What It Will Take to Make AI Sustainable
Nobody is talking about AI's actual carbon footprint. Here's why the emissions data we have is broken.
Why it matters
As AI infrastructure scales, transparency on environmental impact and usage patterns becomes a critical governance issue for enterprise leaders and policymakers. Better emissions data is emerging as a prerequisite for sustainable AI deployment.
The key facts
8 to knowResearcher Sasha Luccioni argues for improved emissions transparency
Current AI emissions data lacks granularity and comprehensive tracking
Usage pattern visibility is identified as foundational to sustainability strategy
Published May 2026 — sustainability governance increasingly central to AI strategy discussions
Researcher Sasha Luccioni identifies emissions data as a critical gap in AI sustainability
Current AI usage patterns poorly understood and undocumented
Sustainability of AI systems tied to both technical infrastructure and adoption measurement
Implications for regulatory compliance and corporate governance of AI projects
Go to the source
Wired AIwired.com
Publisher excerpt: Researcher Sasha Luccioni argues we need better emissions data and a better sense of how people are using AI in the first place.