COMMUNICATION FROM THE COMMISSION TO THE EUROPEAN PARLIAMENT, THE COUNCIL, THE EUROPEAN ECONOMIC AND SOCIAL COMMITTEE AND THE COMMITTEE OF THE REGIONS on boosting startups and innovation in trustworthy artificial intelligence
Date: 2024-01-24
Institutions: Directorate-General for Communications Networks, Content and Technology, European Commission
Subjects: EU financial instrument, EU strategy, aid to undertakings, artificial intelligence, cybernetics, data processing, data protection, diffusion of innovations, scientific cooperation, start-up, technological change

EN 

  EN 

   EUROPEAN COMMISSION  Brussels, 24.1.2024  COM(2024) 28 final  COMMUNICATION FROM THE COMMISSION TO THE EUROPEAN PARLIAMENT, THE COUNCIL, THE EUROPEAN ECONOMIC AND SOCIAL COMMITTEE AND THE COMMITTEE OF THE REGIONS on boosting startups and innovation in trustworthy artificial intelligence  
 
 
Communication on boosting startups and innovation in trustworthy artificial 

intelligence 

1.  Introduction  

Artificial intelligence (AI) has permeated our lives, transforming how we live and work. Over 
the past few years, a rapid and disruptive acceleration of progress in AI has occurred, driven 
by  significant  advances  in  widespread  data  availability,  computing  power  and  machine 
learning.  Remarkable  strides  were  made  in  the  development  of  foundation  models  -  AI 
models  trained  on  extensive  volumes  of  unlabelled  data1.  This  innovation  has  given  rise  to 
what  is  known  as  ‘General  purpose  AI’,  capable  of  performing  a  wide  array  of  tasks, 
including  the  generation  of  various  forms  of  new  content2,  commonly  referred  to  as 
‘generative AI’. The quality of the output produced by these models is such that it is difficult 
to distinguish it from human-generated content.  

Generative  AI  is  a  general  technology  that  is  accessible,  powerful  and  adaptable  to  a  vast 
range of uses, from health to smart cities, and from meteorology to space and military uses. It 
has the potential to revolutionise human-machine interaction and enhance productivity across 
value  chains  and  organisational  functions,  laying  the  foundation  for  novel  economic 
activities. The use of generative AI is estimated to create business value equivalent to EUR 
2.4-4.0 trillion per year3. Within the first quarter of 2023 alone, global private investment in 
AI was estimated to reach EUR 16.5 billion, up from EUR 8.9 billion in Q4 20224.  

Mastery  of  the  latest  developments  in  generative  AI  will  become  a  key  lever  of  Europe’s 
competitiveness  and  technological  sovereignty.  The  European  Economic  Security  Strategy 
and  the  ensuing  Commission  Recommendation  on  critical  technology  areas5  acknowledged 
AI  as  a  critical  European  asset  and  ranked  it  in  the  priority  four  technologies  that  are 
currently undergoing collective risk assessment6. 

This Communication sets out a strategic investment framework in trustworthy AI for the 
Union to capitalise on its assets, in particular its world-leading supercomputing infrastructure, 
and to foster an innovative European AI ecosystem where startups and innovators can work 
closely  with  industrial  users,  attract  investments  in  the  Union  and  have  access  to  the  key 
ingredients  of  AI  -  data,  computing,  algorithms  and  talent.  In  addition,  it  aims  to  boost 
innovative applications for generative AI in Europe’s industrial ecosystems, while upholding 
European values, tackling risks and promoting the responsible use of AI.  

This Communication lays out the actions and investments in 2024 that will help startups and 
industries  in  Europe  fulfil  their  potential  of  becoming  global  frontrunners  in  trustworthy 
advanced AI models, systems and applications.  

1 For example, models learn from a vast amount of text to understand the structure and context of language without explicit 
instructions  about  what  each  piece  of  text  is  about.  Models  can  therefore  learn  and  generalise  their  understanding  of  the 
world and are capable to handle new and diverse situations. 
2 This content generation spans text, images, sounds, and even code, such as for programming or gene sequencing.  
3 The economic potential of generative AI: The next productivity frontier, June 14, 2023, 
https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/the-economic-potential-of-generative-AI-the-next-
productivity-frontier#introduction 
4 https://www.tortoisemedia.com/2023/06/28/the-global-artificial-intelligence-index/  
5 JOIN(2023) 20 final and C(2023)2113 
6 The proposal for a Council Recommendation on enhancing research security (COM(2024)26 final) will be particularly 
relevant in this context 

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2. The Union’s strategic framework for a thriving AI startup and innovation ecosystem 

2.1. The position of the European Union  

The Union boasts strong assets to create a thriving  startup  and innovation ecosystem for 
AI.  It  has  an  increasing  number  of  fast-growing  AI  startups7,  as  well  as  universities  and 
research  centres  with  high-quality  education,  a  talented  pool  of  researchers  and  a  strong 
science base. The Union also has a large Single Market with many AI users across industrial 
ecosystems,  as  well  as  strong  human  capital,  in  particular  the  presence  of  highly  skilled 
engineers. In each of the ingredients of AI – data, computing power, algorithms and talent – 
Europe has key assets, which should be leveraged and reinforced. 

On  data,  the  Union  is  on  the  cusp  of  realising  a  true  Single  Market  for  data  through  the 
legislative framework recently put in place as part of its European Data Strategy8. The Open 
Data  Directive9  improves  the  availability  of  high-value  datasets,  including  geospatial, 
environmental,  statistical,  and  meteorological  data.  The  Data  Governance  Act10  stimulates 
data  sharing  by  creating  a  common  framework  for  data  intermediation  services.  The  Data 
Act11 will unlock large volumes of IoT-generated data, empowering AI startups to utilise this 
untapped  resource.  The  roll-out  of  European  Common  Data  Spaces  will  improve 
interoperability  and  access  to  large  volumes  of  high-quality  data12.  For  example,  the 
Commission  proposed  the  European  Health  Data  Space  (EHDS)  Regulation  to  provide  a 
consistent,  trustworthy  and  efficient  framework  for  the  use  of  health  data  for  research, 
innovation, policy-making and regulatory activities. 

On computing capacity, large cloud computing platforms have become the main vehicle for 
the training of AI models, offering to other AI business developers, including startups, access 
on  a  commercial  basis.  However,  access  to  such  large  cloud  computing  resources  on  a 
commercial basis is expensive, especially for the emerging AI startups. The Union’s world-
leading  network  of  supercomputers  offers  an  alternative  to  startups,  providing  the  massive 
amounts  of  computing  power  and  storage  required  for  the  development  of  AI  models.  In 
addition, the Union has put in place a major research initiative for designing and developing 
advanced  microprocessors  as  it  is  currently  still  dependent  on  processor  technologies 
developed in other parts of the world.  

On talent, while the Union can already rely on skilled AI expertise, more talent is needed to 
specialise in this rapidly evolving field.  Educational systems are starting to catch up but do 
not yet provide enough specialised programmes to meet the growing needs. Moreover, global 
demand for AI professionals is increasing, making it challenging for the Union to attract and 
retain  experts.  Despite  the  Union’s  scientific  and  industrial  excellence  in  several  strategic 
sectors,  lack  of  an  ecosystem  approach  pooling  the  necessary  AI  and  sectoral  skills  risks 
hampering the Union’s ability to master the latest developments in AI. 

7 When referring to AI startups, this Communication covers startups developing AI models, as well as those that finetune 
them and integrate them in systems and applications.   
8 COM(2020) 66 final 
9 Directive (EU) 2019/1024 
10  Regulation(EU) 2022/868 
11  Regulation(EU) 2023/2854  
12 Commission Staff Working Document on Common European data spaces, SWD(2024)XXX 

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On investment, the Union has a fast growing and vibrant startup ecosystem, with over 600 
startups  focused  on  generative  AI,  of  which  a  third  engaged  in  model  development13. 
However, they do not yet have sufficient access to the investment they need to be able to train 
their models and scale up their activities to become globally competitive.  

