Session Description
The rapid expansion of artificial intelligence is driving unprecedented growth in data centre infrastructure worldwide. By 2030, global data centres are projected to consume 945 terawatt-hours of electricity annually. Water consumption associated with AI could equal the basic annual domestic needs of 1.3 billion people, while the land footprint may exceed 14,500 square kilometres.
Beyond the operational phase—where cooling systems consume vast quantities of water and energy—data centres carry significant “out of sight” impacts. The electricity they consume carries embedded water and land footprints from power generation. Moreover, AI hardware depends on a global supply chain of critical minerals—lithium, cobalt, rare earth elements—whose extraction generates severe environmental degradation, contaminates water supplies, and displaces communities.
Current environmental impact assessment practice need to be tailored and practitioners upskilled to address this challenge. Comprehensive life cycle assessment (LCA) is essential, extending from mineral extraction through manufacturing, operation, and end-of-life disposal.
This panel, convened jointly with UN agencies, industry leaders, and the EIA profession, will examine the full environmental footprint of AI infrastructure and identify pathways to strengthen practitioner capacity.
Session Summary
AI-driven data centres are consuming vast quantities of electricity, water and land, with hidden impacts across critical mineral supply chains and energy generation. This panel—jointly convened with UN, industry and EIA sectors—will explore how to update EIA practices and upskill practitioners.
Session Chair
Dr Muralee Thummarukudy
United Nations Convention to Combat Desertification
Germany