Learn about EGI’s role in enabling Artificial Intelligence for scientific research and innovation
EGI for AI in Science
About AI in Science
Artificial Intelligence (AI) is transforming scientific research by enabling new approaches to data analysis, modelling, simulation, and knowledge discovery. From machine learning and computer vision to large language models and AI-powered digital twins, AI technologies are increasingly embedded in scientific workflows across disciplines.
Across Europe, numerous initiatives and projects are advancing AI-enabled science, aiming to improve research efficiency, scalability, and reproducibility while addressing challenges related to access to compute resources, data availability, skills, and responsible use. EGI actively supports these efforts by providing federated infrastructure, platforms, and expertise that allow AI to be applied in a trusted and sustainable way.
Through its participation in European projects and collaboration with research infrastructures, digital infrastructures, and policy initiatives, EGI contributes to strengthening Europe’s AI in Science ecosystem.
EGI Support for AI in Science
The EGI Federation actively supports AI in Science through:
1
1
Technological Solutions
EGI provides federated infrastructure and services that support the full AI lifecycle, from development and model training to deployment, reuse and operation. These solutions enable access to compute, integrate AI workflows with data, and deploy AI-ready platforms and Digital Twin frameworks in a secure and trusted European environment.
EGI’s approach focuses on reuse of existing technologies, portability across infrastructures, and support for both experimental and operational AI workloads. AI-enabled Digital Twins are a key emerging technology supported by EGI, providing interoperable simulation and modelling frameworks for complex scientific systems.
2
2
Policy and Governance Support
EGI contributes to the development of governance, trust, and sustainability frameworks that support responsible and transparent use of AI. This includes alignment with and support for European policies, and integration with openness, FAIRness, and interoperability principles.
Through its coordination and contributions to European projects, EGI helps ensure that AI services for science can evolve from pilots into sustainable, long-term operational solutions. In particular, EGI contributes to the European Strategy for AI in Science including the Resource for AI Science in Europe (RAISE) through its involvement in the SCIANCE project, which supports community-driven identification of AI priorities, strategy for infrastructure upgrades, alignment with policy and ethical frameworks, and the development of a roadmap for sustainable AI adoption in scientific research across Europe.
3
3
AI Landscape Harmonisation
EGI helps create synergies between AI-related projects and initiatives by identifying common needs, promoting reuse of platforms and services, and avoiding fragmentation and duplication of effort.
By acting as a connector between research communities, digital infrastructures, and policy initiatives, EGI contributes to a more coherent and efficient European AI in Science landscape.
4
4
Contribution to Projects
EGI leads or contributes to several European projects that advance AI adoption in science. These projects allow EGI to co-design solutions with research communities, validate them in real use cases, and evolve successful results into sustainable services.
Focus Areas
EGI’s activities for AI in Science focus on:
1
1
Enabling scalable and federated access to AI-ready compute and data
2
2
Supporting AI adoption by research communities through co-design and user support
3
3
Promoting reuse of AI models, workflows, and and Digital Twin frameworks across disciplines
4
4
Aligning AI developments with EOSC, Data Spaces, and European policy initiatives
5
5
Contributing to sustainable governance and long-term operation of AI services
Technological Solutions
EGI services support AI in Science in various ways, including enabling access to AI-ready compute resources, integrating data and AI workflows, supporting collaborative environments, and facilitating reuse of AI models, tools, and Digital Twin frameworks.
Examples include federated cloud, notebook environments, Data Exploitation Platforms, AI model serving, and Digital Twin engines that enable cross-domain simulation and data-driven research.
- Federated access to scalable cloud, HTC and HPC compute resources, including GPU-enabled environments
- Interactive notebook environments for development and reproducible research workflows
- Data Exploitation Platforms (DEPs) integrating AI frameworks with scientific datasets and compute resources
- AI model deployment and serving, for operational inference workflows
- Digital Twin frameworks and engines enabling interoperable simulation and data-driven modelling across domain
- Federated identity and access management enabling secure and trusted access to distributed resources
Our Projects and Initiatives
EGI is involved in a broad portfolio of ongoing and past projects that address AI in Science from different perspectives, ranging from platform development to community adoption and coordination.
- Use Cases
- Projects
