COMMUNICATION FROM THE COMMISSION TO THE EUROPEAN PARLIAMENT AND THE COUNCIL A European Strategy for Artificial Intelligence in Science Paving the way for the Resource for AI Science in Europe (RAISE)
Date: 2025-10-08
Institutions: Directorate-General for Research and Innovation, European Commission
Subjects: EU strategy, artificial intelligence, data processing, digital literacy, high-performance computing, innovation, research and development, scientific cooperation, scientific research

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  EN 

   EUROPEAN COMMISSION  Brussels, 8.10.2025  COM(2025) 724 final  COMMUNICATION FROM THE COMMISSION TO THE EUROPEAN PARLIAMENT AND THE COUNCIL A European Strategy for Artificial Intelligence in Science           Paving the way for the Resource for AI Science in Europe (RAISE)  
 
 
A European Strategy for Artificial Intelligence in Science  
Paving the way for the Resource for AI Science in Europe (RAISE) 

1. 

INTRODUCTION  

Science  has  been  a  driving  force  for  building  prosperity  in  Europe.  Today,  artificial 
intelligence (AI) is profoundly transforming the way scientific research is conducted, 
from assisting with literature reviews to automating lab experiments1. Scientists are using 
AI to tackle complex scientific problems and make faster and more disruptive innovations 
in all disciplines2. In biology, the AI tool AlphaFold earned its creators the 2024 Nobel 
prize in  chemistry  and  is  used by  two million  researchers. This achievement  was made 
possible thanks to collaboration with the European Molecular Biology Laboratory (EMBL) 
that  provided  the  high-quality  experimental  data3  required.  In  astronomy,  a  European 
project found over 70 free floating planets among millions of unrelated stars using machine 
learning algorithms4. 

Europe’s researchers were among the first to integrate AI in their work and, until 2017, 
were leading in terms of number of scientific publications using AI applications. However, 
China  and  the  US  have  since  caught  up  and overtaken  the  EU,  with  China  leading 
globally5. The EU’s global share of AI computational capacity is less than 5%, compared 
to  the  75%  for  the  US  and  15%  for  China6.  Europe  remains  a  major  hub  for  basic  AI 
research, reflecting the continent's active AI research community. However, the EU has a 
small global share of AI players (6%) compared to the US and China, and an even smaller 
share of AI patents (3%)7. 

Countries like the US, China, Japan and the UK are investing heavily in AI in science 
and  the  required  resources,  such  as  computational  power  and  datasets.  They  have 
launched national AI in  science initiatives to boost their scientific ecosystems and their 
economies, gain and maintain technological sovereignty, protect their national security and 
increase their political influence8. Similarly, major tech companies identify AI in science 
as a strategic area with high growth potential, establishing internal AI in science teams and 
partnering with top research institutions. 

A  European  approach  to  AI  in  science  is  required  for  Europe  to  strengthen  its 
economic position and competitiveness, in an extremely dynamic context in which AI is 
reshaping our societies and economies, including the scientific community. Several major 
reports9,10  have  recommended  leveraging  AI  to  close  the  innovation  gap  and  boost 
productivity and prosperity. The EU must step up its ambition and pursue a strategic and 
coordinated  approach  to  AI  in  science  and  science  in  AI  to  become  an  AI  Continent11, 
pushing the frontiers of AI while respecting and enhancing its values.  

(1)  Successful and timely uptake of artificial intelligence in science in the EU, Berlin: SAPEA 2024  
(2)  Working paper, ‘Artificial intelligence in science Promises or perils for creativity?’  
(3)  "AlphaFold uses open data and AI to discover the 3D protein universe", EMBL  
(4)  COSMIC-DANCE project, https://cordis.europa.eu/project/id/682903  
(5)  Working paper, ‘Trends in the use of AI in science’, https://data.europa.eu/doi/10.2777/418191  
(6)  AI computational capacity with specialised chips (GPUs, TPUs,…) as defined in Pilz et al, 2025 
(7)  “The Role of Artificial Intelligence in Scientific Research – A Science for Policy, European Perspective” 

Publications Office of the European Union, Luxembourg, 2025, JRC143482, DOI: 10.2760/7217497. 

(8)   US; China; Japan; UK 
(9) The future of European competitiveness – A competitiveness strategy for Europe  
(10) Much more than a market - Speed, Security, Solidarity 
(11)  AI Continent Action Plan, COM(2025) 165 final  

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The EU can lead the way, building on its unique strengths in excellent research across 
domains and in trustworthy AI. Europe can take advantage of a long-standing academic 
tradition  and  respect  for  research  freedom,  with  world-class  scientists  and  research 
facilities  that  collaborate  to  push  technological  boundaries,  supported  by  sustained 
funding.  To  lead  in  AI  in  science,  Europe  must  develop  AI  solutions  that  ensure 
technological  sovereignty,  both  by  advancing  AI  tools  for  scientific  research  and  by 
facilitating critical scientific breakthroughs. A European approach to a safe, sustainable, 
human-centric  and  trustworthy  AI  in  science  is  a  strategic  opportunity  in  the  rapidly 
changing geopolitical environment. 

This  European  Strategy  for  Artificial  Intelligence  in  Science  (the  ‘Strategy’)  presents  a 
distinctly European approach to accelerate the adoption of AI by European scientists 
in  all  disciplines.  It  includes  building  leading  European  AI  scientific  models  and 
supporting  their  innovative  potential  to  boost  the  impact,  quality  and  productivity  of 
science12. A science for policy report by the Joint Research Centre (JRC) accompanies this 
Communication, providing a detailed analysis of the use of AI in the scientific process and 
the landscape of AI in science13. It is adopted alongside, and complements, the Apply AI 
Strategy  which  focuses  on  boosting  AI  adoption  to  enhance  the  EU's  competitiveness, 
particularly in strategic industries. 

The  initial  actions  of  this  Strategy  will  primarily  be  financed  through  Horizon 
Europe. Since 2021,  Horizon Europe  has  already  supported AI with  more than EUR 8 
billion14  in  funding.  To  drive  progress  and  affirm  Europe’s  position  at  the  forefront  of 
scientific  innovation,  the  Commission  will  aim  to  provide  significant  and  dedicated 
financial support under the next Multiannual Financial Framework (MFF). 

The EU needs to address the key challenges faced by the European R&I ecosystem, namely 
the fragmentation of resources and research efforts, difficulties in accessing computational 
resources and datasets, and the global competition for top AI and scientific talent. To this 
end, the Strategy develops the foundations of a Resource for AI Science in Europe 
(RAISE) as a virtual institute that pools excellent talent, compute, data and research 
funding for AI. It will advance core AI capabilities through sustained support for basic 
research,  addressing  the  limitations  of  AI  and  ensuring  robust,  safe  and  trustworthy  AI 
development. It will expand the tools available to scientists across disciplines and reinforce 
Europe’s position as a key player in the global scientific landscape. 

(12)  This strategy is informed by the recommendations of the Commission’s Scientific Advice Mechanism. 
(13)  “The Role of Artificial Intelligence in Scientific Research – A Science for Policy, European Perspective” 

Publications Office of the European Union, Luxembourg, 2025, JRC143482, DOI: 10.2760/7217497. 

