TÜRKİYE’S ARTIFICIAL INTELLIGENCE PLAN

Türkiye’s 2026–2030 Artificial Intelligence Action Plan translates the national strategy launched in 2021 into measurable targets. The Plan treats energy, computing infrastructure, data, human capital, financing, and regulation as complementary inputs to production. By 2030, it targets 1 GW of AI/data center capacity, at least USD 10 billion in predominantly private-sector investment, 10,000 advanced AI specialists, and 100,000 AI application professionals. Through initiatives such as “GPU for All,” support for SMEs, and public procurement, the Plan also aims to broaden access to computing power and create demand for domestic solutions.

WHAT WILL THE ROLE OF THE STATE BE?

Under the financing model, the state’s role is not so much to undertake all investments itself as to act as a catalyst for mobilizing private capital. The USD 10 billion target is not a public fund, but rather the amount of predominantly private-sector investment expected to be mobilized. At the same time, a Research Fund of at least TRY 10 billion will support early-stage AI research, while a TRY 15 billion Growth Fund will support startups at the commercialization and scaling stages. For the latter fund, the target is to mobilize at least two units of private capital for every unit of public funding. In this way, the Plan seeks to establish a financing chain extending from research to commercialization.

DATA, COMPUTING, AND ENERGY INFRASTRUCTURE

Another critical input in the Plan is data. The objective is not merely to open up public-sector data, but to create a supply of standardized, up-to-date, secure data that can be used for AI development. In this context, the targets include at least 2,000 public datasets and 100 high-value data products accessible via APIs. At the same time, because the targeted 1 GW capacity will require substantial energy, low-carbon electricity, grid capacity, and energy efficiency are also becoming part of AI policy. This reflects the recognition that computing power cannot be transformed into economic value without complementary inputs such as data and energy.

WHERE DOES TÜRKİYE WANT TO POSITION ITSELF IN THE GLOBAL AI RACE?

Behind these targets lies a clear preference regarding Türkiye’s position in the global AI race. Rather than competing with the United States and China at the same scale in the race to develop general-purpose models, Türkiye aims to use AI to scale sectors in which it is already strong; to become a hub that produces trusted products and services, develops solutions in strategic sectors, and attracts investment and talent from its region (KÜME Araştırma, 2026). This objective also shapes the Plan’s understanding of digital sovereignty: securing critical computing, data, and human-capital capacity without disconnecting from the global technology ecosystem, while reducing the strategic risks created by external dependencies.

WHAT KIND OF ARTIFICIAL INTELLIGENCE ECOSYSTEM IS BEING BUILT?

The Plan conceptualizes the AI ecosystem as a set of interdependent vertical layers—Energy → Computing Hardware → Infrastructure → Models and Data → Applications—while talent, financing, and regulation and trust are defined as horizontal components supporting all layers. Since a bottleneck in a lower layer can constrain the capacity of the layers above it, Türkiye’s approach is based on developing complementary inputs simultaneously rather than supporting individual projects in isolation.

To assess the scale and policy design of Türkiye’s targets, they need to be considered alongside current AI infrastructure, investment, and human-capital policies in different countries. However, the figures included in the comparison below are not directly equivalent: some represent national policy targets, some public programs, some existing capacity, and others private-sector investment commitments.

Table 1. Comparison of Türkiye’s Artificial Intelligence Action Plan with Selected Country and Regional Policies