Finally,  a  major  asset  is  the  European  approach  to  AI:  this  means  a  focus  on  AI  that  is 
trustworthy,  reliable  and  accessible  and  works  for  people,  respecting  fundamental  rights, 
democracy  and  security,  reflecting  EU  values  and  trusted  by  business  and  consumers.  The 
Union is close to adopting a regulation laying down harmonised rules on AI (the “AI Act”), 
the  world’s  first  comprehensive  regulatory  framework  for  trustworthy  AI.  This  is  coupled 
with  the  first  publicly  mandated  standardisation  work  on  AI14,  which  the  Commission  is 
undertaking with all relevant stakeholders.  

The AI Act provides legal certainty and enhances the uptake of trustworthy AI solutions by 
focusing its regulatory requirements on high-risk applications. Moreover, it sets proportionate 
rules for general-purpose AI models, with a focus on models with a systemic impact, giving 
downstream  providers  the  confidence  to  adopt  and  integrate  these  models  in  their  AI 
applications15. For the time until the rules become applicable, the Commission has initiated 
the  AI  Pact16,  seeking  the  voluntary  commitment  of  industry  to  start  implementing  the 
requirements of the AI Act ahead of its entry into application.  

2.2. The strategic framework  

To overcome the challenges and exploit  its assets, it is  vital  to  strengthen the  Union’s tech 
landscape and ensure its global competitiveness.  

First, in order to support the further development and scalability of AI models in the Union, 
access to world-class supercomputers that accelerate AI training, reducing training time from 
months  to  a  matter  of  weeks,  is  crucial.  The  Union  will  further  upgrade  the  EuroHPC17 
supercomputers to AI capabilities and facilitate access for startups and the science and 
innovation community in need of training AI models. 

Second,  the  Union  will  increase  the  availability  of  and  facilitate  access  to  high-quality 
data  for  AI  startups  and  the  science  and  innovation  community,  by  accelerating  the 
development and deployment of its Common European Data Spaces.  

Third, the Union will support algorithmic developments that are trustworthy, in line with 
the AI Act, including by making available R&I supporting funds.  

Fourth, the Union will strengthen the EU’s generative AI talent pool, by developing and 
federating both AI-specific and sector-specific skills, and by attracting and retaining talent. 

Fifth,  the  Union  will  promote  the  widespread  uptake  and  use  of  generative  AI  in 
application  areas,  including  by  public  administrations  that  could  act  as  lead  user  of  such 
applications.  

Sixth, the Union will encourage public and private investments in AI startups and scale-
ups, including through venture capital or equity support. 

13 ‘Generative AI in the European Startup Landscape 2024’, appliedAI Institute for Europe, https://www.appliedai- 
institute.de/en/hub/2024-generative-ai-study  
14 C(2023)3215. 
15 The regulatory framework also includes the Machinery Regulation ensuring the safety of AI-powered machines, including 
robots. (Regulation (EU) 2023/1230)) 
16 https://digital-strategy.ec.europa.eu/en/policies/ai-pact  
17 https://eurohpc-ju.europa.eu/supercomputers/our-supercomputers_en 

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This strategic framework, aligned with Union law, including internal market and competition 
rules,  will  foster  an  innovative,  fair,  open  and  contestable  AI  market,  while  not  only 
bolstering  European  companies  at  home  but  also  empowering  them  to  compete  confidently 
on the global stage. It will build upon the existing European approach to excellence in AI, in 
particular the Coordinated Plan on AI.18 

The following sections describe how the above strategic framework will be put in motion. 

3.  “AI  Factories”  and  supporting  activities  for  the  AI  startup,  science  and 

innovation ecosystem  

3.1. AI Factories 

To bolster the leadership of European startups and stimulate the emergence of competitive AI 
ecosystems  in  the  Union,  the  Commission  will  establish  “AI  Factories”.  These  are  open 
ecosystems  formed  around  European  public  supercomputers  and  bringing  together  key 
material  and  human  resources  needed  for  the  development  of  generative  AI  models  and 
applications.  These  include  AI-dedicated  supercomputers,  associated  data  centres  in 
proximity or connected via high-speed networks and equally importantly the human capital to 
use  these  resources  effectively  –  from  supercomputing  and  AI  experts,  through  data 
specialists,  researchers,  startups  and  end  users.  “AI  Factories”  will  therefore  include 
computing  power,  data  and  supercomputing  services  as  well  as  large-scale  talent  attraction 
activities. 

Computing power 

In line with the 2023 State of the Union Address of President von der Leyen, the Commission 
is  announcing  actions  to  facilitate  access  to  the  Union’s  public  network  of  interconnected 
supercomputers for startups and the scientific community.  

The “AI Factories” will be deployed around the Union’s EuroHPC supercomputing facilities. 
In  the  period  2018-2027  the  Union  will  invest  EUR  8  billion  in  state-of-the-art 
supercomputing  capacities,  through  the  European  High  Performance  Computing  Joint 
Undertaking (EuroHPC JU).19 The Union has created a world-class public network of eight 
interconnected  supercomputers  located  throughout  Europe20  and  is  at  the  forefront  of 
supercomputing globally. Three of these supercomputers are currently among the top ten 
supercomputers  in  the  world21.  With  the  forthcoming  two  new  supercomputers  to  be 
installed respectively  in  2024 and 2025, the  capabilities of the EuroHPC  infrastructure will 
soon  reach  well  beyond  exascale  performance.  Many  of  the  EuroHPC  supercomputers,  in 
particular  the  most  powerful  ones  have  or  will  have  accelerated  partitions  that  are  very 
suitable for running AI training and AI application tasks.  

The Commission proposes a targeted amendment to the Regulation establishing the EuroHPC 
Joint Undertaking22, introducing an “AI Factories” pillar. This pillar will focus on providing 
an  AI-oriented  supercomputing  service  infrastructure,  fostering  scientific  and  innovation 
capabilities and skills within the AI ecosystem. 

The first element of the “AI Factories” pillar will therefore be the acquisition of AI-dedicated 
supercomputers,  i.e.  supercomputers  equipped  with  very  powerful  processors  adapted  to 

18 COM(2021) 205 final 
19 The EuroHPC Joint Undertaking is bringing together 33 participating states, including all Member States, the Commission 
and three private associations.  
20 https://eurohpc-ju.europa.eu/index_en  
21 LEONARDO in Bologna, Italy, LUMI in Kajaani, Finland, and MareNostrum 5 in Barcelona, Spain. 
22 Regulation (EU) 2021/1173 

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train large-scale AI models. These could be either new EuroHPC supercomputers or upgrades 
of existing EuroHPC supercomputers.  

AI  startups  and  the  wider  scientific  community  will  have  access  to  these  EuroHPC 
supercomputers  in  line  with  Union  rules  and  values.  Access  will  only  be  provided  for  the 
development of ethical and responsible AI models and systems23, a commitment that may be 
demonstrated,  for  example,  by  subscribing  to  the  AI  Pact.  Such  access  can  become  a 
substantial  competitive  advantage  for  the  startups  for  two  main  reasons.  Firstly,  the  use  of 
supercomputers  can  significantly  accelerate  the  training  of  large  AI  models  (from  typically 
six  to  nine  months  on  average  to  just  a  few  weeks).  Secondly,  each  AI  startup  or  research 
organisation accessing a supercomputer for model training can achieve cost benefits reaching 
tens of millions of euros as compared to using commercial cloud platforms. The opportunities 
offered  by  the  “AI  Factories”  will  be  widely  communicated  to  the  startups,  SMEs  and 
researchers active in European programmes such as Horizon Europe and the Digital Europe 
Programme.  

