AI, Data Centers, and Europe’s Hard Energy Choices

Europe wants to lead in artificial intelligence. At the same time, it has locked itself into legally binding climate targets and a push for greater energy independence. Both ambitions are serious, but together, they create friction.

That friction becomes visible the moment AI leaves the abstract and hits physical infrastructure. Data centers sit at the heart of Europe’s digital economy, turning electricity into computing power, services, and economic value. As AI workloads scale, they concentrate energy demand and waste heat in ways that put pressure on grids, planning authorities, and climate targets. eco’s study The Internet Industry in Germany 2025–2030 documents this shift in concrete terms, showing how rising data center demand, limited grid capacity, and tighter regulation are converging into a real planning and investment challenge for operators.

This article examines how Europe is responding. It starts with the EU-wide policy framework and then takes a closer look at Germany’s Energy Efficiency Act (EnEfG) as a national example. The question is not whether AI should expand, but how that expansion fits within Europe’s energy system and climate commitments.

In practical terms, the constraint is straightforward. AI is driving sharp increases in data center electricity demand, while European energy policy requires lower emissions and more efficient use of power. Regulation increasingly treats data centers as a leverage point where digital growth and sustainability can be brought back into alignment. Germany’s Energy Efficiency Act shows what that approach looks like when it becomes legally binding.

The energy equation of AI in Europe

AI data centers consume more energy because high-performance GPUs concentrate enormous computing power into dense racks that need constant electricity and intensive cooling.

Training and operating large AI models relies on high-performance computing and tightly packed GPU clusters. Compared to traditional enterprise IT, these systems draw far more power and do so continuously. This is not a short-lived spike. The eco study Spillover Effects of Data Centres: The Backbone of the AI Revolution in Germany describes how AI-driven compute establishes a lasting new baseline for electricity demand that grid planners, regulators, and operators must now factor into long-term decisions.

The shift is particularly clear at rack level. Where standard racks once operated at 10–20 kW, AI-ready installations are being designed for well above 100 kW. Klaus Landefeld, eco Board Member for Infrastructure and Networks, has described this as a structural change in how digital infrastructure is planned and interconnected, rather than a marginal technical upgrade.

High power density brings heat with it. Every additional kilowatt of compute has to be cooled, removed, or reused, and the cooling systems themselves consume substantial energy. The Orientation Guide to Power Density and Load Determination of Servers, Data Cabinets and Data Centres by Ulrich Terrahe, Peter auf dem Graben, and Marcus Pump details how power density, cooling design, and efficiency are now tightly linked planning variables rather than independent considerations.

In Germany, projections from The Internet Industry in Germany 2025–2030 suggest that installed IT load could grow by around 50 percent by 2030, reaching roughly 3.7 GW, with annual electricity consumption rising to 30–35 TWh. Thomas Amberg of Ynvolve places these figures in a global context, noting that AI and connected technologies could push data centers toward roughly 8 percent of worldwide electricity demand by the end of the decade.

This growth collides with the realities of renewable energy. Wind and solar fluctuate, while AI workloads expect constant availability. Jan Moll of the dtm group captures this tension succinctly, describing electricity as a limiting resource for digital infrastructure and data centers as a stress test for Europe’s energy transition. It is here that regulation moves from abstract policy to practical constraint.

European regulatory frameworks shaping AI-driven data centers

European regulation shapes AI data centers by setting binding efficiency, transparency, and reporting requirements that influence how facilities are designed, operated, and connected to energy systems.

The European Union (EU) increasingly treats digital infrastructure as part of its climate and energy system. Energy efficiency and transparency sit at the center of this approach. eco’s study Digital Transformation For More Sustainability links digital growth directly to environmental responsibility, framing data centers as contributors to climate solutions rather than passive energy consumers.

At the EU level, instruments such as the Energy Efficiency Directive (EED) and the European Green Deal translate climate objectives into obligations for energy-intensive sectors, including data centers. The study Data Centres in Europe – Sustainability & Digitalisation (Part 1) shows how this framing positions data centers as active elements in European energy policy, with efficiency metrics, such as power usage effectiveness, serving as comparable and enforceable benchmarks across the EU.

Simultaneously, European digital policy drives demand in the opposite direction. The AI Act, the Data Act, and sector-specific initiatives encourage data sharing, automation, and cloud mobility. Michael Hase of eco notes that policies designed to improve data portability and competition also increase demand for computing capacity.

Data centers sit at the intersection of these forces. They are expected to absorb rising workloads while meeting tighter efficiency requirements and integrating into local energy systems. The follow-up study Data Centres in Europe – Sustainability & Digitalisation (Part 2) points out that many of the technical and operational solutions already exist, from advanced cooling to smarter energy management, even if implementation remains uneven. Germany’s Energy Efficiency Act (EnEfG) shows how demanding this balance becomes once it is written into law.

Germany’s Energy Efficiency Act (EnEfG) as a case study

Germany’s Energy Efficiency Act (EnEfG), effective since late 2023, turns European energy and climate goals into enforceable rules for data centers. The law sets clear efficiency standards, requires renewable energy use, and mandates straightforward reporting. Dr. Béla Waldhauser of the Alliance for the Strengthening of Digital Infrastructures in Germany notes that pragmatic enforcement could greatly improve the sustainability of digital infrastructure. Efforts continue to align the German Energy Efficiency Act with the European Energy Efficiency Directive, particularly regarding PUE targets and waste heat rules.

Germany is often seen as a particularly strict implementer of EU rules, and its Energy Efficiency Act reinforces that reputation. eco and other industry groups have warned that moving faster and further than neighboring countries could weaken Germany’s attractiveness as a data center location, especially in a competitive European market.

