AI & Environment Resource HubAuthor or publisher unknown · 2026-05-20
Susanna Kass, operating partner at Digital Gravity Infrastructure Partners and senior data center advisor to the UN SDGs, shares how absolute-zero data center design, grid collaboration and circular economy thinking can enable sustainable, resilient and capital-efficient data centers as AI demand accelerates.
Author unknown. 2026-05-20. Sustainable AI Data Centers for a Carbon-Free Future. https://www.projectfinance.law/uptime-now/ep9-sustainable-ai-data-centers-for-a-carbon-free-future (AI & Environment Resource Hub; record pod-0204; collection snapshot 2026-09-15).
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Shared topics: Cross-cutting sustainability; Energy and electricity; Climate and greenhouse gases; Weather, hazards, and adaptation; Built environment and infrastructure
AI is being deployed across both generative and predictive applications, but while generative AI demands enormous energy and data center infrastructure, predictive AI offers more efficient, targeted tools for climate solutions, such as emissions tracking, renewable grid forecasting, and extreme weather nowcasting, highlighting a crucial trade-off between innovation and sustainability.
Shared topics: Cross-cutting sustainability; Energy and electricity; Climate and greenhouse gases; E-waste and circularity; Built environment and infrastructure
In the Environmental Impacts of Data Centers 101 course, you will learn to analyze the environmental impacts of data centers using a life cycle assessment (LCA) perspective that goes beyond what you see in the news. This will include energy, water, land use, carbon emissions, global supply chains, e-waste concerns, ecological impacts, and environmental justice case studies. Whether you work in tech, sustainability, policy, or are just curious about how AI systems operate behind the scenes, this course gives you the clarity and frameworks to understand these impacts from end-to-end.
Shared topics: Cross-cutting sustainability; Energy and electricity; Climate and greenhouse gases; Weather, hazards, and adaptation; Built environment and infrastructure
This panel will detail how AI is emerging as a powerful ally in supporting disaster preparedness and building resilience across interconnected systems.
Shared topics: Cross-cutting sustainability; Energy and electricity; Climate and greenhouse gases; Weather, hazards, and adaptation; Built environment and infrastructure
This course will help you understand AI's climate implications and identify practical next steps within your organization. The course begins with demystifying the connection between AI, Large Language Models (LLMs), data centers, and energy and water demand. Then you will learn about AI's environmental footprint, the related environmental and community impacts, you will evaluate real-world applications of AI across climate adaptation, energy transition, and nature conservation, and understand the business and policy landscape shaping corporate decisions.