What the EU initiative means for Greece, its technology ecosystem and the public.
Europe is building the computing infrastructure needed for the next generation of artificial intelligence, with AMD helping advance the processors, accelerators, networking and open software required to support this transformation. For Greece, this conversation is not starting from zero: the country is already part of Europe’s AI infrastructure through the Pharos AI Factory and the Daedalus supercomputer. The new AI Gigafactories initiative could expand that role, bringing more compute capacity, research opportunities and AI-enabled services to Greece and the wider South-Eastern European region. At the same time, the final locations of the future gigafactories have not yet been announced.
Contents
- Europe’s AI strategy and the AI Gigafactories initiative
- Greece’s position: from Pharos to the next generation of AI infrastructure
- AI Gigafactories explained: why Europe is investing in large-scale compute
- What the initiative could mean for Greek businesses, researchers and citizens
- AMD technologies for efficient and open AI infrastructure
- Energy, water and sustainability considerations
- Timeline and next steps
- Greece’s opportunity in a European AI ecosystem
Europe’s AI strategy and the AI Gigafactories initiative #
The European Union is strengthening its ability to develop and operate advanced AI systems on infrastructure located in Europe. The aim is not only to increase computing power, but also to support resilience, data protection, security, innovation and technological choice. The amended EuroHPC framework gives the EuroHPC Joint Undertaking a role in deploying and operating AI Gigafactories, alongside the network of AI Factories already being established across Europe.
On 30 July 2026, EuroHPC launched a call for consortia to establish and operate up to seven AI Gigafactories. The initiative is supported by up to €10 billion in European and national funding and is expected to unlock at least €20 billion in private investment. The facilities are intended to provide access to advanced computing for researchers, public authorities, start-ups, scale-ups, SMEs and established industries.
The tender deadline is 12 November 2026. The selection of consortia and the final host locations will follow the evaluation process. Greece is therefore part of an important European discussion.
Greece’s position: from Pharos to the next generation of AI infrastructure #
Greece already has a foundation on which to build. The Greek AI Factory, Pharos, was selected under the EuroHPC AI Factories initiative and is designed to connect academic and research organisations, the public sector and private companies. Its work focuses on practical AI applications in areas including health, the Greek language and culture, and sustainable development.
Pharos is linked to Daedalus, the high-performance computing system being developed in Greece. This gives Greek researchers and companies a route into European AI computing and helps connect national capabilities with the wider EuroHPC network. The Greek ecosystem also has a regional dimension: Pharos has been positioned as a hub for South-Eastern Europe, with connections to AI Factory antennas in Cyprus, Malta, North Macedonia and Serbia.
This is the most important point for understanding Greece’s role. Greece is already participating in the AI Factory layer, which supports experimentation, model development, testing and adoption. AI Gigafactories represent a much larger scale of infrastructure, designed for the most demanding training and inference workloads. Greece can benefit from the gigafactory network whether or not a facility is ultimately located on Greek territory, by contributing research, applications, skills, data expertise and regional connectivity.
AI Gigafactories explained: why Europe is investing in large-scale compute #
An AI Gigafactory is more than a very large data centre. It is a coordinated computing environment built to train, fine-tune and run advanced AI models at a scale beyond today’s typical research and enterprise systems. Each facility must combine large numbers of advanced processors with high-speed networking, substantial memory capacity, efficient cooling, reliable power and software that allows users to make productive use of the infrastructure.
The scale matters because modern AI systems move enormous amounts of data between processors, memory and storage. If any part of the system becomes a bottleneck, the whole facility can waste energy and time. For this reason, competitiveness will depend not only on the number of accelerators installed, but also on performance per watt, the efficiency of data movement, software portability and the total cost of operating the system.
What the initiative could mean for Greek businesses, researchers and citizens #
For Greek universities and research centres, access to European-scale compute could shorten the path from an AI research idea to a tested model or service. It could support work in Greek-language technologies, scientific research, climate and environmental analysis, health, agriculture, logistics and cultural heritage. It could also make it easier for Greek teams to participate in cross-border projects that require more computing power than a single institution can provide.
