---
title: "The Energy and Water Footprint of Generative AI: A Vanguard Leadership Perspective"
url: "https://talirezun.com/library/energy-water-footprint-generative-ai"
markdown: "https://talirezun.com/library/energy-water-footprint-generative-ai.md"
type: "Paper"
brand: "Research"
published: "2025-06-01"
updated: "2026-10-19T09:31:17.178Z"
authors: ["Tali Režun","Dražen Kapusta"]
topics: ["Sustainability"]
---

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

- URL: https://talirezun.com/library/energy-water-footprint-generative-ai
- Type: Paper
- Brand: Research
- Published: 2025-06-01
- Updated: 2026-10-19
- Authors: Tali Režun, Dražen Kapusta
- Topics: Sustainability

## Summary

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.

## Overview

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.

## Editions

Where to read the full work (the canonical edition first):

- [International Leadership Journal (full issue, PDF)](https://internationalleadershipjournal.com/wp-content/uploads/2026/03/ILJ_Summer2025_Full_Issue.pdf) (canonical)
- [International Leadership Journal (issue page)](https://internationalleadershipjournal.com/ilj_summer2025_full_issue/)
- [PDF](https://talirezun.com/library/energy-water-footprint-generative-ai/pdf)
- [ResearchGate](https://www.researchgate.net/publication/394255359_The_Energy_and_Water_Footprint_of_Generative_AI_A_Vanguard_Leadership_Perspective)

## 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

## Related

- [The Hidden Cost of AI: What Every Leader Needs to Know About Energy and Water](https://talirezun.com/library/hidden-cost-of-ai-energy-water.md)
- [AI as a Force Multiplier: Leaders for Industry 5.0](https://talirezun.com/library/ai-force-multiplier-industry-5.md)
- [Chasing Jarvis: Can Technically Sophisticated Non-Programmers Deploy SaaS Applications Using AI Coding Agents? An Empirical Investigation Through Context Engineering and the Lumina AI Case Study](https://talirezun.com/library/chasing-jarvis-non-programmers-saas.md)

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