(14)  EUR 6.4 billion for 2021-24 and more than EUR 1.6 billion in the Work Programme 2025 

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2.  RAISE: THE RESOURCE FOR AI SCIENCE IN EUROPE 

RAISE  will  be  launched  as  a  virtual  European  institute  that  pools,  aligns  and 
coordinates essential AI resources, including computational power, data, excellence and 
talent, and research funding, across the EU, Member States and private sector. RAISE will 
pursue two complementary and mutually supportive objectives: promoting cutting-edge 
research in AI (science for AI) as well as the uptake of AI for scientific progress across 
disciplines  (AI  in  science)15.  These  objectives  embody  the  European  approach  to  AI 
science,  based  on  catalysing  close  interdisciplinary  collaborations  between  the  best 
scientists in Europe, coming together from different disciplines and perspectives to carry 
out excellent research with and on AI. Fostering this collaborative interdisciplinary culture 
is necessary to reduce fragmentation of research efforts and reach a critical mass. This is 
essential to push the boundaries of science and to develop the next generation of AI, as 
proposed in the future Horizon Europe moonshot16. RAISE will thus ensure that European 
science is at the forefront of global AI developments and that new breakthroughs in AI 
capabilities will empower European research to achieve significant advancements across 
multiple scientific disciplines.  

RAISE is founded on the unique strengths and values of European research and a 
distinctive  EU  approach  to  AI.  RAISE  will  support  the  development  of  AI  systems 
beyond the current state of the art, that are ethical, explainable, transparent, accountable, 
reliable,  safe,  human-centric  and  aligned  with  human  rights  and  societal  values.  The 
application of these models in scientific research will help mitigate the current limitations 
and risks of AI and maintain the integrity and transparency of scientific knowledge, thus 
preserving the credibility of science and increasing confidence in AI-driven science17.This 
collaborative  culture  and  interdisciplinarity  is  necessary  to  reduce  the  fragmentation  of 
research efforts and reach critical mass.  

(15)  Advancing both science for AI and AI in science in close interaction has been successfully  applied in 
both  public  and  private  contexts  (e.g.  CNRS  AISSAI,  Google  DeepMind).  Different  approaches  to 
pooling AI resources for science exist globally but are limited to data and compute, e.g. NAIRR (USA). 
(16)  Proposal for a Regulation establishing Horizon Europe for the period 2028-2034, COM(2025) 543 final  
(17)  Only 38% of Europeans trust scientific discoveries with AI according to the Eurobarometer. 

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RAISE by and for scientists 

RAISE  will  first  and  foremost  build  a  dynamic  research  community,  in  which 
scientists in Europe will both advance AI technologies and apply them to the toughest 
scientific and technological challenges. RAISE will raise the visibility of European AI and 
AI  in  science  research,  strengthening  collaborations  among  leading  institutes  and 
promoting world-class developments in the field. 

At the heart of the RAISE community will be Thematic Networks of Excellence in AI 
in science and the European Network of Frontier AI Labs. Every Network will group 
leading  researchers  working  with  AI  in  a  specific  scientific  discipline  or  advancing  AI 
capabilities, building a focal point of European excellence in that area. The Networks will 
have access to the AI resources they need. This means not only targeted and sufficiently 
long-term funding but also access to the EU’s computational power and datasets, at a scale 
that can only be coordinated at EU level. Through exchanges within and among networks 
and  coordination  across  all  areas,  RAISE  will  reduce  fragmentation  and  better  align 
research efforts.  

RAISE will spread excellence in AI science throughout Europe by supporting training 
activities for scientists and other academic staff, as well as fellowships, doctoral networks 
and mobility schemes. Through the lively circulation of talent and ideas, the discoveries 
made with the help of RAISE will be available for all scientists to build on. RAISE will 
support  scientists  in  translating  their  most  promising  scientific  and  technological 
breakthroughs  into  real-world  applications  and  new  products  and  solutions,  laying  the 
groundwork for rapid industrial uptake and future competitiveness. To this end, RAISE 
will  closely  cooperate  with  AI  Factories  and  AI  Gigafactories  and  private  sector  and 
industrial partners.  

RAISE for Materials Science 

As  an  example,  a  Thematic  Network  of  Excellence  for  materials  science  will 
bring together excellent research labs deploying AI to analyse, discover and test 
materials, including in industrial settings. Through collaborative research efforts 
and aligned research agendas, facilitated through advanced sharing of data and results (folowing 
standards defined in the Materials Commons), access to dedicated AI infrastructure and data 
management services, the network will advance the state of the art in this field. AI-ready data 
sets,  foundation  models  in  materials  science  and  automated  laboratories  will  equip  the 
community  with  powerful  tools  that  facilitate  the  simulation,  design,  synthesis  and 
manufacturing of advanced materials.  

The development of these tools will bring forward innovative AI techniques, while also paving 
the  way  for  game-changing  innovations  based  on  safer  and  renewable  or  low-  carbon  based 
materials, materials for quantum technology and energy, including high-performance batteries, 
photovoltaics, fuel cells, carbon capture materials and more. European spin-offs and startups 
will  capitalise  on  these  results,  both  in  materials  and  in  AI  technologies,  and  benefit  from 
possible  regulatory  sandboxes.  The  gained  scientific expertise  and  excellence  will  be  spread 

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through  events,  fellowships  and  mobility  schemes,  further  enlarging  the  pool  of  European 
excellence in AI-based materials science.  

Building RAISE 

To accommodate the fast-paced changes in innovations and the shifting needs of the AI 
science ecosystem, RAISE will be built using a phased approach, that can grow as its 
partners, resources, contributions and needs evolve. The Commission will first launch the 
initial elements of a pilot phase under the Horizon Europe and Digital Europe programmes. 
To build RAISE and ensure its longer-term sustainability, both in terms of governance and 
pooled resources, the Commission will work with Member States, research stakeholders, 
including  higher  education  institutions,  and  the  private  sector,  with  a  view  to  further 
develop RAISE under the new MFF. 

An  appropriate  governance  structure  will  ensure  close  interconnection  and 
collaboration  between  RAISE’s  different  components  and  Thematic  Networks  of 
Excellence. It will ensure proper representation of both science for AI and AI in science 
communities, of Member States (linking directly to the AI Board18) and the private sector, 
including  AI  startups  and  scaleups.  A  high-level  academic  advisory  board  can  provide 
scientific guidance. Initially, a secretariat will be established via Coordination and Support 
Actions under Horizon Europe to ensure the symbiosis of RAISE elements. It will also 
link, use and directly inform the activities of the Apply AI Alliance introduced in the Apply 
AI Strategy. 

To establish RAISE as an engine for AI scientific excellence in Europe, and to enable and 
support AI in science in Europe more generally, the Commission will implement an action 
plan, targeting key aspects of the AI in science practice and ecosystem, including actions 
relating to excellence and talent, computational power, data, research funding, as well 
as coordination and collaboration. 

The Commission will: 

• 

launch the RAISE pilot with EU 108 million funding under Horizon Europe 
WP 2026-27, during the first edition of the AI in Science Summit in 
Copenhagen on 3-4 November 2025, under the Danish Presidency of the 
Council of the EU. 

•  establish initial RAISE coordination for AI in science through a Coordination 

and Support Action (CSA) under Horizon Europe (WP 2025).  
•  partner with Member States and the private sector to build RAISE.  
•  establish a high-level RAISE academic advisory board. 

(18)  established in the AI Act. 