Data storage facilities  

The  second  pillar  of  the  “AI  Factories”  concerns  support  for  using  AI-dedicated 
supercomputers to train AI models. “AI Factories” will have to be located in proximity to or 
connected via high-speed networks to an established data centre to benefit from  large-scale 
data  storage  capacities.  In  addition,  such  data  centres  will  be  interconnected  with  the 
Common  European  Data  Spaces  in  order  to  facilitate  the  model  training  in  key  sectorial 
domains. 

Supercomputing services 

The third pillar of the “AI Factories” concerns dedicated supercomputing support services 
centres  for  AI  startups  and  the  research  and  innovation  ecosystem.  These  services  include: 
facilitating  access  to  supercomputers;  dedicated  supercomputer-friendly  programming 
facilities  and  algorithmic  support  for  the  further  development,  testing,  evaluation  and 
validation of AI training models and systems; and support for the development of a variety of 
novel  use  cases  and  emerging  applications  based  on  AI  in  key  areas  such  as  robotics  and 
manufacturing,  new  materials  (e.g.,  for  batteries),  connected  and  automated  driving, 
personalised health and care, biotech, climate change and adaptation.  

The  EuroHPC  JU  will  act  as  a  single  contact  point  at  the  EU  level  directing  startups  and 
interested users to a specific service centre. Every service centre will also create a one-stop 
shop  for  the  startups  to  facilitate  access  to  its  support  services.  Moreover,  Union-level 
cooperation of “AI Factories” will make computing power available as-a-service throughout 
the Union, as part of the support services. 

Talent and the science ecosystem  

A  key  aspect  for  the  success  and  further  deployment  of  “AI  Factories”  is  their  ability  to 
engage  and  attract  a  diverse  pool  of  talent,  including  students,  AI  startups,  researchers  and 
scientists, and the user community. The objective is to provide training that effectively equips 
them  with  the  necessary  skills  needed  to  use  EuroHPC  supercomputers  for  model  training 
and application development. For this, “AI Factories” should work in close partnership with 
startups, universities and research centres as well as key industrial sectors. The AI Factories 

23 Access to the EuroHPC supercomputers is also available to the public sector including for testing and evaluation purposes 
of generative AI models. 

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will  also  bring  the  scientific  community  closer  to  AI,  offering  specialised  user  support  and 
training to AI scientists and experts.  

Synergies at Union level 

All  “AI  Factories”  will  closely  interact  with  each  other  to  make  their  services  accessible 
across  Europe.  They  will  also  cooperate  with  the  EuroHPC  Competence  Centres  and  the 
EuroHPC Centres of Excellence, as well as with relevant AI initiatives of the Union, such as 
existing  hubs  of  AI  startups,  the  AI  Testing  and  Experimentation  Facilities24,  the  European 
central  AI  platform25,  the  European  Digital  Innovation  Hubs26,  the  Regional  Innovation 
Valleys  in  the  area  of  AI27,  the  AI-related  EIT  Knowledge  and  Innovation  Communities, 
relevant European research infrastructures and other related initiatives.  

Finally, while “AI Factories” are financially supported mainly by public funds, they are also 
open to pledges and investments by the private sector.  

3.2. Other supporting initiatives  

Improving the availability of and access to quality data 

The performance and capabilities of generative AI models today rely heavily on the quality 
and  diversity  of  the  data  they  are  trained  on.  Although  emerging  methods,  improved 
algorithms and the increasing availability of synthetic data may in the future reduce reliance 
on  massive  datasets,  high-quality  data  will  remain  of  paramount  importance  in  the 
development of increasingly sophisticated models.  

The Common European Data Spaces are therefore key to provide a varied data ecosystem 
for AI startups, integrating data  within and  across sectors like health28, media29, mobility30, 
tourism31, agriculture, construction, environment and manufacturing, as well as the data space 
for research and innovation (EOSC32).   

The Commission will strengthen its financial support for the Common European Data Spaces 
with new calls covering major sectorial application areas such as mobility and energy, being 
launched in 2024 under the Digital Europe Programme.  

Federating language resources: ALT-EDIC 

‘Large Language Models’ are advanced AI models that excel in understanding and generating 
human-like language. These capabilities, cutting across several applications, are key to the AI 
transformation. It is therefore important for the Union to ensure that these models embrace its 
linguistic  diversity,  and  that  initiatives  to  create  and  share  available  datasets  for  languages 

24 https://digital-strategy.ec.europa.eu/en/activities/testing-and-experimentation-facilities 
25 https://aiod.eu/ 
26 https://european-digital-innovation-hubs.ec.europa.eu/  
27 https://research-and-innovation.ec.europa.eu/news/all-research-and-innovation-news/results-regional-innovation-valleys-
calls-are-strong-interest-member-states-and-associated-countries-2023-10-19_en 
28  For  example,  the proposed  European  Health  Data  Space  (EHDS)  will  facilitate  access  to  quality data  to be  used in the 
in  health.  https://health.ec.europa.eu/ehealth-digital-health-and-
training, 
care/european-health-data-space_en 
29 As outlined in the Media and Audiovisual Action Plan, COM(2020) 784 final  
30 COM(2023)751 final 
31 Communication from the Commission, Towards a Common European Tourism Data Space: boosting data sharing and 
innovation across the tourism ecosystem, 2023/C 263/01 
32  https://research-and-innovation.ec.europa.eu/strategy/strategy-2020-2024/our-digital-future/open-science/european-open-
science-cloud-eosc_en 

testing,  and  validation  of  generative  AI 

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contribute to improving the capabilities of AI models in addressing the linguistic needs of the 
smaller Member States and language communities.  

To achieve these twin objectives, several Member States will join forces through the Alliance 
for Language Technologies European Digital Infrastructure Consortium (ALT-EDIC)33 
initiative. This will provide centralised access to language resources for the development of 
European ‘Large Language Models’, offering valuable tools in particular for Member States 
with  limited  language  data  and  empowering  users  to  engage  with  digital  content  in  their 
native  languages.  The  supply  of  high-quality  language  data  will  be  key  for  Union’s  model 
developers.  

As  part  of  its  efforts  to  support  the  European  Data  Strategy,  the  Commission  will  make 
available  high-quality  language  data  from  European  institutions  covering  all  European 
languages. 

Finally,  as  advanced  models  can  effectively  handle  multiple  types  of  data  simultaneously 
(text,  audio,  video,  images,  code,  etc),  ALT-EDIC  will  also  open  up  possibilities  for  more 
holistic and comprehensive AI applications across various domains.  

Supporting the development of algorithms 

Advanced AI algorithms can guide AI systems to not only process vast amounts of data but 
also to comprehend, generate, and take or underpin contextually appropriate decisions.  

To  support  the  continuous  refinement  and  innovation  of  algorithms,  the  Commission  has 
already put in place a number of initiatives. Most recently, in 2023 the Commission launched 
the Large AI Grand Challenge34 rewarding the AI  startups developing the best models with 
financial and computing power support.  
Moreover,  the  Commission  under  the  2024  Digital  Europe  Programme35  will  support  the 
scale-up  of  a  large  language  model  capable  of  addressing  all  European  languages  and 
facilitate its fine tuning by a large number of SMEs. This model is based on open source that 
holds the promise of wider access and greater transparency in terms of how it works, and its 
architecture  and  training  methodologies.  Open-source  models  exploit  European  strengths  in 
the field and encourage trust, while fostering innovation.  

