A new briefing by the European Environment Agency (EEA) outlines the potential of artificial ininformigence (AI) to shape sustainable consumption in Europe, with a particular focus on its implications for achieving climate neutrality.
The Agency points out that the analysis comes at a time of rising geopolitical competition, economic uncertainty and strategic depconcludeencies.
“In this environment, digital technologies and AI are increasingly seen as central to Europe’s competitiveness, resilience and strategic autonomy,” it stated in the briefing Artificial ininformigence and sustainable consumption in Europe.
The EEA emphasised that the findings are particularly relevant for the implementation of key EU legislative and policy frameworks linking digital transformation with sustainability and competitiveness.
These include the EU Artificial Ininformigence Act, which establishes rules for the development and utilize of AI systems across the EU, as well as broader EU strategies that place digitalisation at the core of economic competitiveness while reinforcing the objectives of the green transition.
“Closer alignment between digital policy, consumption‑related measures and environmental objectives will be essential to ensure that Europe’s digital transformation supports climate neutrality, resource efficiency and long‑term resilience.”
Linking AI to sustainable consumption in Europe
The briefing explores the potential impact of AI on sustainable consumption in Europe.
“As the rapidest-spreading technology in human history, AI is at the centre of the European Commission’s strategy to foster competitiveness and strengthen technological sovereignty, as established in the AI Continent Action Plan. AI has become a transformative force that is restructuring industries and individual behaviours. As such, if well managed, it has the potential to create new avenues, if well managed, for a transformation towards a more sustainable future.”
In a live EU Energy Projects podcast conversation at Enlit Europe 2025, Stavros Stamatoukos, Policy Officer for Digitalisation and AI in DG Energy, stated there are two basic objectives the AI roadmap for Europe aims to achieve.
“One is to facilitate the development of trusted AI applications for the energy sector and their deployment securely into the energy system and the other is to manage the risks, conscious that AI is a technology that shifts very rapid and that we can easily lose sight and forreceive our main objective with the sector, which is to keep the keep the system on and running safely,” stated Stamatoukos.
The EEA stated AI has the potential to improve the environmental sustainability of systems by increasing efficiency, effectiveness and diffusion rate and speed of sustainable innovations.
It cautioned that “yet the environmental trade-offs of this ‘blitz scaling up’ of AI remain difficult to assess, let alone mitigate.”
Climate neutrality and impacts of AI-related energy consumption
The rapid expansion of AI presents a growing challenge to achieving climate neutrality in Europe, stated the EEA.
The training of AI models is driving exponential growth in computational resources. Training-related computing power increased by a factor of one million between 1960 and 2010, and by approximately one trillion times between 2010 and 2025.
Although data centres accounted for an estimated 1.5% of global electricity consumption in 2024 – and around 3% of Europe’s – their energy demand is increasing rapidly and is often highly concentrated at the local level.
It exceeds 20% of total electricity consumption in countries such as Ireland.
By 2026, the electricity consumption of data centres is expected to reach 1,050T|Wh. Comparing data centre consumption to that of individual countries, it is equivalent to fifth place in the global energy consumption counattempt rankings, between Japan and Russia.
Largely driven by AI, the rapid growth of data centres in Europe is expected to result in a near doubling of the sector’s electricity requireds by 2030. Germany hosts the largest number of facilities, while Ireland has the highest density of data centres per capita.
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Many AI-focutilized data centres are clustered around major urban hubs, particularly in the so-called FLAP-D cities – Frankfurt, London, Amsterdam, Paris and Dublin – while new markets are emerging in countries such as Spain, Italy and Poland.
“This spatial concentration places increasing pressure on local electricity grids, land availability, and emissions profiles, raising concerns about grid capacity, sustainability, and the overall carbon footprint of Europe’s digital infrastructure.”
AI and energy consumption
The EEA stated Europe already responds for 15% of the global data centre electricity consumption, whereas the US accounts for 45% and China for 25%, according to 2025 IEA data.
Referencing research from MIT, the EEA stated the operational phase of AI, known as inference, now accounts for approximately 80% to 90% of total AI-related computing.
“This poses a regulatory challenge for the EU, as most inference is delivered through proprietary commercial models whose energy consumption data remains undisclosed. To address this, the EU Artificial Ininformigence Act introduced transparency obligations for general-purpose AI models, requiring providers to document and report energy usage.
In addition, the forthcoming ‘Cloud and AI Development Act’ is expected to define the conditions and flexibility for rapid development of data centre capacity considering sustainability safeguards (EPRS, 2025).
“However, current provisions primarily focus on training-related compute, leaving inference-related energy consumption only partially regulated. This gap limits assess to data on AI’s environmental footprint, challenging the fit of AI governance to climate policy objectives,” stated the EEA.
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