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Facilitated cooperation for AI in Science (CSA)

European Commission

Expected Outcome:

Projects are expected to contribute to the following outcomes:

Identify the long-term research challenges where AI can make a meaningful breakthrough contributing to EU’s competitive edge in selected scientific disciplines/areas, through a Strategic Research and Innovation Agenda.
Provide evidence to structure the resources for AI in Science at European level, as a feasibility test towards potential R&I initiatives beyond the CSA that could optimise access to relevant data, infrastructure and talent across different scientific domains for more and better AI-enabled research.
Coordinate, strengthen the network and raise awareness and a community of scientists, including citizen scientists, research organisations and stakeholders towards new paradigms of research with AI.

Scope:

Artificial intelligence is a game-changer for science and innovation, and promises significant opportunities to boost the European competitive edge in R&I that need to be capitalised on. The aim of the CSA is to structure AI-enabled research in Europe and assess options towards optimising the ecosystem for AI in Science in Europe, through a Strategic Research & Innovation Agenda and assessing the potential for possible future R&I initiative(s), in line with the recommendations of the Scientific Advice Mechanism[1], and the European Commission President’s political guidelines, for the setting up of an AI Research Council[2]..

The project should develop a Strategic Research and Innovation Agenda for AI in Science by mobilising large groups of domain and AI researchers in different fields to identify key long-term research challenges in a diverse range of scientific areas where AI can make a meaningful difference for scientific breakthroughs, which are compelling to the EU competitive, environmental and social policy agenda. The project should come up with pilot areas from across Horizon Europe Pillar II Clusters, building on Europe’s competitive advantages in science and AI technologies. The research challenges should be related to prediction and design problems in the different scientific fields identified that could be solved with AI.

The SRIA should also include areas where AI can improve generic scientific tasks e.g virtual research assistant / tools for literature-based discovery, for improving / enabling research workflows, lab automation and collaborative human-AI work in science. Research priority areas involving the use of models based on frugal AI, which are more compact, more efficient and less energy intensive, as well as human-centric and trustworthy AI for scientific work should also be explored.

The project should build evidence and assess the needs and potential for R&I initiatives for AI in Science beyond the CSA, in an effort to identify ways to improve the EU landscape for support for AI in Science, to be discussed and agreed upon with the Commission and the Member States. The assessment should identify the ways for improving data access, infrastructure and support services, as well as skills and talent-related needs to boost the integration of AI in different fields of science at larger scale in Europe in research processes and lab automation, while promoting reproducibility, transparency and open science. It should also identify options for EU to better enable cooperative development and sharing of AI models for scientific discovery across different scientific fields. It should also take into account existing EU efforts to support access to data, research infrastructures, networks, HPC.

Different scenarios of R&I initiatives and infrastructure improvements should be prototyped together with a diverse range of users and stakeholders from the research community, industry, start-ups, civil society and policy-maker communities. Based on the feasibility test results, the project should develop a roadmap on the needed steps for a more effective coordination between the domain and AI scientific communities in Europe and the needed upgrades in service and infrastructure provision at EU level for the integration of AI in different scientific fields, including research processes engaging citizens and civil society, e.g. Citizen Science.

The proposals should also provide coordination and dissemination for interdisciplinary AI-enabled science to facilitate stakeholder engagement, coordination and promotion of AI in Science initiatives across Europe. The CSA should develop a website, organise awareness raising events for the benefits of AI in Science and create opportunities for exchanging on good practices.

Projects should build on or seek collaboration with existing projects and develop synergies with other relevant European, national or regional initiatives, funding programmes and platforms, in particular with EU-level initiatives such as EOSC[3],EuroHPC Joint Untedtaking[4], ESFRI,[5]AI Factories,[6] the EU AI, Data and Robotics Partnership,[7]AI4EOSC[8] the AI on Demand Platform[9] and the GenAI4EU Central Hub.

AI Based Application Success Predictor

🧪 1. Scientific Excellence Is Paramount

For ERC grants, excellence is the sole selection criterion—evaluations focus exclusively on the quality of the research and track record .

Peer-reviewers adhere strictly to predefined criteria (e.g., Horizon ITN evaluations), and weaknesses—rather than strengths—often decide the outcome .

🌍 2. Strategic Alignment with EU Priorities

Horizon Europe emphasizes Green & Digital Transitions and resilience, with specific budget steering across biodiversity, climate, digital, and societal missions .

Proposals that clearly align with these strategic orientations and EU missions are significantly more competitive.

🤝 3. Strong, Diverse European Consortia

Horizon projects demand well-balanced consortia across Europe—geographically and disciplinarily diverse, including academia, industry, SMEs, NGOs .

Effective leadership, communication, trust, and active collaboration are key success factors.

🧴 4. Proven Research Infrastructure & Track Record

A strong publication record—especially in high-impact venues—and prior grant awards bolster chances .

ERC starting, consolidator, or advanced grants require exceptional citation records, strong proposals, and investigator track records .

📈 5. Robust Project Management

For large collaborative grants, project coordination, administration, and communication are just as crucial as scientific content .

Demonstrating realistic budget planning (100% direct costs + 25% indirect costs), administrative frameworks, and governance structures strengthens proposals .

💼 6. Fostering Mobility & Career Growth

Marie Skłodowska-Curie fellowships emphasize researcher mobility, interdisciplinary training, and developing future talent .

🧷 7. Geographical & Gender Equity

Northern and certain Eastern European institutions currently have higher success rates (≈22% vs below 18% in Southern Europe) .

ERC gender data: male and female applicants have similar success rates, though male applicants apply more frequently .

📌 Key Takeaways

Factor	Why It Matters
Excellence-first	Superior science and investigator record are non-negotiable.
Strategic fit	Alignment with EU green, digital, and mission goals is essential.
Consortium quality	Geographic, sectoral, and expertise balance enhances impact.
Management capacity	Good PM builds confidence in successful delivery.
Experience track record	Publications, previous funding, and citations build credibility.
Mobility & careers	MSCA focuses on researcher development and interdisciplinary collaboration.

🧭 Applicant Tips

Master criteria & avoid weaknesses: Make sure your proposal addresses common reviewer pitfalls—methodology, innovation, budget clarity.

Map to EU priorities: Explicitly connect your objectives to Horizon Europe’s strategic plan (2025–2027).

Build strong consortia early: Prioritize complementary expertise, geography, gender balance, and partner roles.

Show robust project management: Include a Work Package structure, governance plans, and clear communication strategies.

Leverage your track record: Highlight high-impact papers, leadership in projects, and previous awards.

Consider MSCA opportunities: Use them for mobility grants or integrating training into your project.

✅ In Summary

To maximize success with European Commission grants—especially ERC or Horizon Europe—focus relentlessly on scientific excellence, strategic EU alignment, consortium strength, and solid project planning. Combine these with a strong publication record and researcher development elements, and aim to close off any potential reviewer concerns.

Specialties

Artificial Intelligence

Eligibility Requirements

General conditions

1. Admissibility Conditions: Proposal page limit and layout

described in Annex A and Annex E of the Horizon Europe Work Programme General Annexes.

Proposal page limits and layout: described in Part B of the Application Form available in the Submission System.

2. Eligible Countries

described in Annex B of the Work Programme General Annexes.

A number of non-EU/non-Associated Countries that are not automatically eligible for funding have made specific provisions for making funding available for their participants in Horizon Europe projects

Sponsor Details

Sponsor Institute/Organizations: European Commission

Sponsor Type: Corporate/Non-Profit

Address: Rue de la Loi 200, 1040 Bruxelles, Belgium

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