The consumption of resources and energy required to run artificial intelligence (AI) systems is an increasingly high-stake issue. It is the subject of major controversy, as there is a lack of precise data to enable a proper forward-looking assessment. Operators do not communicate transparently about the energy and resource consumption of the AI systems they design and operate. Nevertheless, some studies and indirect data allow us to establish orders of magnitude.
In 2023, according to the International Energy Agency (IEA), data centre consumption accounted for 2% of global electricity demand, 80% of which was linked to computing operations and infrastructure cooling requirements. This figure could double by 2026. Water withdrawals from Meta, Google and Microsoft data centres amounted to 2.2 billion cubic metres in 2022, double the annual withdrawals of a country like Denmark. Computers heat up and need to be cooled down to protect electronic components, which means that cold water circuits are still needed in most cases. Due to the dominance of GAFAM (Google, Apple, Facebook, Amazon), most of this resource consumption takes place in the United States (40% for electricity), although the geographical reach of these players is expanding.
For the past five years or so, AI has been the main driver of growth in data centre resource requirements, alongside cryptocurrencies. This is because AI models have become more complex