Country / Region	Compute Infrastructure	Investment / Financing	Human Capital	Comparison with Türkiye
Türkiye	Increase data centre capacity to 1 GW Provide compute infrastructure to researchers, startups and SMEs Provide 10 million GPU-hours of access per year	Mobilise US$10 billion in private-sector investment	Train 10,000 advanced AI specialists and 100,000 AI application professionals	Reference country
United States – Stargate	Target of 10 GW of AI infrastructure capacity by 2029 The 10 GW target was exceeded in 2026; capacity expansion continues through additional data-centre sites	US$500 billion investment commitment	No quantitative target for training AI specialists has been specified.	The 10 GW target is ten times Türkiye’s 1 GW target. However, Stargate is not a U.S. national action plan; it is a private-sector-led AI infrastructure initiative.
UAE – Stargate UAE	Stargate UAE: 1 GW AI infrastructure project First 200 MW planned to come online in 2026 Part of a larger 5 GW data-centre complex	Partnership involving G42, OpenAI, Oracle, NVIDIA, SoftBank and Cisco (major international technology partnership)	No quantitative target for training AI specialists has been specified.	Stargate UAE’s 1 GW capacity is the same order of magnitude as Türkiye’s 1 GW national target. However, Stargate UAE is a single infrastructure project, whereas Türkiye’s 1 GW figure is a national 2030 target.
Saudi Arabia – NEOM/DataVolt	Up to 1.5 GW of AI data-centre capacity First phase planned to become operational in 2028 Facility targeted to run entirely on renewable energy	US$5 billion investment by DataVolt for the first phase	No quantified human-capital target is specified in the cited source	Comparable in order of magnitude with Türkiye’s 1 GW target. However, 1.5 GW refers to a single NEOM project rather than a national target.
France	63 data-centre sites identified; 26 secured SoftBank committed to develop at least 3 GW, potentially rising to 5 GW, of AI data-centre capacity	€109 billion (approx. US$127.1 billion) in AI infrastructure investment commitments announced in 2025 SoftBank announced an initial €45 billion (approx. US$52.5 billion) investment in 2026 for 3.1 GW of AI data centre capacity; the broader programme could reach €75 billion (approx. US$87.5 billion) and 5 GW	Train 100,000 people in AI per year by 2030 Develop AI skills among 15 million professionals	France’s absolute scale is larger, but the figures are not directly comparable: Türkiye’s 1 GW is a national target, while France’s 3–5 GW figure is SoftBank’s investment commitment.
European Union	Shared AI compute network being built around 19 AI Factories Procurement launched for up to 7 substantially larger AI Gigafactories	Target to mobilise at least €20 billion (approx. US$23.3 billion) in private investment with up to €10 billion (approx. US$11.7 billion) in public support for Gigafactories	Develop and attract AI specialists to Europe; build skills through the AI Skills Academy	Both frameworks seek to expand AI infrastructure, mobilise private investment and develop human capital; the EU does so through a multi-country structure and at a larger aggregate scale.
South Korea	Target of more than 50,000 GPUs through public-private cooperation Construction of the National AI Computing Center has started; 15,000 AI chips targeted by 2028	More than KRW 2 trillion (approx. US$1.45 billion) in public-private investment for the national centre; private-sector share above 70%	Target of 200,000 AI specialists by 2030	Türkiye measures capacity primarily in GW, while Korea relies more heavily on GPU/AI-chip counts. Korea’s distinctive feature is developing compute infrastructure alongside a domestic AI-chip policy.
Japan	AI compute capacity at firms such as Sakura Internet, SoftBank and KDDI is being expanded with public support GENIAC provides compute resources to AI-model development projects Nine candidate regions selected for data-centre clusters	More than JPY 10 trillion (approx. US$62.8 billion) in public support for AI and semiconductors through 2030; target to mobilise more than JPY 50 trillion (approx. US$314.0 billion) in public-private investment over 10 years	Develop AI and digital specialists; strengthen AI-development capabilities through GENIAC	Türkiye places greater emphasis on explicit capacity and investment targets, while Japan integrates AI infrastructure with semiconductor policy, domestic technology companies and AI-development programmes.
Canada	Large-scale national AI supercomputer being developed Commercial AI data-centre capacity supported SME access to compute infrastructure supported	Up to C$700 million (approx. US$505 million) for commercial capacity; up to C$1 billion (approx. US$722 million) for public compute infrastructure; up to C$300 million (approx. US$216 million) for SME access	Develop AI capabilities and retain/attract AI talent in Canada	The approaches are similar; Canada additionally strengthens sovereign compute through a publicly owned national AI supercomputer.
Singapore	More than 70 data centres and over 1.4 GW of existing capacity New national AI supercomputer launched in June 2026 Additional 200 MW allocated to four data-centre projects in August 2026	More than S$1 billion (approx. US$787 million) in public investment for AI R&D and talent; additional S$12 billion (approx. US$9.45 billion) AWS cloud-infrastructure investment; more than S$300 million (approx. US$236 million) OpenAI ecosystem commitment; Google technical-infrastructure investment reached US$5 billion	Develop AI-bilingual talent, cultivate AI practitioners and strengthen broad-based AI capabilities across the workforce; no single quantitative national target is specified.	Türkiye also seeks to stimulate private investment; Singapore is distinguished by already-materialised global technology investment and selective capacity allocation under land and energy constraints.
United Kingdom	Isambard-AI and Dawn public supercomputers operational Target to increase public AI compute power at least 20-fold by 2030 At least 6 GW of data-centre capacity estimated to be needed by 2030; at least one designated AI Growth Zone targeted to exceed 1 GW	Up to £2 billion (approx. US$2.73 billion) in public compute investment through 2030; £44 billion (approx. US$60.0 billion) in private AI data-centre investment over the last 12 months; £500 million (approx. US$682 million) Sovereign AI support for domestic AI companies	Target to provide AI skills to 10 million workers	Policy instruments are broadly similar; the UK is further advanced in implementing public compute infrastructure and AI Growth Zones, building on a larger existing private-investment ecosystem.
