T_HQ
Summary
A new whitepaper from climate finance company Opna calls for a fundamental redesign of how artificial intelligence (AI) infrastructure is built, powered, and financed. The paper argues that the current hyperscale model—massive, resource-intensive data centres concentrated in a few regions—threatens to deepen global inequalities and strain vital resources such as water, land, and energy.
Instead, the report proposes a shift to inference-first, modular, and distributed data centres – a model that aligns AI’s physical footprint with climate resilience and community prosperity. Properly designed, these “right-sized” facilities can anchor clean energy projects, stabilise grids, reuse waste heat and water, and drive demand for low-carbon materials and carbon removal.
“Decentralised compute decentralises power,” said Shilpika Gautam, CEO and Founder of Opna. “By embracing modular, inference-first design, we can redirect the trillions flowing into AI infrastructure toward assets that strengthen both communities and the planet. AI infrastructure can and should become climate infrastructure.”
The paper outlines seven principles for achieving this transition, including anchoring clean power, embedding circularity, advancing water stewardship, using low-carbon materials, and establishing binding community benefit agreements. It also calls for rigorous transparency in energy and water data, localised siting strategies, and policy frameworks that reward integration with renewables and district energy systems.
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