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3.  AI IN SCIENCE ACTION PLAN: BUILDING THE WAY TO RAISE 

3.1.  Excellence and talent 

Excellence 

The European approach to AI is rooted in excellence and trustworthiness. A continued 
focus on excellence will be essential for the EU to develop AI models to solve complex 
scientific  problems,  as  exemplified  in  the  RAISE  Thematic  Networks  of  Excellence, 
ensuring EU’s scientific leadership and competitiveness.  

Excellent  research  with  AI  requires  AI  solutions  which  are  human-centric, 
explainable, unbiased and safe. This means addressing, from the start all issues that are 
related to the technology, from accuracy and reliability to ethical concerns19 and research 
integrity challenges. According to one survey20, 81% of researchers have concerns relating 
to AI models (ethics, accuracy, security/privacy, and/or lack of transparency) and 63% to 
the lack of guidelines, hindering the adoption of AI. To facilitate the responsible uptake of 
the  technology,  guidelines  and  support  are  fundamental  for  the  scientific  and  academic 
community. The Commission has a long-standing tradition of addressing ethical concerns 
under  Horizon  Europe,  through  ethics  appraisal  frameworks  for  research  with  AI  and 
operational guidelines21. The Commission will continue to promote the “ethics by design” 
approach and develop different resources with the scientific community (training, tools, 
etc.). In addition, the European Group on Ethics in Science and New Technologies (EGE) 
will be asked to deliver an opinion on AI in science. 

Since  the  use  of  generative  AI  has  become  widespread,  issues  such  as  unverified  text 
fragments in papers, fabricated citations, or plagiarism, have become more common. The 
Commission  will  regularly  update  the  Living  guidelines  on  the  responsible  use  of 
generative AI in research22, a successful example of practical and actionable guidelines 
that were co-developed with European Research Area (ERA) members (countries and R&I 
stakeholders) to respond to emergent challenges in the community. 

The  Joint  Research  Centre  will  support  the  strategic  advancement  of  trustworthy 
and reliable AI for science in close collaboration with the European AI Office. This 
may include assessing the current landscape of scientific AI models23 through qualitative 
and quantitative methods, focusing on capabilities, evaluation practices, benchmarks, and 

(19)  https://digital-strategy.ec.europa.eu/en/library/ethics-guidelines-trustworthy-ai  
(20)  https://www.wiley.com/en-de/ai-study/for-researchers    
(21) Ethics By Design and Ethics of Use Approaches for AI, guidance for Horizon Europe  
(22) Living guidelines for the use of generative AI in research  
(23)  Article 2(6) AI Act (Regulation (EU) 2024/1689) 

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possibly developing EU-centric metrics to evaluate their performance and trustworthiness 
in scientific research.  

Talent 

Europe  is  home  to  world-class  research  groups  and  organisations  across  disciplines, 
offering  a  strong  foundation  to  foster  a  critical  mass  of  talent  and  ideas.  By  enhancing 
connectivity, collaboration and leadership across these groups, they can scale to address 
more complex scientific questions using AI. Interdisciplinary collaborations are crucial 
to developing and using cutting-edge AI in solving scientific problems 24. 

The EU needs to enlarge the pool of scientific talent with strong AI knowledge and 
skills. As stated in the Union of Skills25, the EU’s prosperity depends on its skilled human 
capital, including to strengthen its position in research and innovation, and in AI in science 
in  particular.  Not  only  must  Europe  train  the  next  generation  of  scientists  and  upskill 
current scientists to be AI-ready, it must also retain this talent and become an attractive 
beacon for global interdisciplinary talent in AI and its scientific applications. Moreover, 
given that the development of advanced uses of AI in science requires interdisciplinary 
research  teams,  the  EU  also  needs  to  support  other  types  of  profiles,  such  as  research 
engineers  and  data  stewards,  who  follow  different  career  paths,  in  line  with  Apply  AI 
Strategy’s  goal  of  developing  hybrid  profiles  (e.g.  AI  specialists  with  industry-specific 
expertise).  This  ambition  also  requires  targeted  efforts  to  strengthen  inclusiveness  and 
gender balance in AI, where structural inequalities persist26. 

AI skills will be increasingly important for researchers and must be developed early on 
across all disciplines and career stages. As announced in the AI Continent Action Plan, the 
Commission is already promoting the development of AI and digital skills, including AI 
literacy and advanced AI skills27, through the Digital Education Action Plan28, the AI Skills 
Academy, the STEM Education Strategic Plan29, and other education, training and skills 
development instruments30. It will continue to do so with the 2030 Roadmap on the future 
of digital education and skills, through its dedicated AI dimension. These initiatives are 
available  for  researchers  to  take  advantage  of  AI.  To  further  increase  researchers’ 
awareness of AI literacy as an essential skill, the Commission will update the European 
Competence  Frameworks  for  Researchers  (ResearchComp31)  and  launch  a  new  Self-
Assessment  Tool  that  will  include  AI  proficiency  among  targeted  competences.  This 
mirrors the broader efforts to support AI literacy for workers in different sectors and job 
roles under the Apply AI Strategy.  

The EU must retain and attract scientific and AI talent. The Commission has already 
launched several initiatives to make Europe an attractive place for research and innovation, 
including  improving  research  careers  through  the  Choose  Europe  package32;  lowering 
barriers  to  attract  and  retain  talent  from  non-EU  countries  through  the  EU  Visa  policy 

(24)  AI Skills and Occupations in the European Start-up Ecosystem, EIT, 2025 
(25) Union of Skills communication, COM(2025) 90 final 
(26)  Women represent only 22% of AI professionals globally and account for 13.8% of AI research paper 
authors. World Economic Forum, 2022. The Roadmap for Women’s Rights highlights the importance 
of encouraging women and girls’ acquisition of digital skills and competences, including in AI. 

(27)  AI talent, skills and literacy | Shaping Europe’s digital future 
(28)  Digital Education Action Plan (2021-2027) - European Education Area 
(29) STEM Education Strategic Plan  
(30) EU instruments for education and training include Erasmus+ and the Marie Skłodowska-Curie Actions. 
(31) ResearchComp; as done for the Research Managers Competence Framework (RM Comp)   
(32) Choose Europe for Science  

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strategy and the  EU Talent  Pool initiative;  supporting entrepreneurship through the  EU 
Startup and Scaleup Strategy33 and the actions proposed by the Apply AI Strategy.  

As part of the “Choose Europe for Science” initiative34, RAISE will be a focal point 
for excellence and talent in AI science. The Commission will invest in training the next 
generation of AI in science researchers by  funding RAISE Doctoral Networks on AI in 
Science using the MSCA Doctoral Networks model35. The RAISE Doctoral Networks will 
provide specific training on AI in science and support aspiring doctoral students using AI 
in their scientific work. The RAISE Networks of Excellence will retain and attract talent 
by creating an interdisciplinary and dynamic AI in science ecosystem through training and 
mobility schemes, including with aspiring research groups.  

The Commission will 

• 

• 
• 

fund  Doctoral  Networks  on  AI  in  science  to  train  the  next  generation  of 
researchers (RAISE pilot). 
fund thematic Networks of Excellence on AI in science (RAISE pilot). 
regularly update the ‘Living Guidelines on the responsible use of generative AI 
in research’ and other ethics-related operational materials. 

