILOT_PROJECTS CAPACITY_BUILDING INNOVATION_COMMERCIALIZATION OPERATIONAL_SUPPORT
21000000.00
5000000.00
7000000.00
EUR
50.00
Oct. 2, 2025, midnight
None