As the artificial intelligence (AI) boom intensifies, Europe stands at a strategic crossroads. With the European Union aiming to triple its data center capacity within the next decade, the continent faces a critical constraint—its electricity grids. A new report by Ember, Grids for Data Centres in Europe, underscores that proactive grid planning will determine whether Europe can compete in the global AI race or fall behind under the weight of its infrastructure limitations.
Data Centers: The Pillars of the AI Economy
Data centers are not just large warehouses of servers; they are the operational core of the AI-driven digital economy. From training complex AI models to managing cloud-based services, they provide the computational muscle required for innovation, productivity, and economic growth. But they also represent one of the fastest-growing sources of electricity demand in Europe, with consumption projected to soar from 96 TWh in 2024 to 236 TWh in 2035—a staggering 150% increase.
In traditional hubs like Dublin, Frankfurt, London, and Amsterdam, data centers now account for 30–80% of local electricity consumption. As demand grows, these city grids are reaching their limits, increasing the waiting time for grid connections by 10 to 13 years. The grid, once a passive utility, is now a central factor in economic development and strategic investment.
The Geography of Grid Readiness: Winners and Losers
A key theme in the report is geographic divergence. Countries that have foreseen and invested in scalable, flexible network infrastructure – particularly in the Nordic countries and parts of Southern Europe – emerge as attractive destinations for data center expansion. Norway, Denmark, and Sweden benefit from uncongested networks, low electricity prices, cooler climates (reducing cooling needs) and a legacy of long-term energy planning.
For instance, Norway’s transmission system operator (TSO), Statnett, plans to triple data center electricity demand by 2030, while Denmark has enjoyed a 26% annual growth in capacity for the past five years, thanks to early substation investments. Conversely, the FLAP-D markets (Frankfurt, London, Amsterdam, Paris, Dublin) are experiencing grid saturation, pushing investors to seek alternative sites. Ireland, for example, has enforced a moratorium on new data center applications in Dublin until 2028.
This shift is significant: by 2035, half of Europe’s data center capacity is expected to be outside traditional hubs. In short, grid capacity has become the new competitive advantage.
AI, Sovereignty, and Economic Opportunity
The stakes are high. AI has the potential to raize GDP growth in Europe by 0.5 percentage points annually between 2025 and 2030, according to the International Monetary Fund. Governments across the continent are responding with ambitious national strategies. The EU’s InvestAI initiative seeks to mobilize €200 billion for AI, while France has committed €109 billion, and the UK is crafting a 10-year investment plan.
But these initiatives hinge on one critical factor: grid readiness. Without the ability to quickly connect new data centers, these massive investments risk being underutilized. Moreover, with AI models increasingly requiring secure and sovereign data handling, Europe’s ambition to assert digital sovereignty depends on having domestic infrastructure ready to process and store sensitive data.
Smarter Grid Solutions: A Toolkit for the Future
The report doesn’t just identify problems – it offers concrete solutions. Ember outlines a series of measures that can drastically reduce the time and cost of connecting data centers to the grid, which include:
1. Smarter Connection Agreements
Instead of waiting years for full-scale connections, phased or “non-firm” agreements could allow data centers to connect to partial capacity in the short term. This strategy, widely used in the U.S., can cut queue times by up to 80%. Italy is a pioneer in this approach in Europe: its TSO, Terna, received 30 GW of data center connection requests by the end of 2024, with 80% within 12 months. That’s equivalent to nearly 40% of Italy’s peak electricity demand.
2. Flexible Consumption Models
Contrary to popular belief, data centers can be flexible energy consumers. Electricity usage varies depending on workload, time of day, and season. AI workloads in particular can be batched and scheduled to coincide with lower grid stress. The IEA estimates that even modest flexibility – 30 hours annually – could double grid capacity availability for data centers. Pilot projects like DCFlex, launched in 2024, aim to formalize and scale this approach across the continent.
3. Strategic Siting and Co-location
Rather than retrofitting congested grids, countries can steer new developments toward underutilized or post-industrial zones. France’s EDF has designated ready-to-use industrial sites with 2 GW of available capacity, while the UK is launching AI Growth Zones to attract clustered investments. Co-location of data centers near renewable energy sources can also reduce transmission needs and stabilize electricity costs.