Rigorous testing procedures are crucial for evaluating the performance of algorithms across 
various scenarios, datasets, and edge cases. They help identify and address biases in training 
data, prevent the generation of inappropriate content, etc. The Commission has set up several 
initiatives to facilitate the testing of AI algorithms in real world conditions through  Testing 
and  Experimentation  Facilities36,  offering  AI  developers  virtual  and  physical  facilities  in 
the  areas  of  agrifood,  manufacturing,  healthcare  and  smart  cities.  In  addition,  under  the  AI 
Act,  Member  States  will  put  in  place  AI  regulatory  sandboxes37  providing  a  controlled 
environment  for  startups  to  develop,  test  and  validate  innovative  AI  systems,  under  the 

33  The  European  Digital  Infrastructure  Consortium  (EDIC)  is  an  instrument  established  under  the  Digital  Decade  Policy 
Programme to offer Member States a stable framework to implement multi-country projects. Its main advantages are: legal 
personality, flexibility of design and relative speed in setting it up. This allows Member States participating in the EDIC to 
pool funds for large-scale, long-term digital infrastructures. https://digital-strategy.ec.europa.eu/en/policies/edic 
34 https://aiboost-project.eu/large-ai-grand-challenge/ 
35 https://digital-strategy.ec.europa.eu/en/activities/work-programmes-digital 
36 Testing and Experimentation Facilities (TEFs) https://digital-strategy.ec.europa.eu/en/activities/testing-and-
experimentation-facilities   
37  With  the  adoption  of  the  AI  Act,  one  regulatory  sandbox  will  be  set  up  in  all  Member  States.  These  sandboxes  will 
provide  a  controlled  environment  for  the  development,  testing  and  validation  of  innovative  AI  systems,  under  the 
supervision of competent authorities. In the sandboxes, companies will receive guidance on regulatory expectations and best 
practices to assist the future implementation of their systems. 

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supervision  of  competent  authorities.  In  2024,  the  Digital  Europe  Programme  will  also 
support the development of tools for testing and validation of AI models and systems, to be 
used in testing facilities and sandboxes. 

Finally, to advance research and unlock the potential of future generations of  AI models, in 
the  period  2024-2027,  the  Commission  will  support  through  Horizon  Europe,  projects  that 
could  enhance  the  capabilities  of  generative  AI,  enabling  it  to  effectively  exploit  and 
combine multimodal inputs and foster innovative learning approaches.  

Investing in AI startups and scale-ups 

Today more than 90% of the worldwide venture capital investment in AI, which shot up from 
EUR 2.7 billion in 2022 to EUR 24 billion in 202338, is done in the United States.  

Attracting investment  in  European AI startups is crucial  for  accelerating  the deployment  of 
advanced AI solutions. The collaboration between investors and these startups holds the key 
to unlocking new possibilities and driving the next wave of technological breakthroughs.  

This  is  why  the  Commission  is  putting  in  place  financial  instruments  to  support  these 
startups’  efforts:  first,  Horizon  Europe’s  European  Innovation  Council  will  continue  to 
provide, through its accelerator scheme, dedicated investment possibilities39 in the forms of 
grants and equity to support startups and attract investors; second, InvestEU will provide a 
dedicated  instrument  for  venture  capital  funds  to  support  scale-ups  and  SMEs.  Both 
instruments  are  designed  to  de-risk  and  crowd  in  private  investors.  In  addition,  the 
Commission continues to work on the development of the Capital Markets Union40, in order 
to improve financing for European startups and strengthen European economic security.  

Skills: leveraging on European capacities 

The  Union  needs  to  attract,  train  and  retain  generative  AI  specialists.  The  Commission  is 
already  supporting  an  Erasmus+  Alliance  for  Innovation,  ARISA  (Artificial  Intelligence 
Skills  Alliance41),  developing  a  sectoral  skills  strategy  on  AI  in  the  context  of  the  Pact  of 
Skills. The Commission will support training, skilling and reskilling activities in  generative 
AI,  for  example  by  supporting  dedicated  masters  and  doctoral  programmes  through  the 
Digital Europe Programme, including by targeting female participation42. In addition, it will 
involve education and training providers, including in its Large-Scale Partnership for digital 
skills  under  the  Pact  for  Skills,  as  well  as  the  Networks  of  Excellence43  and  their  doctoral 
programme. Horizon Europe, including through the European Research Council (ERC)44 and 
the Marie Skłodowska-Curie  Actions, will play a significant  role in  attracting and retaining 
AI talent. By acting as a prestigious “quality label” for research labs and financing ambitious 
AI-related  projects,  the  ERC  will  attract  both  EU  and  non-European  research  talents.  The 
programme  is  open  to  startups  and  SMEs  active  in  AI  to  team  up  in  consortia  with 
resourceful institutions worldwide to attract, train and retain AI talents. 

38 https://oecd.ai/en/data?selectedArea=investments-in-ai-and-data&selectedVisualization=vc-investments-in-generative-ai-
by-country 
39 EIC Accelerator - https://eic.ec.europa.eu/eic-funding-opportunities/eic-accelerator_en;  
40 https://finance.ec.europa.eu/capital-markets-union-and-financial-markets/capital-markets-union_en   
41 https://aiskills.eu/ 
42 In Europe, 16% of AI-skilled individuals are women. 
43  The  Networks  of  Excellence  in  AI bring  together  the  best  research  teams  in  Europe from  academia  and  industry 
solutions. 
challenges  hampering 
addressing 
to join forces 
 https://www.ai4europe.eu/Network-of-Excellence  
44 AI accounts today for around 15% of all ERC projects 

the  deployment  of  AI-based 

the  major 

in 

8 

 
 
 
The  European  Institute  of  Innovation  and  Technology  (EIT)  and  its  Knowledge  and 
Innovation  Communities  (KICs)  already  partner  up  with  leading  education  institutions, 
research  organisations  and  businesses.  The  EIT  Campus45  will  continue  to  support  the 
development  of  a  workforce  equipped  with  future-proof  competences.  As  part  of  the  New 
European  Innovation  Agenda46,  the  Deep  Tech  Talent  Initiative47  will  train  one  million 
Europeans by the end of 2025 in deep tech fields, including AI. 

The  application  of  generative  AI  also  holds  huge  promise  across  several  scientific  and 
industrial  sectors,  where  Europe  is  leading  and  has  a  breadth  of  talent  spanning  from 
researchers  and  scientists  to  practitioners  and  engineers.  Combining  their  sector-specific 
skills  with  those  of  generative  AI  specialists  around  several  ambitious  use  cases  can  be 
catalytic for the further development of these sectors. The Commission will therefore propose 
activities  under  the  Digital  Europe  Programme  to  enhance  talent  and  cultivate  the  required 
skills in a few strategic application areas. Examples of such areas include robotics, healthcare 
and  biotechnologies,  mobility  and  manufacturing.  The  Commission  will  encourage 
stakeholders implementing the above initiatives to closely engage with “AI Factories”. 

The Commission will also work with the European Digital Innovation Hubs specialised in AI 
to engage SMEs and the public administrations and deliver training that corresponds to their 
needs,  as  the  integration  of  AI  models  is  expected  to  have  a  multi-fold  impact  on  work, 
changing the skills requirements in all public and private sectors. 

Enabling AI processor chips  

The training of AI models relies on specialised AI chips but these are mostly designed and 
developed outside the Union. This is why the EU launched the European Processor Initiative 
in  2019,  aiming  to  develop  high-end  processors,  including  for  AI.  A  follow-up  major 
initiative  will  be  launched  in  2024  under  the  EuroHPC  JU,  to  address  the  design  and 
development of a new generation of microprocessors and AI accelerators. The first objective 
is to use this technology to fully power the first European post-exascale supercomputer. The 
second  objective  is  to  support,  through  the  Chips  JU,  the  embedding  of  such  processors  in 
automated and connected vehicles, future advanced communication systems such as 6G, and 
the  development  of  trustworthy  low-power  edge  AI  chips  which  are  crucial  for  numerous 
applications. Finally, the Commission is  also supporting the development of quantum chips 
for  quantum  computers  that  have  the  potential  to  boost  the  training  performance  of  AI 
models.  