Australia	Data-centre and AI compute capacity is expanding; Microsoft expanded its data-centre network from 20 to 29 facilities Government is mapping national compute capacity to identify infrastructure gaps and new investment needs Greater HPC access for domestic firms and researchers is targeted	Data-centre investments announced in 2023–2025 could exceed A$100 billion (approx. US$71.5 billion) Amazon A$20 billion (approx. US$14.3 billion), Microsoft A$5 billion (approx. US$3.58 billion); Firmus announced A$4.5 billion initially (approx. US$3.22 billion) and up to A$73.3 billion long term (approx. US$52.4 billion) for Southgate More than A$460 million (approx. US$329 million) in existing/committed public funding for AI and related ventures	AI skills are being developed through the national vocational education system; more than 150,000 enrolments recorded in AI/digital micro-credentials	Australia’s distinctive feature is linking large data-centre investments to requirements concerning new energy supply, grid costs, water use and local benefits.
Brazil	Procurement process launched for a national AI supercomputer worth about R$959 million (approx. US$186 million) New high-performance computers provided to universities for AI research in 2026	PBIA envisages about R$23 billion (approx. US$4.47 billion) in total investment for 2024–2028, mostly from public sources Procurement for a new national AI/HPC system worth about R$959 million (approx. US$186 million) launched in August 2026	R$129 million (approx. US$25.1 million) allocated to Trilhas IA By 2028, target to train 1,800 AI developers and 4,000 AI-tool users, for 5,800 qualified participants in total	Türkiye aims to build a more multi-channel compute ecosystem, while Brazil uses a publicly financed national supercomputer and research infrastructure as more central implementation instruments.
India	Shared AI compute infrastructure has reached 45,000+ GPUs By August 2026, 237 projects had been allocated 9.318 million GPU-hours of subsidised compute 20 domestic foundation-model projects are supported	₹10,371.92 crore* (approx. US$1.08 billion) in public funding allocated to the five-year IndiaAI Mission The programme jointly supports compute, domestic models, data, applications and startup financing	543 Data & AI Labs approved 686 AI fellowships awarded across 178 institutions	Both countries aim to open compute access to researchers and startups. In India, shared GPU infrastructure and subsidised usage have already been scaled operationally.
China	AI compute power increased 2.5-fold year on year by March 2026 National infrastructure is being developed around 8 national computing hubs and 10 computing clusters A large scientific AI computing cluster with 60,000 domestic AI accelerators became operational in April 2026	No single aggregate national investment budget has been announced for the AI+ Action Financial and fiscal support is being expanded, with long-term, patient and strategic capital encouraged toward AI investment	AI + Education Plan extends AI education across all levels Universities are expanding common foundational AI courses and interdisciplinary programmes Target to increase the scale and quality of AI human capital by 2030	Absolute capacity is not directly comparable because of the scale difference. Türkiye is expanding the ecosystem through capacity, GPU-access and private-investment targets; China is integrating its much larger existing infrastructure into a national compute network, scaling domestic AI accelerators and linking compute with a broader technology-industrial policy across industry, science and education.
Germany	More than 2,000 data centres and about 3 GW of existing capacity Target to at least double total data-centre capacity and quadruple AI/HPC capacity by 2030 JUPITER supercomputer operational Germany aims to attract at least one EU AI Gigafactory investment	Private investment is a major driver; one large German company announced €11 billion (approx. US$12.8 billion) for new data centres in Brandenburg Federal policy seeks to accelerate investment by improving land, energy, grid and permitting conditions No definitive investment amount has yet been allocated to Germany for an EU AI Gigafactory	Hightech Agenda seeks to develop AI talent both at the research frontier and across the broader workforce AI transfer among universities, research and industry, and international talent attraction are emphasised	Policy instruments are similar: both address capacity growth, private investment, compute access and the investment environment. Germany is expanding from an existing base of about 3 GW and operational HPC such as JUPITER, while integrating this with EU AI Gigafactory and technological-sovereignty policy.
Spain	MareNostrum 5 is operational at the Barcelona Supercomputing Center (BSC); a €129 million (approx. US$150 million) upgrade has been contracted to expand its AI capabilities Spain has two EuroHPC AI Factories: the BSC AI Factory in Barcelona and 1HealthAI at CESGA in Galicia The BSC AI Factory is a multinational initiative involving Spain, Portugal, Türkiye and Romania	€1.5 billion (approx. US$1.75 billion) in additional public funding for the 2024 AI Strategy, bringing the framework to €2.1 billion (approx. US$2.45 billion) including the previous €600 million (approx. US$700 million) €720 million (approx. US$840 million) in public investment plus a €300 million (approx. US$350 million) EuroHPC contribution approved for the Gigafactory Public-private consortium expected to mobilise up to €5 billion (approx. US$5.83 billion)	€600 million (approx. US$700 million) for AI research/talent programmes, plus €160 million (approx. US$187 million) for scholarships and specialised training AI Factory network provides training and technical support to startups and SMEs	Both countries combine public compute capacity, SME/researcher access, private investment and domestic model development. Spain is building on MareNostrum 5 and two operational European AI Factories, while advancing a 2026 Gigafactory initiative; Türkiye is also a partner in the BSC AI Factory, so that infrastructure should not be treated as exclusively Spanish in a bilateral comparison.