The law requires ambitious PUE targets for new and existing facilities, binding quotas for waste heat reuse that rise step by step through 2028, and a transition to fully renewable electricity by 2027. Operators must also report detailed energy data to a European database, making performance visible and comparable across sites.

Waste heat reuse has proven particularly challenging. It forces operators to coordinate with municipalities, utilities, and planners beyond the data center perimeter. At the same time, the rise of AI workloads changes the technical conditions under which reuse becomes feasible.

Waste heat reuse and the AI effect

Waste heat reuse matters for AI data centers because higher-density workloads generate temperatures that make practical and economic reuse more realistic. For years, waste heat was an inconvenient by-product. Traditional data centers produced relatively low temperatures, typically between 25 and 35°C, which limited their usefulness for district heating. The eco white paper Waste Heat in the Data Centre, produced with the Network of Energy Efficient Data Centres (NeRZ), documents how early integration of waste heat planning can improve both efficiency and economic performance, drawing on national and international examples. Older heat networks, designed for much higher input temperatures, made reuse technically complex and costly.

AI workloads change that equation. Dense computing produces higher-grade waste heat, often approaching 60°C, which aligns far better with modern district heating systems. Experts from the German “RheinEnergie”, Manuel Gerdsmeyer and Emil Issagholian, explained how this reduces the need for energy-intensive heat pumps and improves overall system efficiency in sector coupling projects.

Projects in cities such as Frankfurt and Cologne show how this works in practice. The eco study The Internet Industry in Germany 2025–2030 highlights cases where data center waste heat already supplies residential and commercial buildings, including a Cologne facility designed from the outset to meet EnEfG targets years ahead of schedule.

What began as a regulatory requirement increasingly looks like infrastructure potential. Dr. Béla Waldhauser argues that waste heat can support municipal heat planning, reduce fossil fuel use, and create new location advantages for energy-intensive activities such as vertical farming.

The main challenge isn’t really the technology itself, but finding consumers who can make use of the heat generated. This issue is made more complex because data centers are often located far from district heating network feed-in points. Efforts are underway to match waste heat disposal requirements with the standards set by the European Energy Efficiency Directive (EED). The entire cycle – from supplying power to utilizing waste heat – could move faster if enough battery storage solutions were available.

Adapting infrastructure for compliance

Meeting European efficiency rules requires a rethink of how data centers are designed and operated, touching every layer of the infrastructure stack.

• Cooling: Air-based systems struggle with the heat loads generated by AI racks, which is why liquid cooling and similar approaches are becoming standard in new facilities. In some cases, AI also manages cooling itself. Alicja Niekrawietz of etalytics describes how AI-driven optimization at Equinix’s FR6 site in Frankfurt cut cooling energy onsumption by nearly half.
• Energy management: Regulatory reporting accelerates the adoption of real-time monitoring systems that allow operators to adjust workloads, fine-tune efficiency, and coordinate on-site generation or storage based on actual conditions.
• Connectivity: Ivo Ivanov, CEO of DE-CIX, argues that provider-neutral interconnection allows AI workloads to be placed where energy and infrastructure conditions align best, improving efficiency and reducing systemic risk.

Industry and policy perspectives

From the industry’s perspective, the regulatory shift is demanding. Colocation providers, in particular, point out that they are assessed on facility-level efficiency metrics while having limited control over customer hardware choices, a tension also discussed in eco’s work on power density and load planning.

At the same time, regulation has become a catalyst for operational change. Mandatory measurement and reporting turn energy data into a management tool rather than a compliance exercise. Operators who invest early in data-driven efficiency gain insights that would otherwise remain hidden, as etalytics’ Alicja Niekrawietz notes.

Several structural challenges remain. The study The Importance of Digital Infrastructures in Germany compares German data centers internationally and highlights persistent obstacles, including cost pressure, regulatory complexity, and long approval timelines. Grid connection approvals can take up to seven years, electricity prices remain higher than in Nordic markets, and the skills gap continues to widen. The eco study The Internet Industry in Germany 2025–2030 estimates that tens of thousands of additional specialists will be needed by the end of the decade.

Industry associations such as eco advocate pragmatic adjustments, from electricity tax relief to VAT exemptions for waste heat provided free of charge. Many stakeholders agree that continuous dialogue between policymakers and operators is essential if regulation is to remain workable as AI demand grows.

Europe’s strategic choice

Europe’s regulatory approach to AI infrastructure reflects a deliberate strategic choice to combine digital competitiveness with climate responsibility.

Rather than focusing on speed alone, Europe embeds sustainability, transparency, and trust into the foundations of its digital economy. Initiatives such as Gaia-X reflect this ambition, positioning digital resilience and freedom of choice as location factors for cloud and AI infrastructure, as eco’s Shipra Kren argues.

This approach offers potential advantages. Clear rules can create investment certainty, set standards, and attract organizations that value ESG performance. The risks are equally tangible. Oliver Süme, Chair of the Board of the eco Association, warns that complex or fragmented regulation could slow infrastructure investment and weaken Europe’s position in the global AI race.

The balance Europe strikes between ambition and constraint will shape whether AI becomes a driver of sustainable growth or another pressure point in an already stretched energy system.

References and further reading

Roland Broch is Senior Project Manager Digital Infrastructures and the contact person for the Data Center Expert Group at eco – Association of the Internet Industry.

Cáit Kinsella is a Project Manager for eco International Communications and part of the dotmagazine editorial team at eco – Association of the Internet Industry.