Sustainable AI white paper: innovation with environmental integrity

Yet AI also brings challenges. Data centres consume up to 3% of the world’s electricity, and large-scale model training adds to carbon emissions. Without a clear focus on sustainability, AI could worsen the very problems it aims to solve. Responsible innovation must ensure that AI grows in a way that reduces, not increases, environmental impact.

How sustainable AI supports climate goals

In our new white paper, we explore the role of sustainable AI in tackling urgent environmental issues:

• Greener AI training methods: researchers are creating algorithms that need less computing power, cutting both costs and emissions.

• Sustainable data centres: liquid cooling and renewable energy reduce the footprint of facilities that power modern AI.

• AI-driven material discovery: platforms use AI to design new materials for carbon capture and clean energy production.

• Responsible waste management: startups apply green AI to identify and recycle electronic waste more effectively.

These case studies show how responsible AI can deliver measurable progress against climate change targets.