For start-ups and SMEs, the benefit is access. Training advanced models is expensive when companies must acquire and operate all the required infrastructure themselves. Shared European facilities can lower the barrier to experimentation, allow companies to test ideas before making large capital investments, and provide a route to scale when a product moves from prototype to production.
For the public sector, European AI infrastructure can support services that are more responsive to local needs while remaining aligned with European rules on data protection, security and trustworthy AI. In Greece, possible applications include public-service automation, better forecasting and planning, more efficient energy and transport systems, and tools that work well with the Greek language and national cultural data.
The public impact will depend on how access is organised and how projects are selected. The strongest outcome would be an ecosystem in which public institutions, researchers, companies and citizens benefit from the infrastructure, rather than a system that serves only the largest technology organisations. Skills, transparency, responsible data use and measurable public value will be as important as computing capacity.
AMD technologies for efficient and open AI infrastructure #
AI Gigafactories require a complete system architecture. AMD’s approach combines AMD EPYC processors, AMD Instinct accelerators, AMD Pensando networking solutions and AMD ROCm open software. Together, these components are designed to help infrastructure operators balance compute performance, memory, networking, software flexibility and energy efficiency.
AMD also promotes Sovereign AI: the idea that organisations should retain control over their data, models and infrastructure while preserving the freedom to choose among technologies and suppliers. For Europe and for countries such as Greece, this approach can reduce the risk of dependence on a single closed technology stack. Open software can also help universities, start-ups and public-sector teams adapt models and applications without having to rebuild their work around one proprietary environment.
Energy, water and sustainability considerations #
Large AI facilities require significant electricity, cooling and network infrastructure. This makes sustainability a central design question for Greece and for Europe. A credible AI Gigafactory must be judged by the useful work it delivers per unit of energy and water, not only by its peak computing capacity.
Efficient processors and accelerators, high-bandwidth networking, liquid cooling, advanced power management and workload optimisation can reduce the energy required for each AI operation. Facilities can also be designed to support circularity, minimise water use and explore the reuse of waste heat. Whether heat reuse is practical depends on location, local demand and the design of the surrounding energy system, but it illustrates the broader principle: AI infrastructure should be integrated into its environment rather than treated as an isolated building.
Timeline and next steps #
- July 2026: EuroHPC launches the call for AI Gigafactory consortia.
- 12 November 2026: Deadline for consortium proposals.
- After the deadline: Evaluation, selection and contracting of the successful consortia.
- Following selection: Detailed design, financing, site preparation, power and network integration, and deployment of the first systems.
For Greece, the near-term priority is to strengthen the capabilities already being developed through Pharos, Daedalus, universities, research centres, public bodies and technology companies. Greece can also position itself as a valuable regional partner by developing applications, talent and cross-border services that use European AI infrastructure.
Greece’s opportunity in a European AI ecosystem #
The AI Gigafactories initiative gives Greece a chance to build on an existing role rather than wait for a single announcement about location. Through Pharos and Daedalus, Greece is already connected to the European AI and high-performance computing landscape. The next step is to turn that infrastructure into lasting value: stronger research, more competitive businesses, better public services, new skills and AI applications that reflect Greek and regional needs.
Whether or not a future gigafactory is built in Greece, the country can be an active participant in the network. Its opportunity lies in combining infrastructure with expertise, open technology, responsible governance and practical use cases. In that sense, Europe’s AI Gigafactories are not only a construction programme. They are an invitation to build a wider AI ecosystem in which Greece can play a meaningful role.
About AMD #
AMD (NASDAQ: AMD) drives innovation in high-performance and AI computing to solve the world’s most important challenges. Today, AMD technology powers billions of experiences across cloud and AI infrastructure, embedded systems, AI PCs and gaming. With a broad portfolio of AI-optimized CPUs, GPUs, networking and software, AMD delivers full-stack AI solutions that provide the performance and scalability needed for a new era of intelligent computing. Learn more at www.amd.com.