The Hidden Cost of AI: Energy, Nature and Infrastructure
The race to build artificial intelligence is often discussed in terms of innovation, productivity, and economic growth. Less attention is paid to the physical systems that make AI possible: the power grids, water resources, land use, and natural ecosystems that support an expanding network of data centres and digital infrastructure.
This discussion will examine the growing environmental footprint of AI and the practical challenges it presents for the climate transition. As demand for computing power accelerates, so too does demand for electricity, raising important questions about grid capacity, energy planning, and competition for clean power. At the same time, the rapid expansion of data centres is creating new pressures on water resources, land, and local ecosystems, bringing nature-related risks and dependencies into sharper focus.
Participants will explore whether existing governance and disclosure frameworks are equipped to assess these impacts, and what greater transparency could mean for investors, policymakers, technology companies, and communities. The conversation will also consider how decisions made today about digital infrastructure could shape future energy systems and environmental outcomes.
As AI moves from a niche technology to critical infrastructure, understanding its resource requirements is becoming increasingly important. This conversation asks how society can support technological innovation while ensuring that the energy, nature, and infrastructure systems underpinning it remain resilient, sustainable, and fit for the future.
Discussion Group Leaders
A. Toni Young is Executive Director at Community Education Group, Principle at A Global Firm, advancing equitable access to health, technology, and AI capacity-building in rural communities.
Charlotte Blommestijn is Head of Sustainability at Kaluza, advancing power system transformation, grid flexibility, and the role of AI in the energy transition.
Discussion Questions
How should governments and utilities plan for rapidly growing electricity demand from AI and data centres while maintaining progress on climate goals?
What are the most significant nature-related impacts and dependencies associated with AI infrastructure, and how should they be measured and managed?
Are current climate and nature disclosure frameworks sufficient for the technology sector, or do new approaches to transparency and accountability need to emerge?
How can the expansion of AI infrastructure be balanced with the needs of local communities, energy systems, and environmental protection?