•  create a JRC Scientific AI Hub to monitor and evaluate AI models and systems 
for strategic scientific research, in close alignment with the European AI Office. 

3.2.  Compute  

Computational capacity is one of the main enablers of AI development and therefore 
also one of its key bottlenecks. Academia has generally less computational infrastructure 
at its disposal than Big Tech36, while the demand for computational resources is growing 
as more scientists across different disciplines integrate AI into their work. 

Researchers  across  Member  States  report  difficulties  in  either  accessing  sufficient 
computational resources or in effectively using them37. This often leads users to turn to 
private  providers,  resulting  in  vendor  lock-in  effects  (over-dependence  on  proprietary 
models  developed  by  private  and  foreign  companies)  and  increased  industry  influence. 
Consultations informing this Strategy have confirmed the growing importance of publicly 
supported computational infrastructures for the development and deployment of frontier 
AI models and to enable increasingly complex scientific applications.  

Since 2018, the EU has invested in state-of-the-art supercomputing capacities, through the 
European  High  Performance  Computing  Joint  Undertaking  (EuroHPC  JU38)  and  the 
European Regional Development Fund (ERDF), via its national and regional programmes. 
Additional  AI  capabilities  for  researchers  and  innovators  are  currently  being 
developed.  The  creation  of  AI  Factories,  built  around  new  or  upgraded  AI-optimised 
EuroHPC  supercomputers  across  the  EU  in  2025-26,  will  more  than  triple  the  current 
EuroHPC AI computing capacity for European users, including researchers.  
As  part  of  the  AI  research  and  innovation  support  ecosystem (39),  AI  Factories  are 
already  improving  stakeholder  uptake  by  offering  services  such  as  algorithmic 

(33)  COM(2025) 270 final 
(34)  Choose Europe for Science   
(35)  MSCA  Doctoral  Networks  is  a  bottom-up  action  focusing  on  research  training  that  attracts  a  large 

proportion of projects with a significant AI component 

(36) “Academia is falling behind industry in frontier AI research. Today, no university in the world can build 

a frontier AI system on par with industry.” (Stanford Human-Centered AI, 2024) 

(37) According to the results of the consultations with stakeholders for the AI in science Strategy 
(38)  https://www.eurohpc-ju.europa.eu/index_en  
(39)  See more reference to the role played by the ecosystem of support in the Apply AI Strategy.   

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development,  testing  evaluation  and  validation  of  large-scale  AI  models,  providing 
supercomputer-friendly programming facilities and other AI-enabling services. Many of 
the  AI  Factories  will  focus  on  specific  scientific  fields40.  The  EuroHPC  Access  Policy 
includes  a  new  access  mode  for  “AI  for  Science  and  for  Collaborative  EU  Projects”. 
Through  this  access  mode,  selected  EU-funded  research  projects  are  not  subject  to  an 
additional evaluation or peer review process and are given priority over other requests. 

To further scale the EU’s public AI infrastructure, the Commission proposes the EU to 
support  establishing  AI  Gigafactories  by  pooling  EU,  Member  State,  regional  and 
private sector resources41. AI Gigafactories will take the concept of the AI Factories to 
the next level. These will be large-scale facilities designed to develop, train, and deploy 
large AI models and scientific applications at an unprecedented scale, integrating massive 
computing power together with energy-efficient data centres, and AI-driven automation to 
optimise AI model training, inference, and deployment. The Commission will continue to 
anticipate and plan for future computational demands. Infrastructure upgrades will align 
with the scientific priorities of European researchers, ensuring that capabilities remain fit 
for purpose and able to anticipate future trends that are relevant for AI, such as quantum 
computing42.  

RAISE will benefit from the essential European computational resources of the AI 
Factories,  as  well  as  the  future  AI  Gigafactories.  RAISE  will  work  closely  with  the 
EuroHPC Joint Undertaking and ensure guaranteed availability and scheduling priority for 
EU-funded research projects in relation to reserved computational resources. 

The Commission will:  

•  secure dedicated access to AI Gigafactories for EU scientists and startups, 

including for Horizon Europe specific objectives. Horizon Europe will invest 
up to EUR 600 million (RAISE pilot). 

•  continue developing the AI computing resources devoted to science through the 

AI Factories.  

3.3.  Data 

The EU has spearheaded major initiatives in legislation and infrastructure to develop 
a robust data ecosystem in Europe. These include the European Open Science Cloud 
(EOSC) as  the Common European  Data Space for R&I43, the other  Common  European 
Data Spaces44 such as the European Health Data  Space45,  the Open Data Directive, the 
Data Governance Act and the Data Act46. These efforts are complemented by additional 
thematic initiatives like the Cultural Heritage Cloud47, Materials Commons48, or biodata 
resources49. These initiatives will boost the uptake of AI in science, as high-quality data is 
a fundamental enabler for scientific applications of AI. 

While AI-ready research data are needed to enable AI solutions to scientific questions and 
workflows,  the development and scaling of high-quality scientific  datasets still face 

(40)  https://eurohpc-ju.europa.eu/ai-factories_en  
(41)  Public Consultation on the AI GigaFactories 
(42)  https://digital-strategy.ec.europa.eu/en/library/quantum-europe-strategy  
(43)  European Open Science Cloud  
(44) https://digital-strategy.ec.europa.eu/en/policies/data-spaces  
(45)  Regulation (EU) 2025/327 on the European Health Data Space  
(46)  Open Data Directive; Data Governance Act; Data Act 
(47)  The Cultural Heritage Cloud  
(48)  Communication on Advanced Materials for Industrial Leadership, COM(2024) 98 final  
(49)  Communication on Choose Europe for life sciences, COM(2025) 525 final  

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persistent  structural  challenges50.  Europe  is  a  global  leader  in  high-quality,  curated, 
scientific data. Nonetheless, open scientific databases are not used to their full potential 
due  to  the  fragmentation  of  research  infrastructures,  barriers  to  data  sharing,  lack  of 
interoperability,  data  silos and  privacy concerns.  Initiatives like the Common European 
Data Spaces, and in particular EOSC51, aim to make more data available for access and 
reuse, addressing some of these challenges. The European Health Data Space enhances the 
discoverability  and  reuse  of  health  data  across  Europe,  while  providing  a  trusted 
framework supporting fairness and excellence in AI-enabled research. 

As announced in the AI Continent Action Plan, the above-mentioned initiatives will be 
complemented and reinforced by the forthcoming Data Union Strategy, by opening new 
sources  of  high-quality, 
large-scale  data  and  enabling  businesses  and  public 
administrations to share data seamlessly and at scale. In this context, the Commission will 
set up Data Labs within AI Factories that will federate data from different sources, 
including the Common European Data Spaces. Data Labs could also offer a range of 
other  services,  such  as  cleaning  and  enriching  datasets,  providing  technical  tools  (e.g. 
standardised  formats,  synthetic  data,  shared  technical  building  blocks),  supporting 
regulatory  compliance  (e.g.  GDPR)  and  fostering  interoperability  across  sectors  and 
borders. The Data Labs will be an important tool for scientists working with AI, connecting 
data repositories with data services and the EuroHPC infrastructure. Through its Strategy 
for Research and Technology Infrastructures52, the Commission will bolster the capacities, 
accessibility  and  sustainability  of  Europe’s  research  and  technology  infrastructure 
ecosystem and launch actions on Open Science as a key enabler for the development of 
scientific AI applications. 
One objective of the 2025-2027 ERA Policy Agenda 53 in its structural policy on open 
science is to provide researchers with better legal conditions and resources to access and 
reuse  publicly  funded  research  results  and  to  use  publications  and  data  for  scientific 
purposes. In this context, the Commission will gather further evidence54, including through 
stakeholder consultations on existing challenges and possible solutions and policy options.  

