Europe Artificial Intelligence (AI) Optimised Data Center Market Size & Share Analysis - Growth Trends & Forecasts (2025 - 2030)

Europe Artificial Intelligence (AI) Optimised Data Center Market Analysis by Mordor Intelligence

The Europe Artificial Intelligence Optimised Data Center Market size is estimated at USD 17.39 million in 2025, and is expected to reach USD 53.93 million by 2030, at a CAGR of 25.40% during the forecast period (2025-2030).

Europe's AI data center market is evolving rapidly, driven by significant public and private investments. Initiatives like InvestAI aim to mobilize EUR 200 billion for AI gigafactories and infrastructure. The EU's Digital Europe Programme is allocating EUR 1.3 billion to enhance AI, cybersecurity, and digital skills. Additionally, the European AI Alliance promotes discussions on AI's societal impact. These investments are expected to train advanced AI models, provide high-performance computing resources, and foster innovation across industries. Future developments may focus on expanding AI capabilities, improving energy efficiency, and supporting emerging technologies.

Intel is investing USD 330.35 billion to strengthen Europe's semiconductor industry, addressing chip shortages and accelerating digital transformation. This initiative supports green technologies by enabling energy-efficient chips that reduce power consumption. These advancements will drive AI, High-Performance Computing, and data center growth. Future efforts are likely to emphasize sustainable innovations and enhanced computational capabilities to meet increasing data demands.

France has attracted nearly EUR 110 billion in private AI investments, with contributions from the UEA and Brookfield Corporation focusing on large-scale data centers. The European High-Performance Computing Joint Undertaking is developing supercomputers in France, Germany, and Italy to advance AI research and applications. These coordinated efforts position Europe as a leader in AI innovation. Looking ahead, Europe is expected to strengthen its data center infrastructure to support a broader range of AI applications and maintain its competitive edge in the global market.

Surging Demand for Sovereign-AI Compute Clusters across EU Member-States

Europe is experiencing a distinctive shift in AI deployment patterns, with organizations increasingly prioritizing sovereign infrastructure over hyperscaler solutions due to data governance concerns and regulatory requirements. This driver operates through the European Union's comprehensive data protection framework, including GDPR and the AI Act, which creates powerful incentives for keeping sensitive data and AI processing within European jurisdictions and under European control. The economic impact is substantial, with European cloud providers like OVHcloud, Deutsche Telekom, and Orange Business Services experiencing 35-45% year-over-year growth in AI workloads as organizations seek infrastructure that combines advanced GPU capabilities with guaranteed data sovereignty and regulatory compliance. This trend is creating opportunities for providers that can offer both the specialized hardware required for AI and the governance frameworks necessary for sovereignty, with the most successful implementations balancing performance, compliance, and cost-effectiveness

EU Green Deal & Carbon Border Adjustment Mechanism Driving Low-Carbon AI Power Sourcing
The European Union's comprehensive climate policy framework is creating powerful incentives for data center operators to secure low-carbon electricity, fundamentally reshaping energy sourcing strategies for AI infrastructure. This driver functions through multiple regulatory mechanisms, including the EU Emissions Trading System (ETS), the Carbon Border Adjustment Mechanism (CBAM), and the Corporate Sustainability Reporting Directive (CSRD), which collectively increase the cost of carbon-intensive energy while enhancing transparency around environmental performance. The economic impact is substantial, with carbon pricing adding EUR 80-100 per MWh to electricity costs from fossil fuel sources compared to renewable alternatives, creating a compelling financial case for low-carbon sourcing beyond pure sustainability considerations. This advantage is particularly significant for AI workloads, which can consume 10-20 times more power than traditional applications, making energy both a dominant cost factor and a key environmental consideration

Rapid Uptake of AI-Driven Energy-Optimisation Platforms among European Colo & Cloud Operators
European data center operators are at the forefront of adopting AI-powered management systems, creating a virtuous cycle where artificial intelligence helps optimize the very infrastructure that enables it. This driver operates through sophisticated software platforms that leverage machine learning algorithms to continuously optimize cooling parameters, power distribution, and workload placement based on real-time conditions and historical patterns. The economic impact is substantial, with these systems achieving energy savings of 15-25% compared to traditional management approaches, representing millions of euros in annual cost reductions for large facilities while significantly decreasing carbon emissions. The adoption rate in Europe is notably higher than the global average, with approximately 45% of major European facilities implementing AI-driven optimization systems in 2024, compared to a global average of 30%, reflecting the region's strong focus on both technological innovation and environmental performance in response to regulatory pressures and high energy costs

Availability of Horizon-Europe & IPCEI Grants for Exascale GPU Infrastructure

European Union funding mechanisms are creating powerful financial incentives for AI infrastructure development, establishing the region as a global competitor in advanced computing despite its historical disadvantages in semiconductor manufacturing. This driver operates through multiple coordinated programs: Horizon Europe with EUR 95.5 billion for research and innovation; Important Projects of Common European Interest (IPCEI) providing state aid exemptions for strategic technologies; and the Digital Europe Programme allocating EUR 7.5 billion specifically for digital infrastructure. The economic impact extends beyond direct funding to include the catalytic effect on private investment, with EU support typically leveraging 3-5 times its value in additional capital. The geographic distribution is strategically managed to strengthen AI ecosystems across the Union while addressing regional economic disparities, with particular emphasis on creating "innovation corridors" that connect academic research centers with commercial applications

Grid-Connection Moratoria in Amsterdam, Dublin & Frankfurt Hubs

The implementation of formal and de facto power allocation moratoria in Europe's primary data center hubs is creating critical bottlenecks that fundamentally constrain AI infrastructure growth despite strong demand. This restraint operates through a combination of regulatory decisions and physical grid limitations, with Amsterdam implementing a formal moratorium on new data center development in 2024, Dublin's EirGrid imposing connection queues extending to 2029, and Frankfurt's utility providers implementing prioritization systems that effectively halt new AI-focused projects. The severity of this constraint is amplified by the power requirements of AI workloads, which can demand 10-20 times more electricity than traditional applications, creating unprecedented challenges for urban grid infrastructure designed for less intensive uses. The economic impact extends beyond simple delays to include opportunity costs from deferred projects, competitive disadvantages as other global regions move faster, and strategic compromises as operators accept suboptimal locations to secure power availability

High CAPEX of Two-Phase Immersion Retrofits in Legacy Tier III Sites

The capital-intensive nature of implementing advanced two-phase immersion cooling technologies in existing facilities is creating a significant barrier to AI infrastructure expansion across Europe's established data center markets. This restraint functions through the technical and financial challenges of retrofitting legacy sites with immersion systems, which typically cost 50-70% more to implement in existing facilities compared to new builds due to structural modifications, service disruptions, and efficiency compromises. The economic impact is particularly significant for Tier III facilities built between 2010-2020, which represent approximately 60-65% of Europe's current data center capacity yet were not designed with the thermal demands of AI workloads in mind. The constraint creates a strategic dilemma for operators, forcing difficult choices between suboptimal cooling for AI workloads, expensive retrofits with uncertain returns, or new construction in potentially less advantageous locations, collectively limiting the market's ability to rapidly scale AI capacity in established hubs