4.  “GenAI4EU” for developing key AI applications  

The Union can leverage its strategic leadership across diverse industrial and scientific fields, 
including AI, to develop high-impact AI-based applications. To harness the benefits of the AI 
transformation, the Commission will launch “GenAI4EU”, a landmark initiative to stimulate 
the  uptake  of  generative  AI  across  the  Union’s  fourteen  strategic  industrial  ecosystems, 
supporting the transition pathways outlined in the EU Industrial Strategy48. The initiative will 
encourage  the  development  of  large  open  innovation  ecosystems  fostering  collaboration 

45 The EIT Campus currently includes over 200 courses in 28 languages and involves 164 education, research, and business 
partners, https://eit-campus.eu/ 
46  A  New  European  Innovation  Agenda,  COM  (2022)332,  https://research-and-innovation.ec.europa.eu/strategy/support-
policy-making/shaping-eu-research-and-innovation-policy/new-european-innovation-agenda_en      
47 EIT Deep tech talent initiative, https://www.eitdeeptechtalent.eu    
48 COM(2021)350 final 

9 

 
 
 
 
between AI startups and deployers of AI in industry and the public sector.49 This will include 
industrial applications such as manufacturing, while also reflecting the Union’s commitment 
to  greening  its  economy  and  addressing  climate  change.  “GenAI4EU”  will  include  key 
application areas, such as the ones listed below, each benefitting from the “AI Factories” and 
the relevant high-quality data in the Common European Data Spaces.  

The initiative will support the development  of key applications  leveraging generative AI to 
improve their performance or their capabilities. The newly established AI Office (Section 5) 
will  monitor  the  progress  in  developing  these  strategic  applications  through  concrete 
implementation targets. Such monitoring activity will be linked to the assessment that will be 
conducted through the European Transition Pathways Platform50.  

Robotics  
Today the Union is a world leader51 in industrial and service robotics. In particular the Union 
excels  in  areas  such  as  safe  physical  human-robot  interactions,  advanced  robotics 
manipulation and aerial robotics, thanks to its world-class expertise in mechatronics52.  

Generative  AI  enhances  the  capabilities  of  robots  in  terms  of  learning,  interaction  and 
operation, making them more adaptable, efficient, and effective  across  diverse applications. 
More specifically, generative AI can help robots learn from their experiences. 

Generative  AI  can  also  simulate  realistic  environments  for  robot  training,  especially  in 
challenging environments such as nuclear or space environments. It can also optimise robot 
designs  for  specific  tasks,  environments,  or  efficiency  purposes;  or  it  can  enhance  robot 
planning  capabilities  to  predict  the  outcomes  of  different  actions.  In  Human-Robot 
Interaction, generative AI can enhance the robot’s ability to understand and respond to human 
actions. 

The  combination  of  advanced  mechatronics  with  the  impressive  cognitive  capabilities  of 
generative AI will underpin a new wave of breakthroughs that promises to propel the Union 
to new levels of leadership in robotics. 

The  Commission  will  support  AI-enabled  advanced  robotics  applications  through  Horizon 
Europe and its Public Private Partnership on AI, Data and Robotics.53 

Healthcare  

Generative AI holds the potential to revolutionise healthcare. In personalised medical care, it 
will  help  provide  tailormade  healthcare  solutions  to  patients  based  on  their  unique  genetic 
lifestyle  factors.  It  can  also  greatly  benefit 
composition,  and  environmental  and 
epidemiological surveillance, pandemic prevention, and the response to health threats. 

The  potential  impact  of  generative  AI  in  healthcare  has  so  far  been  most  prominently 
prototyped, particularly in applications like radiology, screening and early disease detection, 

49 This will build on the work of the European Clusters Collaboration platform and the Enterprise Europe Network. 
50  European  Transition  Pathways  Platform  will  monitor  the  green  and  digital  transformations  across  various  industrial 
ecosystems, and foster collaboration to accelerate the transition.   
51 The EU robotics industry, with 82,000 industrial robots installed in 2021, is the second-largest global region after China. 
The European Service Robots Market is set for significant expansion, projecting a 14% CAGR by 2026, with the EU playing 
a  prominent  role  across  diverse  sectors.  European  service  robot  manufacturers  hold  a  significant  position  in  the  global 
market, constituting approximately 290 out of the 700 registered companies supplying service robots. https://ifr.org/  
52 Boosted by the world largest civilian robotics programme in the world initiated by the Commission. 
53 The ADRA PPP is benefiting from EUR 2.6 billion Horizon Europe and private funding through 2021-2027, https://adr-
association.eu/  

10 

 
 
 
accurate  diagnoses,  and  personalised  treatments  as  well  as  in  streamlining  of  healthcare 
delivery processes.  

Several EU startups are  developing generative AI solutions for a vast number of  healthcare 
applications54  such  as  improved  accuracy  and  robustness  in  radiology  thanks  to  the 
generation of synthetic data55, or improved efficiency in emergency call processing56. 

The  Commission  will  support  relevant  data  spaces,  namely  the  European  Genomic  Data 
Infrastructure  and  Cancer  Image  Europe,  given  their  importance  for  the  development  of 
future generative models for healthcare. The Virtual Human Twins initiative57 will use these 
data  spaces,  among  others,  to  train  generative  AI  models  that  take  into  account  biological 
processes at different levels  within the human body – from molecules and tissues to organs 
and  the  entire  body.  This  will  help  speed  up  clinical  trials  of  new  medicines  and  optimise 
patient  treatments.  In  addition,  the  Commission  has  launched  an  AI  Testing  and 
Experimentation Facility58 in healthcare. 

As  trust  is  essential  for  the  successful  take-up  of  innovative  solutions  in  healthcare,  the  AI 
Act  complements  the  existing  sectoral  legislation,  such  as  the  medical  device  and  in  vitro 
diagnostic medical device regulations59, by providing additional safeguards for safety and the 
respect of human rights by AI systems used.  

Biotechnologies and chemicals 

By  combining  excellence  in  biotechnology  and  AI,  the  Union  has  a  unique  opportunity  to 
reap  the  huge  benefits  that  generative  AI  is  expected  to  bring  in  various  sectors  such  as 
materials research, chemicals or agrifood. 

The advent of generative AI is expected to lead to significant innovation in the biotech and 
pharmaceutical  industries.  It  holds  the  potential  to  generate  synthetic  genetic  data  in  the 
absence  of  real  data,  generate  new  or  analyse  existing  gene  sequences  to  help  understand 
complex genetic diseases or facilitate drug discovery, as seen in recent breakthroughs on AI 
supported antibiotic development to fight antimicrobial resistance. 

Similarly,  rapid  developments  can  be  expected  in  the  wider  field  of  synthetic  biology,  for 
example to design new genetic sequences with desired proprieties that can produce a specific 
drug. Other examples include production of sustainable fabrics, cheese,  cell-cultured meats, 
plant-based meat alternatives, etc.  

A Dutch startup is using generative AI to help biologists design improved proteins, cutting by 
50% the R&D time needed to design such proteins.60 This innovative approach has attracted 
the  attention  of  leading  drug,  chemical,  food  and  materials  development  companies  and 
mobilised an investment of EUR 30 million. 

In  2024,  the  Commission  will  launch  an  initiative  on  biotechnology  and  biomanufacturing 
which will also involve the use of AI.  

54 https://sifted.eu/articles/europe-generative-ai-startups   
55 https://ryver.ai/   
56 https://www.corti.ai/  
57 European Virtual Human Twins Initiative - https://digital-strategy.ec.europa.eu/en/policies/virtual-human-twins 

59 Regulation (EU) 2017/745 on medical devices and Regulation (EU) 2017/746 on in vitro diagnostic medical devices 
60  Cradle  —  Design  Better  Proteins,  Cradle  –  Cradle  raises  $24M  Series  A  and  signs  partnerships  with  industry  leaders 
https://www.cradle.bio/blog/cradle-raises-24m-series-a-and-signs-partnerships-with-industry-leaders 

11 

 
 
 
 
Similarly to the healthcare sector, in biotech the AI Act will guarantee the use of trustworthy 
AI  and  ensure  the  transparency,  safety  and  required  human  oversight.  In  addition, 
complementary  regulations  ensuring  cybersecurity  and  privacy  are  key  for  biotechnology 
developments,  mitigating  the  risk  of  potential  misuse  of  such  technology,  particularly  in 
contexts like biowarfare.  