RAISE will work closely with EOSC, as well as the other Data Spaces, to make high-
quality  AI-ready  data  available  for  AI  science.  It  will  support  the  development  and 
design of the future Data Labs, as part of the AI Factories, to support the needs of scientists 
(e.g. data gathering, cleaning and enriching services) and promoting its use by the scientific 
community. RAISE will also help to identify strategic scientific data gaps and support the 
efforts to gather, curate and integrate the datasets needed for AI science. 

(50) Mutual Learning Exercise on AI in science – Second thematic report 
(51)  EOSC  is  being  implemented  as  a  federation  of  data  repositories  and  services.  EOSC  also  provides 

scientific services that support the uptake of AI. 

(52)  https://research-and-innovation.ec.europa.eu/document/009f0f91-74d3-4b94-9d79-55668cfd5a78_en  
(53)  Council Recommendation on the European Research Area Policy Agenda 2025-2027 
(54)  Complementing existing evidence, see “Improving access to and reuse of research results, publications 

and data for scientific purposes” https://data.europa.eu/doi/10.2777/633395  

10 

 
 
The Commission will:  

•  support the design of Data Labs, and their linking with Common European 

Data Spaces, in particular EOSC, to ensure their suitability and the accessibility 
and reusability of data for scientific research. 

•  support scientists to identify strategic data gaps and gather, curate and integrate 

the datasets needed through the RAISE Networks (RAISE pilot). 

•  collect evidence on the need to improve access to and reuse of publicly funded 
research results and the use of publications and data for scientific purposes.  

3.4.  Research Funding 

European  research  funding  is  already  supporting  AI  in  science  projects  in  a  wide 
range of disciplines, as well as many projects on the science of AI. This has fostered 
the use of AI as a tool across disciplines and advanced the state of science in those fields 
(see  box  below).  As  AI  technologies  have  become  more  advanced  and  widely  used, 
research funding has increased, which is, for example, reflected in the increase in European 
Research Council (ERC) grants55 for AI in science (see graph below).  

EU-funded AI in science projects56 

F-IMAGE employed AI to classify and analyse seismic signals and understand the behaviour of 
faults during earthquakes. By evaluating the short-term evolution of faults, it becomes possible 
to better understand processes that produce earthquakes. 

AI-PREVENT applied AI to datasets covering health and other lifestyle factors, to achieve more 
predictive and personalised healthcare. The AI-generated models were shown to be powerful 
tools for identifying specific individuals at risk and in need of preventive care.  

BioMonitor4CAP develops biodiversity monitoring systems for agricultural fields that integrate 
classical  indicator  methodologies  with  advanced  technological  approaches,  including  AI.  Its 
main goal is to provide knowledge, methods and tools to farmers and the wider public.  

Under Horizon Europe, the EU has invested EUR 6.4 billion in AI over the 2021-24 
period. The 2025 Horizon Europe Work Programme is investing another EUR 1.6 billion, 
of which around EUR 0.7 billion for AI in science, and further support for AI in science is 
planned  for  the  period  2026-27  of  Horizon  Europe  through  dedicated  topics  promoting 
collaborative research under Pillar II. Additional funding  for AI in  science comes from 
bottom-up  instruments, such  as  the  ERC,  MSCA  and  the  European  Innovation  Council 
(EIC)57.  Dedicated  actions  like  GENAI4EU58  have  further  streamlined  the  use  of 
generative  AI  across  domains  and  applications.  The  Commission  has  also  provided 
funding for over EUR 100 million to nine Networks of Excellence in AI to connect top AI 
research laboratories across Member States and advance AI. In parallel, the Commission 
has committed an additional EUR 70 million under Horizon Europe and Digital Europe to 
develop large, multimodal AI models that push the boundaries of current capabilities and 
support the emergence of frontier AI. 

(55) ERCEA, Mapping ERC frontier research artificial intelligence, 2024 
(56) Examples of EU-funded projects using AI in the CORDIS results pack on AI in science and AI in the 

life sciences 

(57)  The ERC grants on AI in science added up to around EUR 450 million in 2023 and overall invested over 
EUR 2 billion in AI research since 2007. MSCA has funded more than 1000 AI projects with a strong 
AI component, while EIC is supporting several AI in science startups. 

(58) COM(2024) 28 final  

11 

 
 
Share of ERC-funded AI in science projects per domain per year 

The  Commission  will  further  strengthen  active  coordination  and  alignment  of 
investments  in  AI  in  science,  to  maximise  value  and  foster  strategic  investments  in 
thematic  areas  that  can  benefit  from  increased  AI  capabilities.  The  Commission  is 
committed  to  maintaining  and  strengthening  its  role  as  the  main  provider  of  European 
research  funding  for  AI  in  science,  amplifying  Horizon  Europe’s  role  as  a  catalyst  for 
innovative  AI-driven  scientific  approaches.  Cohesion  Policy  funding,  particularly  the 
ERDF,  is  another  principal  Union  instrument  for  supporting  research  and  innovation, 
including in AI59.  

To effectively fund AI in science, it is crucial that funding instruments are tailored to 
its  rapidly  evolving  nature60.  Funding  should  be  flexible,  agile,  and  supportive  of 
interdisciplinarity and collaboration. It should be capable of rapidly reacting to new ideas 
and  trends  and  guarantee  access  to  technical  infrastructure  and  expertise.  Additionally, 
funding  programmes  should  strike  a  balance  between  bottom-up  and  directional  calls, 
different  project  sizes,  individual  and  collaborative  research  initiatives,  and  support  the 
creation and maintenance of necessary infrastructures. 

RAISE will mitigate the fragmentation of  research efforts by incentivising aligned 
and  coordinated  research  funding.  It  will  use  a  variety  of  instruments  under  the 
European  Research  and  Innovation  Framework  Programme  and  engage  in  additional 
coordination efforts. These will include funding of cross-domain research to build models 
and AI tools that benefit scientists across disciplines and working with Member States to 
develop and align national research agendas for AI science. 

The Commission will: 

• 

incentivise and coordinate investments in AI in science through an investment 
agenda in Horizon Europe’s 2026-27 Work Programme (RAISE pilot). 
•  seek to double current Horizon Europe yearly investment figures in AI, 

• 

including doubling that for AI in science by 2028. 
fund scientific laboratory automation and the development and update of 
scientific foundation models, including in industrial settings (RAISE pilot). 

(59)  In particular by using the flexibilities introduced by the Mid-Term Review, including through STEP, to 

strengthen dual-use investments such as AI applications. 

(60)  MLE on AI in science 

12 

 
 
 
3.5.  Collaboration and coordination 

Accelerating  the  responsible  uptake  of  AI  in  science  requires  coordination  and 
collaboration  at  European  level  to  mobilise  additional  resources  and  align  efforts. 
This distinctive European approach will build on three fundamental aspects: (i) building 
successful  collaborations with  the private sector,  (ii) policy coordination  and alignment 
within the EU, and (iii) alliances and cooperation with other international actors61.  

