3. Challenges for the EU AI Cloud The development of the alternative AI cloud ecosystem faces structural challenges that may subvert the intent of the EU´s policy towards more technological sovereignty. 3.1 Physical constraints and bottlenecks Physical constraints regarding land use, power gener ­ation and grid transmission are out of sync with the aspirations of data centre growth. The EU’s objective of‘tripling data centre capacity’ is primarily limited by these infrastructural material realities rather than just directly AI-related capital or hardware availability. AI computing requires vastly more power than previous cloud technologies, creating major challenges for elec­tricity grids and transmission infrastructure. Building energy infrastructure is typically a long-term process, with delays in obtaining permits and procuring the nec­essary energy components, which are currently highly sought after. Beyond environmental questions and the capital expens­es required, there are distributional implications(Leppert 2025). For example, largely as a result of data centre-driv ­en buildout in Ireland, the Commission for Regulation of Utilities(CRU) projects an 8 to 21 % increase in energy prices for households over the next five years, while the data centres and other large energy users will see a 14 % decline(Smyth 2025). While some European companies are positioning themselves to capture markets in the cool­ing and heat re-use solutions, data centre buildouts of the scale proposed is likely to lead to challenging political trade-offs and tensions between other policy objectives, such as energy security and the climate transition. European data centre supply projections 1,200 Figure 8 Forecast MW 1,000 800 600 400 200 0 2017 Source: CBRE 2025d. 2018 2019 2020 2021 2022 2023 2024 2025 Challenges for the EU AI Cloud 19