Materials and batteries  

Generative AI can be used for synthesising new material structures, predicting new material 
proprieties or designing new composite materials achieving specific mechanical,  thermal or 
electric  proprieties.  In  textiles,  generative  AI  can  be  used  to  predict  fabric  and  material 
properties based on fibre and  yarn data.  For batteries,  generative AI can  be  instrumental in 
radically  improving  performance  and  safety  (e.g.,  by  exploring  and  designing  different 
materials,  chemistries  and  cell  structures).  Such  breakthroughs  will  be  key  for  the  green 
transition. 

A Swedish startup is using generative AI to pioneer a transformative approach in the battery 
industry,  focusing  on  accelerating  the  development  of  innovative  battery  materials, 
optimising  cell  production  for  clients,  and  enhancing  sensing  and  analysis  methods  in 
manufacturing.61  

Generative  AI  can  also  be  a  valuable  tool  to  boost  hydrogen  production  as  a  clean  energy 
source,  across  its  entire  production  process.  From  designing  more  efficient  catalysts  to 
discovering new materials for enhanced hydrogen production and distribution, it contributes 
to optimising energy consumption.62   
The  EU-funded  Battery  2030+  flagship  initiative63  is  aiming  at  inventing  the  battery  of  the 
future.  It  uses  AI  to  speed  up  the  discovery  of  new  battery  materials  and  chemistries.  The 
flagship initiative is  supported through Horizon  Europe,  as  part  of the Batt4EU Partnership 
initiative. 

Manufacturing and engineering 

Generative AI will support the Union’s global competitiveness in manufacturing.  Using the 
huge  amount  of  industrial  data  produced  by  IoT,  it  will  improve  manufacturing  processes, 
significantly  reducing  waste  and  costs  and  ensuring  higher  quality  products  for  example  it 
will  improve  additive  manufacturing  and  3-D  printing.  It  can  also  be  used  to  adapt  supply 
chains to changing market conditions or develop greener manufacturing processes. 

A number of European manufacturing companies are already using generative AI to enhance 
their  operations  and  services.64  For  example,  one  company  employs  generative  AI  for 
controlling  manufacturing  machinery,  while  another  uses  it  for  inspection  tasks  in  the 
manufacturing  process.  The  Commission  will  support  European  Data  Spaces  for 
Manufacturing that can be used to train generative AI models. It will also support the use of 
AI in manufacturing and engineering applications through Horizon Europe and the  Made in 
Europe Public Private Partnership. In addition, the Commission has launched a Testing and 

61 https://northvolt.com/articles/northvolt-machine-learning/, https://www.ft.com/content/577920d3-1c60-4105-9503-
80e655280d3a  
62  Clean  Hydrogen 
bodies/search-all-eu-institutions-and-bodies/clean-hydrogen-joint-undertaking_en 
63  https://digital-strategy.ec.europa.eu/en/news/battery-2030-inventing-batteries-future  The  flagship  is  supported  through 
Horizon Europe, in the context of the Batt4EU Partnership initiative. 
64 https://www.bosch-presse.de/pressportal/de/en/bosch-to-use-generative-ai-in-manufacturing-260806.html  

-  https://european-union.europa.eu/institutions-law-budget/institutions-and-

Joint  Undertaking 

12 

 
 
 
Experimentation Facility65 in manufacturing, offering services to AI innovators, in particular 
startups and SMEs, to assess and validate AI solutions, including those based on generative 
AI, under real-world conditions66. 

Mobility 

Generative  AI  is  important  for  the  automotive  industry,  serving  as  a  valuable  tool  for 
advancing  autonomous  driving  and  manufacturing.  It  provides  advanced  capabilities  for 
training, simulation, and enhancing the decision-making processes of self-driving vehicles. It 
can,  for  example,  help  create  large  synthetic  datasets  and  realistic  driving  scenarios  for 
training  AI  algorithms,  making  autonomous  vehicles  more  robust,  safer  and  increasingly 
adaptable  to  traffic  conditions,  etc.  Its  combination  with  advanced  automotive  sensory  and 
safety control systems will reinforce the Union’s leadership in this area.  

Furthermore, generative AI can support coding and help the automotive industry address the 
challenges of increasing software complexity and shortage of skills. However, leveraging the 
forthcoming  innovations  will  require  a  significant  shift  in  the  electronic  and  software 
architecture of vehicles.  

Generative  AI  can,  in  more  general  terms,  optimise  transportation  systems,  identify 
inefficiencies  e.g.  in  supply  of  goods  and  predict  maintenance  needs,  for  instance  for  an 
improved traffic management in our cities. A number of European automotive companies and 
their  suppliers  are  already  using  generative  AI  models  and  systems  to  test  and  validate 
performance and safety and to personalise vehicle experience. 67 

The Commission will support, through the Chips JU, the Vehicle of the Future initiative68 to 
enhance  industry  collaboration  on  the  next-generation  vehicle  software  and  electronics 
platforms.  

Climate change and environmental sustainability  

Generative AI is revolutionising the development of extreme weather and climate prediction 
systems,  an  area  where  the  Union  has  been  a  frontrunner  in  employing  traditional  climate 
modelling and simulation algorithms. Generative AI has also improved our capacity to model 
the  state  of  the  environment  (water,  air,  soil  biodiversity)  and  assess  the  impact  of  the 
economy on natural resources. It can also make weather forecasting more accurate, detailed, 
and adaptable, contributing significantly to disaster preparedness, agriculture, transportation, 
and other sectors reliant on weather predictions.  

The Union needs to seize these opportunities to maintain its leadership in this field at a time 
when  environmental  monitoring,  predicting  extreme  weather  events  and  supporting  climate 
mitigation and adaptation is more vital than ever. 

A  German-based  startup  is  using  AI  to  automate  assessment  of  environmental,  social,  and 
governance criteria to support EU companies in their sustainability reporting requirements.69 

65 https://ai-matters.eu/  
66  The  EIT  is  running  a  series  of  end-to-end digitalised  production  testbeds  in  several  EU  Member  States  where  startups, 
scale-ups,  research  and  technology  organisations,  universities  and  industry  partners  can  collaborate  and  test  their  ground-
breaking products and digital services. 
67  https://prod.ucwe.capgemini.com/wp-content/uploads/2023/07/Final-Web-Version-Report-Harnessing-the-Value-of-Gen-
AI.1.pdf   
68 This initiative represents a total investment of around €250 million in 2023-2024 by the EU, Member States and industry, 
across the Chips JU, CCAM and 2ZERO partnerships. 
69 https://unreasonablegroup.com/ventures/briink  

13 

 
 
 
The Commission will support the Green Deal data space that will make public and privately 
held data accessible for AI-driven solutions and contribute to climate mitigation / adaptation 
and environmental sustainability.    
The Union’s Destination Earth initiative70 will carry out activities towards the creation of an 
open-source  generative  model  for  climate  modelling.  This  work  will  also  support  the 
development of the Union’s AI industry by enabling industrial partners, particularly AI SMEs 
and startups, to train and apply their models in applications of societal relevance. 

Once  the  system  becomes  fully  operational,  the  Commission  will  seek  to  make  it  widely 
available to the global community and international organisations.  

Virtual Worlds and Digital Twins   

Generative AI is an essential technology for the development of realistic, creative, immersive 
and  interactive  virtual  worlds.  For  example,  in  the  cultural  and  creative  industries,  in 
particular  in  gaming  and  entertainment,  this  can  enable  personalised  experiences,  remove 
language barriers and empower AI-driven creativity.   