Private sector collaboration 

The  Commission  is  committed  to  building  a  more  dynamic  and  successful 
entrepreneurial  ecosystem  in  Europe.  The  recently  adopted  EU  Startup  and  Scaleup 
Strategy62 aims to position the EU as the best place in the world to start and scale global 
technology-driven companies. Startups and companies with a focus on AI in science will 
increase in importance in the coming years. These companies base their business model 
and  competitive  advantage  on  new  scientific  discoveries  achieved  with  AI,  the 
development of new tools to conduct science with AI (e.g. models, research assistants), 
and new scientific AI services for key sectors. 

European AI in science startups  

There  are  many  examples  of  European  startups  built  around  the  use  of AI  in  science.  For 
example, a French biotechnology company developed an AI foundation model for biology. 

An Italian startup focusing on climate risk analytics from space uses machine learning on Earth 
observation data (from multiple satellite constellations) to quantify how assets are exposed to 
climate hazards like floods, hurricanes, and droughts.  

A  Polish AI-powered  chemistry  startup  has  built  a  platform  for  planning  organic  synthesis 
routes, a key but complex and time-consuming step in drug development and materials science. 

Companies  leveraging  AI  in  science  face  similar  challenges  to  other  European 
startups and scaleups63, such as the lack of a fully integrated Single Market, including 
for capital, lower investor risk appetite, and regulatory hurdles. In addition, they face an 
even greater challenge in finding talent, as it is highly specialised, in demand and scarce. 
The EIC invested more than EUR 150 million in 2024 in AI projects (and more than EUR 
400 million in the 2021-24 period)64 and will continue to play a large role in supporting 
the startup and scaleup ecosystem of AI in science. It provides venture capital while also 
supporting  early-stage  innovative  ideas,  such  as  AI  research  assistants  and  autonomous 
research  labs.  In  line  with  the  EU  Startup  and  Scaleup  Strategy,  the  Commission  will 
expand and increase the importance of the EIC and simplify its rules as part of broader 
simplification  efforts  to  reduce  administrative  burden  for  businesses.  In  addition,  the 
European Institute of Technology (EIT) is supporting AI-related activities throughout their 
ecosystem, which currently features approximately 800 AI startups with a total valuation 
of close to EUR 20 billion. 

The Commission is committed to supporting the transition from research to market, 
particularly for products and services based on scientific applications of AI. The AI 
Act is designed to foster trust while supporting technological advancement. It will create 
an internal market for AI, avoiding fragmentation and offering legal certainty to investors. 

(61)  For  broader  collaboration  and  coordination  with  the  AI  providers,  industry  leaders,  public  sector 
organisations, academia and the wider public, see the collaboration mechanism put in place under the 
Apply AI Strategy: the Apply AI Alliance.   

(62) https://ec.europa.eu/commission/presscorner/detail/en/ip_25_1350  
(63) The EU Startup and Scaleup Strategy, COM(2025) 270 final 
(64)  EIC impact report 2025 

13 

 
 
The AI Act supports innovation and scientific freedom, as it excludes from its scope AI 
systems  and models  specifically developed  and  put  into service  for the sole purpose of 
scientific  research  and  development.  As  outlined  in  the  AI  Continent  Action  Plan,  the 
Commission is working to support a clear implementation of the AI Act, including help to 
research  institutions,  spin  offs  and  startups  to  navigate  the  AI  regulatory  landscape. 
Support measures include the recent Guidelines65 and Code of Practice66 (both on general 
purpose AI models), the upcoming AI Act Service Desk and the AI Regulatory Sandboxes 
(which  are  mandatory  in  each  Member  State  and  should  include  the  scientific  research 
community in their design and operation).  

This European AI in Science Strategy goes beyond publicly funded research and the 
public sector. Private research should also be mobilised and embrace AI as a fundamental 
tool for research activities. The largest technology companies in the world are establishing 
internal  AI  in  science  teams  and  establishing  partnerships  with  leading  research 
institutions. For that reason, the Commission will launch a pledging exercise targeted at 
the  private  sector,  including  philanthropic  organisations,  to  help  mobilise  additional 
resources  and  investments.  The  Commission  will  also  incentivise  startups  and  other 
companies to participate more actively in EU-funded AI in science research projects that 
are  close  to  the  application  stages,  for  example  through  participants  in  the  Apply  AI 
Alliance.  

The Commission will:  
•  organise AI in Science Summits, annual flagship events bringing together AI in 
science communities (scientists, policy makers, startups, tech companies). 
• 
launch a campaign to encourage pledges from private companies on AI in science. 
•  analyse the implications of the AI Act for the scientific community, for example by 

assessing the AI Act research exemption for spin-offs. 

Member States coordination 

The  Commission  and  Member  States  agree  on  the  strategic  importance  of  AI  in 
science  and  in  developing  a  common  European  approach,  as  reflected  in  the  recent 
Council Conclusions on AI in science67. The Commission is already working with Member 
States  to  build  capacity,  identify  challenges  and  share  best  practices  at  national  level 
through a Mutual Learning Exercise (MLE) on AI in science68. 

Actions  and  investments  at  Member  States  level  are  crucial  for  the  success  of  the 
strategy. Member States need to address their specific needs and act as multipliers of the 
European  efforts  within  their  respective  R&I  systems,  as  approximately  90%  of  public 
research funding in the EU comes from the national level69. Those investments will need 
to build on the strengths of European science, namely collaboration, academic freedom, 
and the responsible use of AI. The Commission and Member States could seek to align 
their research funding agendas on AI in science70.  

High-level  commitments  and  guidance  are  needed  to  ensure  that  AI  in  science 
initiatives align with broader EU and national policies and priorities. Coordinated and 
aligned policies at both EU and Member States level should support and pave the way for 

(65)  https://digital-strategy.ec.europa.eu/en/policies/guidelines-gpai-providers  
(66)  https://digital-strategy.ec.europa.eu/en/policies/contents-code-gpai  
(67)  Council conclusions ‘Towards the EU strategy on AI in science’, 23 May 2025  
(68)  Mutual Learning Exercise (MLE) on AI in science 
(69) All the EU-level funding of public R&D accounts for around one-tenth of the overall public spending on 
R&D in the Union, The future of European competitiveness: In-depth analysis and recommendations,  
(70)  While respecting article 4(3) of  Treaty on the Functioning of the European Union and the applicable 

State Aid rules. 

14 

 
 
other institutions (universities, research organisations, etc.) to accelerate the uptake of AI 
in science through more targeted actions. Coordination efforts should foster a culture of 
co-ownership and collaborative governance.  More national  AI strategies  should include 
concrete measures to support AI in scientific research71. 

Coordination will take place under the ERA governance72, as part of the 2025-27 ERA 
policy  agenda73.  Working-level  coordination  with  Member  States,  Horizon  Europe 
associated countries and R&I stakeholders will ensure that the technical aspects of AI in 
science are thoroughly addressed. This work will aim to align with the forthcoming ERA 
Act and the broader strategic objectives of the ERA. It will support and facilitate the design 
and development of RAISE and future participation of countries. 