Notes: Approximate U.S. dollar equivalents use 25 August 2026 reference rates. EUR, GBP, JPY, KRW, CAD, SGD and AUD conversions are derived from ECB reference rates (EUR/USD 1.1662; EUR/GBP 0.85550; EUR/JPY 185.70; EUR/KRW 1,612.94; EUR/CAD 1.6163; EUR/SGD 1.4814; EUR/AUD 1.6303). BRL uses Banco Central do Brasil PTAX selling rate (US$1 = R$5.1490); INR uses the RBI reference rate (US$1 = ₹95.7143). *1 crore = 10 million Indian rupees. Original-currency amounts are retained; USD equivalents are rounded.

When the countries in the table are considered together, it becomes clear that countries in the AI race combine computing infrastructure, energy, human capital, data, financing, and domestic technological capacity with different priorities. This is where the fundamental distinction emerges: some countries prioritize building AI infrastructure at global scale, others focus on strengthening domestic technological production capacity, while still others prioritize rapidly diffusing AI adoption throughout their existing economic structures.

WHAT PATHS IS THE WORLD TAKING IN AI?

In the United States and Gulf countries, large-scale private capital and data center investments stand out, while in Japan, South Korea, and China, computing capacity is addressed as part of a broader industrial policy alongside semiconductors, domestic hardware, and technology companies. European countries display a different combination: France and the United Kingdom seek to attract major private investments through energy, land, and designated investment zones, while Germany and Spain integrate national capacity with Europe’s shared AI and high-performance computing infrastructure. In countries such as India and Canada, making computing power accessible to researchers, startups, and businesses is a more prominent policy instrument. There is therefore no single successful “national AI model”; countries pursue different paths depending on their existing industrial structures, energy resources, technology companies, and capital capacity. This diversity is also consistent with the OECD’s assessment that countries are developing different investment strategies based on their AI objectives (OECD, 2023).

WHERE DOES TÜRKİYE FIT INTO THIS PICTURE?