Generative AI will also play a role in virtual reality applications applied in smart cities, from 
supporting  tourism,  retail  and  culture  to  optimising  transportation  systems  or  addressing 
sustainability challenges in cities. 

Innovative startups, for example in Sweden, are already offering AI-run digital twins to train 
and test autonomous solutions faster compared to conventional methods, e.g. in mobility.71  

transition 

technological 

In its recent Communication on Web 4.0 and virtual worlds72, the Commission presented the 
Union’s  plan  for  a  ground-breaking 
towards  a  seamlessly 
interconnected  world73.  The  forthcoming  European  Public  Private  Partnership  on  Virtual 
Worlds  will  support  AI-enabled  advancements  in  virtual  reality  applications.  In  2024,  the 
European  Innovation  Council  Accelerator  Challenge  will  also  provide  support  for  enabling 
virtual  worlds  in  industry.  Furthermore,  the  Commission  has  launched  a  Testing  and 
Experimentation Facility74 in the area of smart cities and communities, offering services to AI 
innovators to assess and validate AI solutions under real-world conditions. 
The  CitiVERSE  EDIC75  on  Local  Digital  Twins,  involving  several  Member  States  and 
supported by the Commission, will foster the use of generative AI in smart cities applications. 
These  include  simulation  of  possible  scenarios  such  as  the  impact  of  changing  traffic 
conditions  on  air  quality,  decarbonisation  and  congestion  and  more  broadly  on  greening 
cities.  It  will  also  work  on  generative  AI-based  virtual  reality  applications  to  improve 
interaction with citizens, e.g. to actively consult them on planned urban changes. This EDIC 
will use the Data Space for Smart and Sustainable Cities and Communities as well as other 
relevant  Common  European  Data  Spaces,  for  instance  the  energy,  mobility  and  green  deal 
data spaces.  

Cybersecurity   

70 https://destination-earth.eu/  
71  https://repli5.com/  
72  COM(2023) 442 final   
73 The European Citizens’ Panel on Virtual Worlds provided valuable input; European Citizens’ Panel on Virtual Worlds : 
Final Report: https://citizens.ec.europa.eu/system/files/2023-11/ECP%20on%20Virtual%20Worlds_Final%20Report.pdf 
74 https://citcom.ai/   
75  https://eurocities.eu/latest/launch-of-european-funding-instrument-to-upscale-digital-twins-towards-the-citiverse-through-
living-in-eu/  

14 

 
 
 
Generative AI can exponentially increase the capacity to learn and replicate patterns found in 
cyber threats or in vulnerabilities to improve the detection and the prediction of future threats, 
thereby  assisting  cybersecurity  professionals.  At  the  same  time,  generative  AI  can  also  be 
used  by  cybercriminals76  to  organise  sophisticated  cyber-attacks  and  other  malevolent 
activities. The prevalence of generative AI will therefore further increase the need to ensure 
systems’ robustness, their resilience as well as to prepare preventive and mitigation measures 
for  critical  asset  protection.  In  addition,  internal  security  actors  will  also  need  to  be  well 
equipped to address the use of generative AI by cybercriminals. 

A French cybersecurity startup77 recently launched   a  generative  AI  Assistant  that  already 
demonstrated  a  significant  impact  by  enabling  faster  and  easier  implementation  of  security 
policies, more accurate security alerts and faster decision-making, thus allowing to speed up 
remediation.  

Horizon Europe and the Digital Europe Programme will support the whole spectrum of AI-
centred  research,  innovation  and  deployment  activities  needed  to  effectively  respond  to 
cybersecurity  and  organised  crime  challenges  in  the  generative  AI  era.  This  includes  the 
development  of  AI  capabilities  in  cross-border  and  national  Security  Operations  Centres78. 
Other  collaborative  initiatives  will  continue  to  be  championed  under  the  umbrella  of 
Europol’s  Innovation  Lab.  The  forthcoming  AI  Act  will  provide  guardrails  for  the 
responsible use of AI systems in this area whilst safeguarding fundamental rights and safety. 

Aerospace 

In  the  aerospace  sector,  generative  AI  can  be  used  for  increasing  resilience  of  aerospace 
systems and services, enhancing their sustainability and safety.  

For  example,  in  aeronautics,  generative  AI  can  play  a  key  role  in  operations  and  training, 
autonomous flying and for designing new lightweight and robust materials for aircrafts and 
drones, including for their engines  and other components.  In space, generative  AI  could  be 
used for in-orbit servicing applications, Earth observation data analysis, collision avoidance, 
debris removal, space situational awareness and space traffic management.  

More  broadly,  generative  AI  has  the  potential  to  significantly  enhance  various  aspects  of 
space  applications,  from  improving  accuracy,  to  optimizing  spacecraft  design  and  enabling 
more autonomous and adaptive systems for space exploration. 

On  Earth,  autonomous  navigation  for  terrestrial  transport  will  be  based  on  AI-enabled  data 
fusion including GNSS positioning, navigation, and timing services, etc.  

The  Commission  will  support,  through  Horizon  Europe,  the  whole  spectrum  of  AI-based 
space  research  and  development  of  technologies  (including  computational  space-qualified 
components)  needed  to  effectively  respond  to  space  needs  and  future  EU  space  missions. 
Finally,  Copernicus  provides  daily  high-quality  Earth  observation  data,  serving  as  an 
important  source  of  training  for  generative  AI  with  applications  in  a  variety  of  fields, 
including environmental information services.   

Aerospace is an important element of the defence infrastructure. The European Defence Fund 
also  supports  generative  AI  applications  and  will  explore  possible  synergies  with 
infrastructures, services and evaluation activities supported by this AI package. 

76 Europol’s Innovation Lab’s Observatory has produced reports on both deepfake generation and exploitation of large 
language models for criminal purposes, www.europol.europa.eu  
77 https://www.gatewatcher.com/en/  

15 

 
 
 
 
AgriFood 

Generative  AI  holds  significant  potential  for  advancing  agricultural  practices.  In  livestock 
farming,  it  can  enhance  real-time  monitoring  and  disease  diagnosis  by  generating  more 
accurate models from extensive data on animal health and  behaviour, leading to earlier and 
more  precise  interventions.  For  crop  cultivation,  generative  AI  can  revolutionise  smart 
irrigation systems, synthesising data from various sources to optimise water usage and predict 
future  needs.  By  creating  and  simulating  complex  scenarios,  this  technology  can  not  only 
ensure  efficient  resource  management  but  also  improve  productivity  and  sustainability  in 
agriculture. 
The  Commission  supports  the  agricultural  data  space  and  a  Testing  and  Experimentation 
Facility79.  

Sciences 

Generative AI will have a profound impact on scientific discovery, ushering in a new wave of 
innovation  at  the  intersection  of  AI  and  all  scientific  domains80,81.  Areas  such  as  new 
materials design, fusion research, seismological research or astronomy are already integrating 
generative AI models in their research activities. 
Horizon  Europe  is  already  funding  many  projects82  that  are  using  AI  and  supercomputing 
facilities to solve scientific problems. Generative AI will bring such projects to new levels of 
productivity  and  capability  to  innovate.  The  Commission  will  propose  several  new  funding 
opportunities promoting AI in science in its future work programmes of Horizon Europe that 
would  help  to  reinforce  the  Union’s  position  as  a  leader  in  AI  for  science.  Moreover,  the 
Commission, with stakeholders in the ERA Forum, will develop guidelines on the responsible 
use of generative AI in research.  

The  Commission  requested  an  opinion  from  the  Scientific  Advice  Mechanism  (SAM)83  on 
how to accelerate its uptake by the scientific community.  