As  recommended  by  the  Heitor  Report74,  this  coordination  will  be  supported  by  a 
monitoring mechanism that allows for the orientation and timely adaptation of relevant 
policies  and  investments.  It  will  track  progress  of  the  uptake  of  AI  by  scientists  at  an 
international level, with Key Performance Indicators (KPIs) such as scientific publications, 
key  foundation  models  in  selected  scientific  disciplines  and  their  interconnections, 
strategic  enabling  datasets,  and  other  aspects  (skills,  education,  start-ups/companies). 
These insights will be integrated in the Observatory announced in the Apply AI strategy.  

The Commission will: 

•  coordinate with Member States, Associated Countries and R&I stakeholders in 
the ERA governance, such as the dedicated ERA Action on AI in science.  

•  monitor the uptake of AI in science with indicators and metrics. 

International cooperation 

The EU aims to shape the use of AI in science so that it is open, human-centric and 
rooted in scientific excellence, within the framework of the overall EU policy on AI and 
in synergy with the Apply AI strategy. The EU seeks to position itself as a frontrunner in 
aligning  technological  progress  with  fundamental  rights  and  promoting  this  vision 
internationally.  International  cooperation  thus  supports  both  the  EU’s  open  strategic 
autonomy  and  its  ambition  to  shape  global  standards.  The  EU’s  capacity  to  lead 
responsibly  in  this  domain  depends  on  its  ability  to  work  with  partners  who  share  its 
principles and to play an active role in shaping the use of AI in science. 

This position is based on the international engagement priorities of the EU’s policy 
on AI. It builds on existing strategic frameworks such as the recent “International Digital 
Strategy for the European Union”75, which aims to shape the global digital agenda around 
openness, inclusiveness and rights, as well as the EU’s “Global Approach to R&I”76, the 
Horizon Europe association agreements and the Science & Technology Agreements with 
third countries, subject to their alignment with the international cooperation priorities of 
the  EU  AI  strategy,  which  have  laid  the  groundwork  for  values-based  and  mutually 
beneficial international research and innovation cooperation. It may also be anchored in 
ongoing  regional  policy  dialogues  and  science  diplomacy  where  AI  in  science  can  be 

(71)  Based  on  OECD  AI  Policy  Observatory  2024,  section  in  Bianchini  et  al.,  ‘Artificial  intelligence  in 

science – Promises or perils for creativity?’, 2025, https://data.europa.eu/doi/10.2777/6693925  

(72)  The AI Board -established as part of the AI Act- will be closely linked and kept informed about ERA’s 

activities.  

(73)  Council Recommendation on the European Research Area Policy Agenda 2025-2027  
(74) Align, act, accelerate – Research, technology and innovation to boost European competitiveness, 2024,  
(75) COM(2021) 252 final 
(76)  https://research-and-innovation.ec.europa.eu/system/files/2021-05/ec_rtd_com2021-252.pdf  

15 

 
 
integrated and where this is aligned with the international engagement priorities of the EU 
AI strategy.  

Deeper international engagement must be accompanied by safeguards and openness 
must be balanced with vigilance against unwanted technology transfer or dependencies in 
strategic  areas.  Research  security  is  therefore  a  key  component  of  this  approach  as 
articulated in the European Economic Security Strategy, the International Digital Strategy 
and the Global Approach to R&I. The EU reaches out to trusted partners, amplifying its 
influence  and  ensuring  that  global  rules  and  standards  reflect  its  vision  and  strategic 
interests. This effort complements Member States’ bilateral engagements and strengthens 
the EU’s collective position in multilateral fora such as the G7, G20, UNESCO, the OECD 
and the Multilateral Dialogue on principles and values.  

This  approach  contributes  to  a  globally  connected  yet  strategically  autonomous  ERA, 
where scientific collaboration supports EU competitiveness and global responsibility.  

The Commission will: 

•  address specific issues of AI in science with relevant third countries and 

regions in the context of the overall EU international engagement on AI, in line 
with its priorities, and within the existing framework. 

•  engage through existing regional policy dialogues on R&I to identify joint 
priorities, co-fund the use of AI in science projects and promote capacity 
building and mutual learning in the use of AI in science, in alignment with the 
international cooperation priorities of the EU’s AI strategy. 

•  promote EU principles and values and standards for the responsible use of AI 
in science through relevant multilateral fora and international organisations, in 
alignment with the international cooperation priorities of the EU AI strategy. 

4.  AI IN SCIENCE IN KEY SECTORS: ILLUSTRATIVE CASES FOR AI IN SCIENCE 

Advanced materials and biotechnologies are European R&I priorities and key sectors with 
a strong scientific foundation, for which AI holds great potential, as identified in the AI 
Continent Action Plan. Other sectors for the application of AI are covered in the Apply AI 
Strategy. 

AI for advanced materials design 
AI can facilitate breakthroughs in the entire cycle of advanced materials from discovery77 
to  manufacturing,  while  it  can  also  enable  advanced  manufacturing  techniques  (further 
developed  in  the  Apply  AI  Strategy)  to  develop  an  industrial  base  that  is  interoperable 
between civil and defence domains.  

Advanced materials exhibit superior properties or performance compared to conventional 
materials. They are typically used in cutting-edge applications such as electronics, energy, 
biomedical  devices  or  aerospace  and  are  a  critical  technology  for  the  EU’s  economic 
security. The advanced materials global market can be broadly estimated at around EUR 5 
trillion, with the EU representing 25%. Materials science is one of the domains in which 
AI  is  being  adopted  the  fastest  (growing  almost  50%  on  a  yearly  basis),  as  it  can 
significantly  reduce  the  time  and  resources  required  for  industrial  production  and 
accelerate time-to-market.  Combining  AI and robotics in  closed-loop  synthesis  systems 
could perform new material identification and validation more than 1000 times faster than 

(77)  For  more  info  on  AI  and  materials  discovery,  please  check  “The  Role  of  Artificial  Intelligence  in 
Scientific Research – A Science for Policy, European Perspective” Publications Office of the European 
Union, Luxembourg, 2025, JRC143482, DOI: 10.2760/7217497. 

16 

 
 
conventional techniques78.  

The demand for innovative advanced materials is expected to increase exponentially. In 
the coming years, the Commission will put forward an Advanced Materials Act in 2026, 
providing  a  framework  for  the  entire  lifecycle  from  research  to  manufacturing  and 
deployment.  The  Horizon  Europe  Work  Programme  2025  foresees  the  creation  the 
Materials Commons for Europe, a federated digital infrastructure for R&D on advanced 
materials, highlighting the major transformative potential of this technology area. 

AI for biotechnology 

Biotechnologies  are  a  key  sector  for  the  competitiveness  of  the  EU’s  economy. 
Biotechnologies can offer solutions to challenges such as human health, climate change or 
agrifood  supply79and  it  is  a  critical  technology  area  for  the  EU’s  economic  security80. 
Biotech  in  the  EU  represents  almost  EUR  65  billion  in  turnover  and  employs  300 000 
people81. The Commission is set to propose a Biotech Act in the near future. 

AI is rapidly transforming biotechnologies, advancing all domains from drug discovery to 
precision  fermentation.  Biological  AI  models  are  used  to  analyse  complex  biological 
systems,  predict  the  3D  structure  of  biomolecules82  without  the  need  for  lengthy 
experiments  and  even  generate  new  biological  agents  from  scratch.  The  number  of 
biological AI models has been rapidly increasing and growing in size and capabilities83. 
While the EU can count on an excellent biotech research ecosystem, leading biological AI 
models are mostly being developed outside the EU and by private actors84. 