Türkiye’s approach seeks to combine several policy instruments within a single framework. On the one hand, as in the examples of France and the United Kingdom, there is an objective to mobilize private investment in data centers; on the other hand, similar to India, there is an approach aimed at making computing power accessible to startups, SMEs, and researchers. Human capital, public-sector data, startup financing, and public procurement are also used as complementary instruments to facilitate the diffusion of this infrastructure throughout the economy.

For Türkiye, the central issue appears to be specialization and capacity building. This is also the most important question that the international comparison raises for Türkiye: to what extent will Türkiye be able to transform the AI capacity it builds into economic and technological capacity? A key strength of Türkiye’s Action Plan is that it does not reduce the issue solely to the question of “how much computing power will be built?” The Plan’s more ambitious objective is to turn computing power, data, talent, energy, and financing into components of the same production system. International examples indicate that this is possible. What will ultimately determine Türkiye’s position in 2030 will be not so much whether it reaches 1 GW of capacity, but how much of that capacity can be translated into domestic value added, productivity gains, scalable AI companies, and exports.

REFERENCES

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Türkiye

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United States

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United Arab Emirates

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Saudi Arabia

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France

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European Union

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South Korea

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Japan

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22. Ministry of Economy, Trade and Industry. (2026, April 24). Selection of promising regions (regions passing the first screening) under the GX Strategic Area System [GX戦略地域制度の有望地域（1次審査通過地域）を選定しました]. Government of Japan. https://www.meti.go.jp/press/2026/04/20260424007/20260424007.html

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Canada

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Singapore

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37. Ministry of Digital Development and Information. (2026, February 25). MDDI’s response to PQ on data on total number and load capacity of data centres in Singapore. Government of Singapore. https://www.mddi.gov.sg/newsroom/mddi-s-response-to-pq-on-data-on-total-number-and-load-capacity-of-data-centres-in-singapore/

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39. Smart Nation Singapore. (2026). Update to National AI Strategy. Government of Singapore. https://isomer-user-content.by.gov.sg/39/cb52d9a0-0d6c-484d-96fe-571031b37eb7/NAIS_update.pdf

United Kingdom

40. Department for Science, Innovation and Technology. (2026, January 29). AI Opportunities Action Plan: One Year On. UK Government. https://www.gov.uk/government/publications/ai-opportunities-action-plan-one-year-on/ai-opportunities-action-plan-one-year-on

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42. Department for Science, Innovation and Technology. (2026). UK compute roadmap. UK Government. https://www.gov.uk/government/publications/uk-compute-roadmap/uk-compute-roadmap

43. Department for Science, Innovation and Technology. (2026). AI Skills Boost: Explainer. UK Government. https://www.gov.uk/government/publications/ai-skills-boost-explainer/ai-skills-boost-explainer

Australia

44. Ayres, T. (2026, July 15). AI in Australia’s interests. Ministers for the Department of Industry, Science and Resources, Australian Government. https://www.minister.industry.gov.au/t-ayres/media/ai-australias-interests

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47. Department of Industry, Science and Resources. (2025). Spread the benefits. Australian Government. National AI Plan. https://www.industry.gov.au/publications/national-ai-plan/spread-benefits

Brazil

48. Laboratório Nacional de Computação Científica. (2026, August 21). LNCC conduz implantação de supercomputador de inteligência artificial que ampliará a capacidade computacional do Brasil [LNCC leads implementation of artificial intelligence supercomputer that will expand Brazil’s computing capacity]. Governo Federal do Brasil. https://www.gov.br/lncc/pt-br/assuntos/noticias/ultimas-noticias-1/lncc-conduz-implantacao-de-supercomputador-de-inteligencia-artificial-que-ampliara-a-capacidade-computacional-do-brasil

49. Instituto de Pesquisas ELDORADO. (2026, June 22). MCTI lança programa de Residência em TICs para formar quase seis mil profissionais em inteligência artificial [MCTI launches ICT Residency program to train nearly six thousand professionals in artificial intelligence]. https://www.eldorado.org.br/noticia/mcti-lanca-programa-de-residencia-em-tics-para-formar-quase-seis-mil-profissionais-em-inteligencia-artificial/

50. Centro de Tecnologia da Informação Renato Archer. (2026, May 8). CTI Renato Archer pode receber novo supercomputador brasileiro [CTI Renato Archer may receive new Brazilian supercomputer]. Governo Federal do Brasil. https://www.gov.br/cti/pt-br/assuntos/noticias/cti-renato-archer-pode-receber-novo-supercomputador-brasileiro