Public sector 

Generative AI has a strong transformative potential for the public sector in a wide range of 
areas,  such  as  health,  social  affairs,  education,  culture,  justice,  mobility,  waste  or  water 
management  and  urban  planning.  For  example,  it  can  enhance  the  efficiency  of  public 
administration,  facilitate  access  to  information  for  citizens  or  help  carry  out  market 
surveillance  tasks.  The  Commission  as  a  public  institution  itself  is  actively  pursuing  the 
development  and  use  of  trustworthy  AI  in  its  internal  operations,  fully  committed  to  early 
application of the principles of the AI Act, in line with the AI Pact.  

Generative AI can also allow citizens to enjoy improved access to general and personalised 
information on one’s entitlements, or simplified application processes. Digitalisation and AI 
can therefore contribute to transparency and simplification in the area of social protection, a 
commitment  existing  at  EU  level  through  the  Council  recommendation  on  access  to  social 

79 https://www.agrifoodtef.eu/  
80  Detailed  bibliometric  analysis  is  showing  that  the  EU  is  among  the  leaders  in  AI  for  science.  https://research-and-
innovation.ec.europa.eu/knowledge-publications-tools-and-data/publications/all-publications/trends-use-ai-science_en  
81 The policy brief “Artificial Intelligence in Science” shows that the EU is the global leader in terms of laboratory robots 
facilitating scientific discoveries, https://research-and-innovation.ec.europa.eu/research-area/industrial-research-and-
innovation/key-enabling-technologies/artificial-intelligence-ai-science_en 
82 
innovation  
83 https://scientificadvice.eu/advice/artificial-intelligence-in-science/ 

https://cordis.europa.eu/article/id/446030-artificial-intelligence-expanding-scientific-boundaries-and-enhancing-

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protection84.  Government  institutions  need  to  deploy  trustworthy  AI  solutions  to  ensure 
public confidence in their use.  

The  city  of  Heidelberg,  in  Germany,  has  launched  an  AI-based  chatbot85  developed  by  a 
German  startup86,  the  country’s  first  digital  citizen  assistant,  enabling  citizens  to  easily 
navigate  government  services  such  as  applying  for  a  new  identity  card,  getting  a  driving 
license, and registering a place of residence. 

Public procurement is an important lever to stimulate investments in AI, as stated in the New 
European  Innovation  Agenda.  By  embracing  innovation  procurement,  the  public  sector  can 
accelerate  the  development,  testing  and  deployment  of  innovative  AI-based  solutions.  To 
encourage  the  uptake  of  AI-based  solutions  by  public  authorities,  the  Commission  has 
contributed to the development of AI-specific contractual clauses tailored for public buyers, 
which  are  designed  to  streamline  the  procurement  process  of  AI  technologies  by  public 
authorities.  Additionally,  the  Commission  facilitates  the  Community  of  Practice  on  AI  and 
Public  Procurement  and  supports  experimentation  and  piloting  through  the  GovTech4all 
Incubator, providing public administrations the opportunity to test generative AI solutions.  

The Commission has also developed the Public Sector Tech Watch observatory dedicated to 
monitoring,  analysing  and  disseminating  the  use  of  emerging  technologies  including 
generative AI within the public sector in Europe. 

5.  Summary of key action points and conclusions 

The  development  of  generative  AI  is  of  great  significance  due  to  its  potential  for 
transformative  social  and  economic  impact.  To  leverage  its  benefits  and  mitigate  risks, 
Europe needs a thriving startup and innovation ecosystem capable of developing trustworthy 
AI  models  and  ground-breaking  applications  that  are  consistent  with  the  European  way  of 
life. This Communication outlines a number of actions to achieve this goal.  

In 2024, the Commission will:  

•  Support the setup of “AI Factories”, through the amendment of the EuroHPC Regulation; 
•  Accelerate the development and deployment of the Common European Data Spaces and 

make them available to the AI community; 

•  Support the development of large AI models and systems;  
•  Support  “GenAI4EU”  for  developing  novel  use  cases  and  emerging  applications  in 

several industrial and societal sectors; 

•  Support initiatives to strengthen the Union’s generative AI talent pool; 
•  Provide innovative financial instruments through the EIC Accelerator Programme and the 
InvestEU  guarantee  and  encourage  Member  States  and  private  investors  to  undertake 
similar investments for AI startups and scale-ups. 

In 2024, the Member States will: 

•  Establish the ALT-EDIC and the CITIVERSE EDIC with the support of the Commission. 

The above activities will be financed in the following way:  

84 2019/C 387/01 
85 https://www.heidelberg.de/Digitale-Stadt/startseite.html 
86 https://aleph-alpha.com/  

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•  Funding  for  “AI  Factories”:  through  the  EuroHPC  JU,  the  Commission  and  Member 
States  will  invest  a  total  amount  of  EUR  2.1  billion  in  acquiring  new  or  upgrading 
existing  EuroHPC  supercomputers  with  AI  capabilities,  the  creation  of  supercomputing 
services in AI and developing AI-oriented microprocessors and skills support.  

In  addition,  the  Commission  will  provide  financial  support  for  startup  incubation  and 
scale-up  activities  of  EUR  100  million  via  InvestEU  that  would  leverage  an  additional 
investment of EUR 1 billion.  

•  Funding  for  GenAI4EU:  the  Commission  will  support  under  Horizon  Europe  and  the 
Digital  Europe  Programmes  the  development  of  novel  use  cases  and  emerging 
applications in several industrial and societal sectors for an estimated amount of EUR 500 
million by 2027.  

In addition, Member States with the support of the Commission will invest around EUR 
100 million in ALT-EDIC and CitiVERSE EDIC. 

to  EUR  
This  package  will  generate  an  additional  public 
3  billion  in  generative  AI  until  the  end  of  this  multiannual  financial  programme  (2027),  as 
well  as  significant  private  investments,  including  EUR  1  billion  through  InvestEU.  This 
comes  on  top  of  existing  Union,  Member  State  and  private  investments  in  the  broader  AI 
domain.   

investment  of  close 

To  underpin  this  strategy,  a  strong  coordination  approach  across  the  Union  is  necessary, 
bringing together Member States, the Commission and all relevant stakeholders. In particular, 
as  foreseen  in  the  AI  Act,  the  Commission  will  set  up  an  AI  Office  which  will  supervise 
policy and regulatory activities in the area of AI. The AI Office will collaborate closely with 
Member  States,  the  EuroHPC  Joint  Undertaking  (JU),  and  key  stakeholders,  including 
players  in  industry,  academia  and  civil  society.  This  collaborative  effort  will  coordinate 
actions and combine resources, encouraging investment in the development, refinement, and 
integration of advanced models into key applications.  

Today, the rapid developments in AI are the source of intense international debates.  In line 
with  the  European  Economic  Security  Strategy,  the  Commission  will  continue  to  build 
partnerships  with  key  digital  economies  and  maintain  access  to  these  markets  that  will 
continue to be important sources of innovation. The AI Office will contribute to international 
cooperation  on  AI,  including  on  the  promotion  of  adequate  regulatory  guardrails  and  the 
democratic  governance  of  AI.  This 
includes  supporting  bilateral  cooperation  with 
international  partners,  including  in  the  AI  for  Public  Good  initiatives87,  where  the  EU  has 
concluded an agreement with the United States to address global challenges in the fields of 
climate change, natural disasters, healthcare, energy and agriculture88. 

The Union continues also its long-standing international engagement in different rules-based, 
multilateral  fora  and  international  organisations,  notably  the  UN,  OECD,  the  Council  of 
Europe, G7, G20 and the Global Partnership on AI.  

A  sense  of  urgency  in  implementing  the  actions  presented  in  this  Communication  is 
necessary, because the battle may not be to the strong, but this race will definitely be to the 
swift. 

87 The European Union and the United States of America strengthen cooperation on research in Artificial Intelligence and 
computing for the Public Good | Shaping Europe’s digital future (europa.eu). 
88 https://digital-strategy.ec.europa.eu/en/news/european-union-and-united-states-america-strengthen-cooperation-research-
artificial-intelligence 

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