4. Spatial Planning and Grid Transparency
To coordinate growth efficiently, long-term spatial planning is essential. The UK’s Strategic Spatial Energy Planning process exemplifies a collaborative model where TSOs, clean energy developers, and data center investors align infrastructure investment cycles. Transparency also matters – grid capacity maps and connection queues should be publicly available to facilitate informed site selection.
Economic Impact: More Than Just Servers
Beyond electricity and AI, data centers generate tangible economic benefits. The Netherlands attributes 20% of its foreign direct investment to the data center and cloud industry. In Germany, data centers added €10.4 billion to GDP in 2024 – a figure expected to more than double by 2029. Jobs, too, are a major consideration: in the Netherlands, 11,000 direct jobs in data centers support over 2.1 million positions in the wider digital economy.
Furthermore, the sector strengthens Europe’s competitiveness in industrial automation, an area where European firms already lead globally. Since late 2022, the surge in AI demand has boosted the market capitalization of key players like Siemens by over 60%, showing that digital infrastructure investments ripple across sectors.
Grid Congestion as Strategic Risk
Despite these benefits, the report makes it clear that current grid conditions could derail Europe’s ambitions. If the continent fails to keep pace with AI infrastructure requirements, it risks losing ground to more agile competitors in North America or Asia. Grid congestion is not just a technical or regulatory issue – it’s a geopolitical and economic vulnerability.
Investors won’t wait for governments to catch up. As shown in Belgium, where operators are now scrambling to manage a flood of new applications redirected from the oversaturated Dutch and German markets, developers follow readiness, not promises. Ireland’s grid operator, EirGrid, has even warned of a potential “mass exodus” of data center investments unless connection issues are resolved.
Policy Recommendations: A Six-Point Plan
To stay competitive, Ember recommends the following actions:
1. Governments and Regulators Must Recognize Grids as Strategic Economic Infrastructure. Grid planning should no longer be reactive but anticipatory, aligning with fast-moving industries like AI.
What it means:
Electricity grids are no longer just a technical asset for managing energy flow – they are strategic enablers of national economic competitiveness. The rapid growth of digital infrastructure, especially data centers tied to AI, requires grid systems that can handle high and flexible demand quickly and reliably.
Key actions:
• Governments should integrate AI and digital infrastructure planning into national energy strategies.
• Anticipatory investments should be made – building grid capacity in areas projected to host new data centers, even before demand is fully realized.
• National energy regulators should evolve from cost-focused oversight bodies into economic development partners, ensuring grid planning aligns with innovation and industrial strategies.
Why it matters:
Slow, reactive grid investment is now a bottleneck for multi-billion-euro investments. By rethinking grid planning as a growth lever, countries can attract more digital, AI, and clean tech investments — creating jobs and GDP growth.
2. Establish AI Priority Zones to Tackle Grid Congestion. Directing investments into areas with available capacity can alleviate pressure on saturated hubs.
What it means:
Governments and grid operators can direct AI-related infrastructure (especially data centers) toward areas where electricity grid capacity is underutilized or easier to expand.
Key actions:
• Designate “AI Growth Zones” or similar economic clusters outside congested metro areas.
• Provide fast-track grid connections, permitting, and incentives in these zones.
• Encourage clustering of data centers and related digital infrastructure to maximize shared utility use (e.g., substation access, cooling infrastructure).
Examples in action:
• France is offering ready-to-develop industrial sites with pre-allocated grid capacity.
• The UK’s AI Growth Zones (AIGZ) initiative is seeking to concentrate large-scale infrastructure (e.g., 500 MW clusters) in grid-prepared areas.
Why it matters:
This approach reduces grid stress in traditional hubs like Dublin or Amsterdam while stimulating regional economic growth elsewhere.
3. Use Strategic Spatial Planning to Align Grids and Growth. Co-locating data centers with renewables and storage can reduce grid costs and network tariffs.
What it means:
Data centers should not be developed in isolation from energy infrastructure. Instead, countries should promote long-term, spatially coordinated planning that co-locates data centers, renewable energy sources, and storage facilities.
Key actions:
• TSOs (transmission system operators), clean energy developers, and data center investors must coordinate their planning cycles, even if they traditionally operate on different timelines.