51. Ministério da Ciência, Tecnologia e Inovação. (2025). Plano Brasileiro de Inteligência Artificial: IA para o bem de todos (2024–2028). Governo Federal do Brasil. https://www.gov.br/mcti/pt-br/acompanhe-o-mcti/transformacaodigital/arquivosinteligenciaartificial/plano-brasileiro-de-inteligencia-artificial-pbia-_vf.pdf/@@download/file

52. Ministério da Ciência, Tecnologia e Inovação. (n.d.). Plano Brasileiro de Inteligência Artificial [Brazilian Artificial Intelligence Plan]. Governo Federal do Brasil. https://www.gov.br/mcti/pt-br/acompanhe-o-mcti/transformacaodigital/plano-brasileiro-de-inteligencia-artificial

India

53. Press Information Bureau. (2026, August 13). Semiconductor and AI revolution: Powering the future. Government of India. https://www.pib.gov.in/FactsheetDetails.aspx?ModuleId=16&NoteId=150860&id=150860&lang=1&reg=46

54. Ministry of Electronics & Information Technology. (2026, July 29). IndiaAI Mission advances AI-driven governance and public service delivery through collaborative roadmaps, innovation challenges and capacity building. Press Information Bureau, Government of India. https://www.pib.gov.in/PressReleasePage.aspx?PRID=2291062&lang=1&reg=1

55. Press Information Bureau. (2026, March 25). IndiaAI Mission expands AI ecosystem with affordable compute and startup support. Government of India. https://www.pib.gov.in/PressReleasePage.aspx?PRID=2245069

56. Prime Minister’s Office, Government of India. (2026, February 19). PM’s remarks in Leaders’ Plenary Session during the India AI Impact Summit 2026. https://www.pmindia.gov.in/en/news_updates/pms-remarks-in-leaders-plenary-session-during-the-india-ai-impact-summit-2026/

57. Government of India, Prime Minister’s Office. (2024, March 7). Cabinet approves ambitious IndiaAI Mission to strengthen the AI innovation ecosystem. https://www.pmindia.gov.in/en/news_updates/cabinet-approves-ambitious-indiaai-mission-to-strengthen-the-ai-innovation-ecosystem/

China

58. People’s Daily Online. (2026, June 18). 国家发展改革委：我国智能算力规模将保持高速增长态势 [National Development and Reform Commission: China’s intelligent computing capacity expected to maintain rapid growth]. https://finance.people.com.cn/n1/2026/0618/c1004-40743220.html

59. The State Council of the People’s Republic of China. (2026, April 15). China aims to build an AI literacy system. China Daily. https://english.www.gov.cn/news/202604/15/content_WS69df29e6c6d00ca5f9a0a6b1.html

60. Cyberspace Administration of China. (2026, April 14). 我国最大规模科学智能计算集群投入使用 [China’s largest scientific intelligent computing cluster put into operation]. https://www.cac.gov.cn/2026-04/14/c_1777993675619656.htm

61. The State Council of the People’s Republic of China. (2026, April 10). China moves to bring AI into classrooms as it accelerates digital push. Xinhua. https://english.www.gov.cn/news/202604/10/content_WS69d8910dc6d00ca5f9a0a554.html

62. State Council of the People’s Republic of China. (2025, August 21). Opinions of the State Council on deeply implementing the “Artificial Intelligence Plus” action [国务院关于深入实施“人工智能+”行动的意见]. https://www.gov.cn/zhengce/content/202508/content_7037861.htm

Germany

63. European Commission, Representation in Germany. (2026, July 30). Ausschreibung für bis zu sieben KI-Gigafabriken in der EU veröffentlicht [Call launched for up to seven AI gigafactories in the EU]. https://germany.representation.ec.europa.eu/nachrichten-und-veranstaltungen/pressemitteilungen/ausschreibung-fur-bis-zu-sieben-ki-gigafabriken-der-eu-veroffentlicht-2026-07-30_de?prefLang=sv

64. Merz, F. (2026, June 23). Rede des Bundeskanzlers beim Tag der Industrie 2026 [Speech by the Federal Chancellor at the 2026 Day of Industry]. German Federal Government. https://www.bundesregierung.de/breg-de/aktuelles/kanzler-tag-der-industrie-2444560?view=renderNewsletterHtml

