AI & Environment Resource HubWorld Business Council for Sustainable Development (WBCSD) · 2025-09-19
Physical risks related to rising temperatures are already impacting business. The next five years are critical for accelerating greenhouse gas emissions reduction if we are to avoid the most catastrophic impacts of climate change. Yet the window for decisive action is closing quickly. Although ambitions have been high amongst corporate leaders, other pressures on business
World Business Council for Sustainable Development (WBCSD). 2025-09-19. Accelerating Emissions Reductions and Strengthening Business Performance. https://www.wbcsd.org/resources/accelerating-emissions-reductions-and-strengthening-business-performance/ (AI & Environment Resource Hub; record report-237; collection snapshot 2026-09-15).
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Source sheet: Policy Document · Row 241 · Original ID: report-237.
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Shared topics: Governance and society; Energy and electricity; Climate and greenhouse gases
This study presents a behavior-driven decision framework that helps AI developers choose models balancing accuracy and environmental sustainability by quantifying energy use and emissions during fine-tuning and applying behavioral decision theories.
Shared topics: Governance and society; Energy and electricity; Climate and greenhouse gases
Generative AI tools, such as DALL-E and DreamStudio, show potential in improving public engagement and energy literacy about low-carbon sources like nuclear energy, though they fall short in representing technical details, addressing biases, and accurately depicting indigenous landscapes.
Shared topics: Governance and society; Energy and electricity; Climate and greenhouse gases
This paper explores green AI as a path to environmental sustainability by promoting energy-efficient models, democratized access, eco-friendly AI applications, and regulatory frameworks to align machine learning practices with global climate goals.
Shared topics: Governance and society; Energy and electricity; Climate and greenhouse gases
Maggie Welsh and Michael Silliman discuss the synergistic relationship between AI and clean tech. Michael covers how AI drives both energy demand and solutions for climate change, and why AI innovation is slower in clean tech compared to other sectors. They also delve into challenges such as data interoperability, regulatory complexity, and venture funding.