• Governments should enable spatial energy planning — identifying optimal zones for energy-demanding industries based on grid and renewable generation availability.
• Encourage co-location of data centers near renewable generation (wind, solar, hydro), thereby:
o Reducing transmission losses.
o Cutting network investment needs.
o Lowering carbon intensity of digital infrastructure.
Why it matters:
Joint planning lowers infrastructure costs and accelerates permitting, making it easier and faster to deploy AI and cloud infrastructure at scale. It also supports green digitalisation goals.
4. Implement Smarter Grid Connection Deals to Speed Up Deployment. Phased or non-firm models can cut connection delays and make use of underutilized capacity.
What it means:
Standard grid connection processes are too slow. New data centers should be allowed to connect using innovative grid contracts that provide partial or flexible access earlier.
Key options:
• Phased connections: Data centers get partial access initially (e.g., 50% of planned capacity), with full access ramping up over time.
• Non-firm (interruptible) connections: Facilities agree to reduce or pause electricity use during periods of grid stress, in exchange for faster connections and/or lower network fees.
Results:
• These contracts could reduce wait times from 7–10 years to 1–3 years in congested areas.
• Italy is already seeing this in action — with 30 GW of grid connection applications for data centers, driven by shorter wait times.
Why it matters:
Time-to-market is crucial for tech companies. Smarter grid deals offer speed without requiring full-scale infrastructure buildout, unlocking rapid economic gains.
5. Explore and Scale Data Center Flexibility. Pilot schemes and regulatory frameworks are needed to harness this untapped resource.
What it means:
Traditionally, data centers are treated as constant, “firm” electricity loads — but in reality, their consumption is more flexible than assumed. Harnessing this load flexibility can ease grid pressure.
Key strategies:
• Encourage AI workload scheduling (e.g., training large models during off-peak hours).
• Support load shaping through price signals or demand-side programs.
• Use on-site battery storage and backup generators to manage peaks and interruptions.
• Launch pilot projects (e.g., DCFlex) to test and prove flexible operations across Europe.
The potential:
• The IEA estimates that just 30 hours of flexibility annually from data centers could double the grid capacity available to them.
• Belgium is already including flexibility levels of up to 75% in some of its long-term grid planning scenarios.
Why it matters:
Unlocking flexibility reduces the need for costly grid upgrades, shortens wait times, and makes more efficient use of existing infrastructure.
6. Improve Data Availability and Transparency. Grid operators should publish capacity maps and queue data to support smarter site selection and planning.
What it means:
A major barrier to smart planning is lack of data — on grid conditions, connection queues, data center demand patterns, and siting plans. Governments and grid operators need to improve transparency.
What’s needed:
• Grid capacity maps: Publicly share where infrastructure can accommodate new demand.
• Connection queue data: Show where bottlenecks exist and allow developers to plan smarter.
• Standardized demand profiles: Improve forecasting by building more accurate models of real-world data center behaviour (e.g., seasonal variation, flexibility).
• Open collaboration platforms: Enable data sharing between governments, regulators, TSOs, and private investors.
Why it matters:
With better data, planning becomes less speculative and more strategic. It allows governments to target incentives, businesses to make informed siting decisions, and TSOs to prioritize investment more effectively.
Conclusion: A Make-or-Break Moment
The AI revolution won’t wait. As Europe races to define its digital future, electricity grids have become the linchpin in the battle for technological and economic leadership. Countries that move quickly to modernize their grids – through smarter policies, collaborative planning, and technical innovation – stand to reap the rewards of a booming AI economy.
Those that lag risk not only missing the train but becoming dependent on foreign infrastructure and technology, undermining their sovereignty, competitiveness, and resilience. Grid capacity is no longer a background issue – it’s front and center in Europe’s future.
In this context, companies like Neterra – already equipped with international network infrastructure and highly reliable data centers – hold a strategic position in the new digital era. With both national and international connectivity, guaranteed power supply, and resilient architecture, Neterra provides the foundation for the growth of the next generation of AI services, without relying on overloaded or insecure energy and communication resources. This makes it a preferred partner for businesses seeking a stable and sustainable digital environment outside traditional hubs.