Faced with the rise in electricity consumption linked to AI, researchers and industry are turning to AI-optimised carbon capture materials, but real-world demonstrations are still limited to small-scale trials.
As the growth of AI data centres increases electricity consumption and associated emissions, carbon capture and storage (CCS) is increasingly being presented as a response element. AI, including machine learning, is mobilized to accelerate the discovery of new capture materials, such as metal-organic structures (MOF), and to optimize the operation of capture facilities in real time.
Demonstrations of direct capture in air (DAC) remain modest, however, from a few hundred to a few thousand tonnes of CO2 captured per year and per site, with typical carbon efficiency of 56 to 64% depending on operating conditions. Some critics believe that this bet on carbon capture risks delaying more structural changes in how digital infrastructure is built and powered.
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