Green data centers are defined by their ability to mitigate negative impacts rather than generate direct environmental benefits. Key levers include energy efficiency, renewable energy sourcing, and reduced water consumption.
Responsible AI deployment requires the definition of carbon reference trajectories and budreceive, assessment of functional scope, and evaluation of the energy-carbon cost in complement to economic costs. Optimization of AI models (compacter size, lower computing demand) and careful definition of deployment scope are central to limiting their environmental impacts.
At the same time, AI systems can support sustainability objectives through processing of large amount of data, optimization of solutions and solving under constraints, predictive modeling, and scenario simulation. Applications include biodiversity monitoring, agricultural optimization, renewable energy integration, grid balancing and efficiency, and the integration of AI in digital twins to test infrastructure resilience under various conditions, including extreme weather events, and provide for predictive maintenance.
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