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Energy demand and cost development of AI data centers in the USA and Europe

What changes are occurring in the electricity consumption of data centers under the influence of artificial intelligence in the US and Europe? How do these new loads affect power grids, prices, and infrastructure, and who ultimately bears the costs? What are the parallels and differences between the two markets, particularly with regard to subsidies and the future burden on businesses and citizens?

Current electricity demand of data centers in the USA

What is the current share of electricity consumption in the USA attributable to data centers, and how is this share developing?

In 2023, according to a report by the New York Times and other surveys, data centers accounted for approximately 4 percent of total US electricity consumption. This figure is expected to rise to 12 percent by 2028 at the latest, driven primarily by the increased use of AI applications and the associated installation of high-performance servers and specialized AI accelerators. According to forecasts from the US Department of Energy (DOE) and the Lawrence Berkeley National Laboratory, the electricity demand of US data centers increased from 76 TWh in 2018 to 176 TWh in 2023. For 2028, figures between 325 and 580 TWh are projected, depending on the pace of AI adoption and efficiency gains from new technologies. The average growth rate is therefore between 13 and 27 percent per year.

Development of energy consumption and its impact on the electricity grid

What does the rapid increase in energy consumption by AI data centers mean for US power grids and prices?

This development is placing a massive strain on existing power grids, which were primarily designed for moderate demand. Data centers require constant, high amounts of electricity, with the consumption of a single large AI data center already comparable to that of hundreds of thousands of households. In Virginia, a hub of the US data industry, data centers account for up to 25 percent of local electricity consumption.

Since 2020, electricity prices in the US have risen by around 30 percent, driven by grid infrastructure repairs, modernization projects, and measures to protect against extreme weather. The expenses incurred by tech companies for their own power plants and the necessary expansion of the electricity infrastructure to meet the demands of the AI ​​boom are expected to be partially passed on to small businesses and consumers. If the US government does not require tech providers to bear these costs themselves, further price increases of up to 25 percent are anticipated in particularly affected regions such as Virginia.

Investments in infrastructure and power plants

How are tech companies reacting to rising electricity demand, and what role do their own power plants play?

Companies like Microsoft, Google, Amazon, and others are increasingly investing in their own conventional and renewable power plants to meet their energy needs independently of the public grid. These investments are also a response to the high utilization and potential bottlenecks of the electricity grid. The trend is toward nuclear power plants and small modular reactors, as well as new gas-fired power plants, to ensure supply and reduce the carbon footprint. Nevertheless, the challenge remains that the expansion and modernization times of the grid infrastructure are often longer than the short construction times of the new data centers.

Price increases and cost passing on to consumers

How are the costs for grid expansion and electricity price increases distributed in the USA, and what political solutions exist?

US utility companies tend to pass on the costs of grid expansion over decades through price increases for all connected customers. Currently, there is discussion about the extent to which large tech companies should contribute to financing the infrastructure, for example, through special tariffs or surcharges for bulk consumers. In states like Virginia, energy prices could rise by up to 75 percent if additional investments are necessary and the costs are distributed among all electricity customers.

At the same time, new regulatory approaches are emerging, such as the targeted charging of tech companies for their own contributions to the resulting network expansion, or the introduction of demand response programs in which data centers reduce their own electricity demand in emergencies.

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Parallel situations and trends in Europe

Can similar developments be observed in Europe?

A similar trend is emerging in Europe. The European Commission has announced a €20 billion funding package for the construction of four to five AI gigafactories, with up to 35 percent of the costs covered by public funds. By the end of June 2025, a total of 76 expressions of interest had been received for gigafactory locations in 16 member states. The planned data centers are equipped with at least 100,000 high-performance GPUs.

According to industry experts and studies, the electricity demand of AI data centers in Europe could increase by a third by 2030, particularly due to the consolidation of data processing and the training of large AI models. Networks in hotspots like Frankfurt and Berlin are already operating at their capacity limits.

Network expansion and cost sharing in Europe

How are network expansion costs and subsidies financed in Europe?

Network expansion in Europe is essential to meet the increasing energy demands of new data centers. The costs of this expansion are primarily covered by tax revenue and EU subsidies, but there is a risk that some of the subsidies and additional costs will be passed on to the general public, i.e., taxpayers, unless private operators are more actively involved in the financing.

At the same time, Europe is competing with the US and China, where electricity costs for data centers are often significantly lower. Average industrial electricity prices in Germany are roughly twice as high as in the US. To ensure competitive prices, initial proposals are being made, for example by Bavaria's Digital Minister, to introduce a European "AI electricity price" or special tariffs for sustainable AI data centers.

Challenges of network infrastructure and energy mix

What problems arise during infrastructure expansion and how does the energy mix change?

In Germany, many regions – including Frankfurt and Berlin – suffer from grid congestion and long waiting times for network connections. Doubling or even tripling the Europe-wide capacity for AI data centers by 2030 therefore seems ambitious; in fact, a doubling is considered more likely. Grid expansion is being supported by substantial investments in renewable energies, but fossil fuels and gas-fired power plants will still be needed for baseload power. Europe is also examining the integration of modular nuclear reactors (SMRs) and battery solutions to supply energy-intensive AI centers.

Energy efficiency and sustainability are part of the political agenda

What political and technical measures exist to limit the environmental and price consequences?

Innovations in energy efficiency – such as more efficient cooling technologies, energy-conscious hardware and software, and the integration of waste heat recovery – can help reduce environmental impacts and stabilize operating costs. The promotion of sustainable data centers through special tariffs, tax breaks, and research programs is being discussed in several countries.

In addition, new regulatory requirements play a role, such as the German Energy Efficiency Act, which imposes higher efficiency requirements on operators and promotes the shift to edge computing. In political discourse, there is an increasing call for a more sustainable and holistic approach that considers the CO₂ footprint, resource consumption, and the entire life cycle of the infrastructure.

AI vs. Energy Supply: The Race Against Rising Costs and Complexity

What can be expected in the medium term regarding electricity prices, the grid, and political control?

The growing energy demand from AI data centers will significantly impact grid infrastructure and energy prices in both the US and Europe in the coming years. If policymakers fail to hold large tech companies more accountable for financing these investments, small businesses and private consumers face a substantial burden in the form of rising electricity prices and taxes. Simultaneously, power grids must be massively expanded, modernized, and made more resilient and flexible in the face of extreme weather and peak loads.

In the long term, only a balanced mix of political steering, innovative cost models, regulatory requirements and technological innovation can secure competitiveness and ensure a fair distribution of burdens according to the polluter pays principle.

The relocation of large parts of the digital infrastructure to energy-intensive AI data centers poses significant challenges to electricity grids and pricing structures in the US and Europe. Current financing practices increasingly shift costs to small businesses and households unless policy countermeasures are implemented. Europe also faces the challenge of protecting the security of supply and the competitiveness of its industries against high energy prices and lengthy grid expansion projects. Sustainable and efficient solutions are needed to prevent a collapse of the grid infrastructure and a loss of competitiveness. The coming years will show whether and how national and European policies can adapt to this new reality.

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