The biotechnology research sector still faces several challenges to take full advantage of 
AI. Data interoperability challenges must be overcome and vast amounts of different types 
of biological data from different organisms, geographic origins and experimental setups 
require integration. The rapid advances in the capabilities of AI models and their dual-use 
potential also increase the risk of misuse of the technology, requiring special mitigation 
measures85.  Strong  collaboration  between  AI  experts,  biologists,  chemists,  clinicians, 
ethicists, and policymakers is needed, along with robust methods to evaluate and improve 
AI safety, security and trustworthiness86. 

The EU has already launched several initiatives that can benefit the uptake of AI in biotech 
research. These include the Life Sciences Strategy87, the European Data Strategy to create 
a single market for data (including health data via the European Health Data Space)88 and 
the Life Sciences AI Factories presented in the AI Continent89.  

(78)  Maqsood A, Chen C, Jacobsson TJ. The Future of Material Scientists in an Age of Artificial Intelligence. 

Adv Sci (Weinh). 2024 May;11(19):e2401401. doi: 10.1002/advs.202401401.  

(79)  COM/2024/137 final  
(80)  https://eur-lex.europa.eu/eli/reco/2023/2113  
(81)  Data 

for  2022,  https://datam.jrc.ec.europa.eu/datam/mashup/LIFE_SCIENCES_SECTORS/  and 

https://publications.jrc.ec.europa.eu/repository/handle/JRC142396  

(82)  For more info on AI and biomolecules structures, please check “The Role of Artificial Intelligence in 
Scientific Research – A Science for Policy, European Perspective” Publications Office of the European 
Union, Luxembourg, 2025, JRC143482, DOI: 10.2760/7217497. 
(83)  https://epoch.ai/blog/announcing-expanded-biology-ai-coverage  
(84)  AI  Index  Report  2024  –  Artificial  Intelligence  Index ; https://epoch.ai/blog/announcing-expanded-

biology-ai-coverage  

(85)  Providers of general-purpose AI models can refer to the AI Act, the Code of Practice and the Guidelines 

on the scope of obligations for further guidance on risk assessment and mitigation at AI model level.   

(86)  Gómez-González,  E.  and  Gómez,  E.  Artificial  intelligence  for  healthcare  and  well-being  during 

exceptional times: a recent landscape from a European perspective  

(87)  Communication on Choose Europe for life sciences, COM(2025) 525 final 
(88)  The European Data Strategy  
(89)  https://commission.europa.eu/topics/eu-competitiveness/ai-continent_en  

17 

 
 
5.  CONCLUSIONS 

The increased adoption of AI in science will have profound scientific, economic and 
social implications; it will accelerate discoveries, stimulate economic growth, radically 
transform  entire  industries  and  create  new  ones.  The  Commission  is  committed  to 
harnessing the power of AI in science, reinforcing the EU’s position as a leader in science, 
and paving the way to a new era of competitiveness.  

The European Strategy for AI in Science builds on existing European strengths and 
embraces a distinctly European approach to AI. It proposes actions to support and further 
boost  European  excellence  in  AI-enabled  science  to  empower  researchers  and  drive 
breakthroughs.  The  flagship  initiative,  embodying  these  ambitions,  is  RAISE,  a  virtual 
European institute that will pool resources, expertise and talent to advance AI science.  

The  implementation  of  this  strategy  is  only  possible  in  close  collaboration  with 
Member States, associated countries, the scientific community and other stakeholders, for 
which the ERA will provide the main governance framework. Coherence with other AI 
policies and initiatives will be ensured, contributing to the overall European AI governance 
proposed in the Apply AI strategy, namely coordination at Member State level with the AI 
Board. 

The Commission invites the European Parliament, the European Council, the Council of 
the EU and stakeholders to endorse the European Strategy for AI in Science and to actively 
contribute to delivering on the initiatives it sets out. A policy monitoring framework will 
be developed to monitor progress towards the goals of this strategy. The Commission 
will report on the implementation of the Strategy by the end of 2027. 

In  the  ongoing  global  race  for  AI,  the  use  of  AI  in  science  presents  the  EU  with  an 
opportunity  to  plant  the  seeds  for  future  innovation  and  competitiveness,  in  AI  and  far 
beyond. We can seize the moment by joining forces, adopting the European approach to 
AI and creating a new dynamic in our world-class ecosystem of scientific excellence.  

18 

 
 
ANNEX I: SUMMARY OF ACTIONS 

RAISE 

Excellence  & 
talent 

Actions 
•  Launch the pilot of RAISE at the AI in Science Summit (Q4/25)  
•  Establish initial RAISE coordination for AI in science (Q4/25) 
•  Partner with Member States and private sector to build RAISE (2028) 
•  Establish a high-level academic advisory board (Q4/25) 
•  Fund  Doctoral  Networks  on  AI  in  science  to  train  the  next  generation  of 

researchers (RAISE pilot) (Q4/25) 

•  Fund  Thematic  Networks  of  Excellence  on  AI  in  science  (RAISE  pilot) 

Compute 

Data 

(Q4/25) 

•  Update  the ‘Living  Guidelines  on  the responsible  use  of  generative  AI in 
research’ and other ethics-related operational materials (on a regular basis) 
•  Create an AI Evaluation Hub to monitor and evaluate AI models and systems 

in strategic scientific fields (2027) 

•  Secure dedicated access to AI Gigafactories for EU scientists and startups, 
including  for  Horizon  Europe  specific  objectives.  Horizon  Europe  will 
invest up to EUR 600 million (RAISE pilot) (Q4/25)  

•  Develop the AI computing resources devoted to science through the AI 

Factories  

•  Support the design of Data Labs and their linking with Common European 
Data Spaces, in particular EOSC, to ensure their suitability for scientific 
research (2026) 

•  Support scientists to identify strategic data gaps and gather, curate and 

integrate the datasets needed through the RAISE Networks (RAISE pilot) 
(Q4/25) 

•  Collect evidence on the need to improve access to and to reuse publicly 

Research 
funding 

• 

funded research results and the use of publications and data for scientific 
purposes (Q4/25) 
Incentivise  and  coordinate  investments  in  AI  in  science  through  an 
investment agenda on AI in Science in Horizon Europe’s Work Programme 
2026-27 (RAISE pilot) (Q4/25) 

•  Seek to double Horizon Europe investment figures in AI and AI in science 

by 2028 

•  Fund scientific laboratory automation and the development  and update  of 

scientific foundation models (RAISE pilot) (Q4/25) 

Collaboration 
& 
Coordination 

Private sector collaboration 
•  Organise  AI  in  science  Summits,  (First  edition  in  Copenhagen  3-4 

November 2025, under the Danish Presidency) (Q4/25) 

•  Launch a campaign to encourage pledges from private companies (2026) 
•  Analyse the implications of the AI Act for the scientific community (Q4/25)  
Member States coordination 
•  Coordinate with Member States, Associated Countries and R&I 
stakeholders through the ERA Action on AI in science (Q4/25) 

•  Monitor the uptake of AI in science with indicators and metrics. (2026)  
International cooperation  
•  Address  specific  issues  of AI  in  science  with relevant third countries  and 

regions (Q4/25) 

•  Engage through existing regional policy dialogues on R&I (Q4/25) 
•  Promote  EU  values  and  standards  for  responsible  AI  in  science  through 

multilateral fora (2026) 

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