65. European Commission. (2026, March 25). Germany: Ericsson and Forschungszentrum Jülich advance 6G research using artificial intelligence and supercomputing. Shaping Europe’s Digital Future. https://digital-strategy.ec.europa.eu/en/miscellaneous/germany-ericsson-and-forschungszentrum-julich-advance-6g-research-using-artificial-intelligence-and

66. Federal Ministry for Digital Transformation and Government Modernisation. (2026, March 18). Bundesregierung beschließt Rechenzentrumsstrategie [Federal Government adopts data centre strategy]. https://bmds.bund.de/aktuelles/pressemitteilungen/detail/bundesregierung-beschliesst-rechenzentrumsstrategie

67. Federal Ministry for Digital Transformation and Government Modernisation. (2026). Nationale Rechenzentrumsstrategie [National data centre strategy]. https://bmds.bund.de/service/publikationen/nationale-rechenzentrumsstrategie

68. Federal Ministry for Economic Affairs and Energy. (2026). Annual economic report 2026. German Federal Government. https://www.bundeswirtschaftsministerium.de/Redaktion/EN/Publikationen/Wirtschaft/annual-economic-report-2026.pdf?__blob=publicationFile&v=1

69. Federal Government of Germany. (2025). Hightech Agenda Deutschland. https://www.bundesregierung.de/breg-de/aktuelles/hightech-agenda-deutschland-2366912

Spain

70. Government of Spain. (2026, July 1). The President calls for public-private partnership to drive forward Spain’s artificial intelligence gigafactory. La Moncloa. https://www.lamoncloa.gob.es/lang/en/presidente/news/Paginas/2026/20260701-spain-ai-gigafactory.aspx

71. Government of Spain. (2026, June 23). The Government of Spain allocates €6.2 billion to overhaul the long-term care system [See section: Investments in artificial intelligence and the photonic chips sector]. La Moncloa. https://www.lamoncloa.gob.es/lang/en/gobierno/councilministers/Paginas/2026/20260623-council-press-conference.aspx

72. Government of Spain. (2026, June 16). Desarrollo de un proyecto español para una gigafactoría de IA [Development of a Spanish project for an AI gigafactory]. La Moncloa. https://www.lamoncloa.gob.es/consejodeministros/referencias/Paginas/2026/20260616-referencia-rueda-de-prensa-ministros.aspx

73. Ministry for Digital Transformation and Civil Service. (2026, June 1). The Government extends the capabilities of the BSC-CNS Artificial Intelligence Factory to the whole of Spain with the implementation of five sector nodes. Government of Spain. https://digital.gob.es/en/comunicacion/notas-prensa/secretaria-digitalizacion-e-inteligencia-artificial/2026/06/el-gobierno-extiende-a-toda-espana-las-capacidades-de-la-factori

74. Government of Spain. (2026, January 26). Adjudicada la ampliación del superordenador MareNostrum 5 para impulsar la Factoría de IA del Barcelona Supercomputing Center [Contract awarded for the expansion of the MareNostrum 5 supercomputer to boost the Barcelona Supercomputing Center AI Factory]. La Moncloa. https://www.lamoncloa.gob.es/serviciosdeprensa/notasprensa/transformacion-digital-y-funcion-publica/Paginas/2026/260126-ampliacion-superordenador-ia-barcelona.aspx

75. European High Performance Computing Joint Undertaking. (2025, October 10). EuroHPC JU selects six additional AI Factories to expand Europe’s AI capabilities. European Commission. https://www.eurohpc-ju.europa.eu/eurohpc-ju-selects-six-additional-ai-factories-expand-europes-ai-capabilities-2025-10-10_en

76. Government of Spain. (2024, May 14). The Government approves the Artificial Intelligence Strategy 2024. La Moncloa. https://www.lamoncloa.gob.es/lang/en/gobierno/councilministers/Paginas/2024/20240514-council-press-conference.aspx

77. European High Performance Computing Joint Undertaking. (n.d.). Spain: BSC AI Factory. European Commission. https://www.eurohpc-ju.europa.eu/ai-factories/spain_en

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