Research · Paper

The Energy and Water Footprint of Generative AI: A Vanguard Leadership Perspective

Published
1 June 2025
Authors
Tali Režun, Dražen Kapusta
Topics
Sustainability

Examines generative AI's energy and water demand, efficiency differences between LLMs (Mixtral 8x22B at ~0.15 Wh per query versus Claude 3.5 at ~0.4 Wh), and regional implications in Europe, the US and Asia. Contrasts AI's footprint with Bitcoin mining (130 TWh for Bitcoin versus 7.3 TWh for AI in 2023, but AI scales with use). Proposes mitigation strategies, and argues leaders must harness AI as a force multiplier within a three-year competitive window tied to Industry 5.0.

Cite this work

Režun, T., & Kapusta, D. (2025). The Energy and Water Footprint of Generative AI: A Vanguard Leadership Perspective. talirezun.com. https://talirezun.com/library/energy-water-footprint-generative-ai

@misc{energy-water-footprint-generative-ai,
  author = {Tali Režun and Dražen Kapusta},
  title = {The Energy and Water Footprint of Generative AI: A Vanguard Leadership Perspective},
  year = {2025},
  url = {https://talirezun.com/library/energy-water-footprint-generative-ai},
  note = {talirezun.com}
}
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