Challenge-Driven GenAI4EU Booster (RIA) (AI/Data/Robotics Partnership) -

Project results are expected to contribute to all of the following expected outcomes:

• Significant technology progress and innovation through challenge-driven approach in the fields of aerospace, pharma/drug development or telecommunication networks.
• Increased competitivity and visibility of the Generative AI community in Europe, in demonstrating their capability to achieve challenging tasks within the aerospace, pharma/drug development or telecommunication sectors.
• Increased adoption of Generative AI in aerospace, pharma/drug development or telecommunication networks through tangible progress and achievement demonstrated via the challenge-driven process.

Generative AI (GenAI) promises to transform most industry sectors. This challenge-driven initiative aims to boost both Europe’s developer community and the adoption of powerful trustworthy generative AI solutions in the strategic sectors of aerospace, pharma/drugs and telecommunication networks, key for their competitiveness. In pharmaceuticals, it can, for instance, accelerates drug design by rapidly creating target-specific molecules, reducing development time from years to seconds, and potentially preventing prolonged health crises like COVID-19. In aerospace, generative AI can for instance optimize aircraft design, streamline manufacturing processes, predict maintenance needs through sensor data analysis, route optimisation, and enhance pilot training with diverse, realistic simulations. By embracing generative AI, telecom companies can position themselves at the forefront of a new era of intelligent and automated telecommunications. Specific use-cases include for instance network management, network optimization, network slicing, network healing, predictive maintenance, network mapping and optimization.

Each proposal should focus exclusively on one of the three key sectors mentioned above: aerospace, pharma/drug development, or telecommunications and clearly specify which sector it addresses. Each proposal is expected to focus primarily on the definition, the organization of a multi-stage competition in the chosen sector, as well as the accompanying support to the companies/teams taking part in the challenges, and related activities to maximise the impact of the action.

User industry companies from the strategic sector targeted by the proposal should be core partners in the consortium. They should demonstrate a genuine interest in the projects results and therefore support the challenge participants - in order to reach the most powerful and exploitable results benefitting their industry. The expected results are pre-competitive but the proposal must include a draft exploitation plan outlining commitments on future exploitation. The consortium is responsible for the various stages of the challenges and should provide the necessary support resources during each stage of the competition, including technical assistance and business support to develop an exploitation strategy, but most importantly, provide the data necessary to fine-tune models and build powerful solutions meeting industry needs.

Proposals should be driven by impactful use-cases where generative AI can make the difference: a number of industries from the targeted sector are expected to join forces to define challenging problems to solve with GenAI solutions, which then drive the rest of the project. Based on such challenges, the consortium organises a multi-staged competition with an increasing level of complexity. In the first two stages, third parties, either single companies (typically start-ups or SMEs) or small team of organisations built around such start-ups/SMEs, compete to address the challenges with GenAI solutions. After these stages, the solutions retained for the last stage will be invited to join the consortium, as full beneficiaries.

For each proposal:

• Stage 1: a challenge, open to all, will allow to select for stage 2 the 20 highest ranked solutions, according to a pre-defined selection process and criteria. Each solution competing for the challenge can be submitted either by a single start-up/SME, developer of GenAI solutions, or a small team of organisations built around such start-up/SME
• Stage 2: the 20 solutions selected from stage 1 receive EUR 250 000 FSTP funding, in form of a grant, in order to address the challenge set for this stage by the consortium. At the end of stage 2, the 4 highest ranked competing solutions will be selected for the next stage according to a pre-defined selection process and criteria.
• Stage 3: after the end of stage 2 and the corresponding FSTP scheme, the 4 selected solutions will be invited to join the consortium and receive EUR 2 millions grants each (as part of the eligible costs of the grant agreement) to prepare for the grand finale. The consortium should define measures to maximise the impact for the team winning the grand finale at the end of the third stage, and maximise the uptake of their solutions (for instance, the best performing team could be offered the opportunity to conclude partnerships or contracts with the user industries leading the consortium. Measures to support the broad uptake of their solutions in the whole sector should also be considered).

Such multi-staged scheme is expected to be implemented in parallel by the successful proposals, each addressing a different sector.

Each proposal, involving several major industry players, should define a clear methodology to implement the various steps of the approach, define the specifications of the stages of the competitions, timelines, targets, KPIs, a solid evaluation methodology including evaluation criteria. The main information should be in the proposal, even if refinements could be further developed during the project. The proposers will also be in charge of implementing the evaluation methodology, and providing the necessary infrastructure/technical support for the participants to the challenges. The consortium members are also responsible for ensuring high visibility of the competitions, including possible sponsorships.

The actions selected from this call, each addressing one of the three targeted sectors, are expected to collaborate among themselves, in order to make economies of scale in sharing best practices, defining processes for organising the challenges, ensuring efficient monitoring, organising dissemination and communication activities, etc. Such collaboration among the linked actions is expected to be formalised by a collaboration agreement, after the Grant Agreement signature.

For each proposal, an amount of EUR 5 millions is foreseen to be distributed among the winners of stage 1, in form of FSTP grants, in order to prepare for stage 2. In addition, a budget of EUR 8 millions is reserved in the initial grant, to carry out the stage 3 of the challenge. The proposal is expected to make the case for such investment in defining the objectives with sufficient level of information, even if the details are to be further elaborated in the course of the project. Such amount will be distributed equally among the 4 winning teams of the stage 2, who will be invited to join the consortium as beneficiaries to develop further the solutions and compete for the stage 3 of the challenge.

Visibility would be important; therefore dissemination and communication campaigns are key. The proposers are also encouraged to seek sponsorship, which would be key for the visibility and prestige of their challenge, and to attract the best developers from the EU and associated countries to compete, particularly SMEs and startups, alone or within a team competing for the challenges.

All proposals are expected to incorporate mechanisms for assessing and demonstrating progress, including qualitative and quantitative KPIs, benchmarking, and progress monitoring. This should include the methodology to accompany the challenge participants to the various stages during the project, and the assessment methodology during the various selection stages. As part of the KPIs, efficiency gains from Generative AI should be considered, to maximize broader impact.

When possible, proposals should build on and reuse public results from relevant previous funded actions. Communicable results should be shared with the European R&D community through the AI-on-demand platform, and if necessary, other relevant digital resource platforms to bolster the European AI, Data, and Robotics ecosystem by disseminating results and best practices.

This topic implements the co-programmed European Partnership on AI, data and robotics (ADRA), and all proposals are expected to allocate tasks for cohesion activities with ADRA and the CSA HORIZON-CL4-2025-03-HUMAN-18: GenAI4EU central Hub.

Proposals should also build on or seek collaboration with relevant projects[1] and develop synergies with other relevant International, European, national or regional initiatives.

[1] In particular, proposals in telecommunication should exploit potential synergies with projects funded under HORIZON-CL4-2025-03-DATA-08, HORIZON-CL4-2025-03-DATA-09 and HORIZON-CL4-2025-04-DATA-02; proposals in pharma/drug should exploit potential synergies with relevant projects from Cluster 1 and IHI Innovative Health Initiative; proposals in the aerospace should exploit potential synergies with relevant projects from the clean aviation JU and other similar projects/initiatives.

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