By Stuart Kerr, Technology Correspondent
Published: 04 August 2025
Last Updated: 04 August 2025
Contact: liveaiwire@gmail.com | Twitter: @LiveAIWire
Author Bio: About Stuart Kerr
Artificial intelligence may be powering the next industrial revolution, but it's also supercharging our carbon emissions. According to a landmark Accenture report, AI could be responsible for an elevenfold increase in global carbon emissions by 2030 unless urgent action is taken.
This stark warning forms part of a broader study titled "Powering Sustainable AI", which outlines a potential future where the energy demand of training and running large AI models spirals beyond the current infrastructure’s limits. Accenture's projections are based on enterprise uptake, scale of deployment, and current inefficiencies in model architecture.
The Unseen Environmental Cost of AI
Much of AI's growth has taken place behind sleek interfaces and promising productivity gains. But behind the scenes, the environmental cost is becoming impossible to ignore. Training a single large model can consume more electricity than 100 U.S. homes use in a year.
As previously examined in Invisible Infrastructure, AI systems rely on vast compute clusters and cloud services that are still largely powered by non-renewable sources. Accenture warns that by 2030, AI could account for up to 20% of global electricity consumption if current trajectories hold.
Mitigation Is Possible, But Not Guaranteed
The arXiv paper "Exploring the Sustainable Scaling of AI Dilemma" echoes these concerns, predicting a 24-fold energy increase under high adoption scenarios. Researchers argue that next-generation models must prioritize energy efficiency from design to deployment.
Solutions include improved model compression, algorithmic efficiency, and hardware innovation. But adoption remains slow. Many companies, particularly startups and mid-sized firms, prioritize accuracy and speed over sustainability.
A Corporate Blind Spot?
The report also highlights a growing disconnect between net-zero commitments and AI strategy. In Algorithmic Hunger, we saw how AI was touted as a tool to solve planetary-scale problems like food scarcity. But these gains may be offset if the tools themselves contribute significantly to climate degradation.
Furthermore, Axios reveals that most corporate sustainability reports still fail to factor in AI-related emissions, making it harder for watchdogs and regulators to assess real progress.
A Ticking Clock
With AI accelerating across every industry, the emissions conversation can no longer be an afterthought. As explored in AI Fights Disinformation, trust in technology relies not only on accuracy but on ethical stewardship. Accenture urges governments and enterprises to collaborate on global sustainability standards specific to AI.
Whether AI becomes a net benefit or liability in the climate fight may depend on decisions made in the next five years. The time to act, Accenture warns, is now.
About the Author
Stuart Kerr is the Technology Correspondent for LiveAIWire. He writes about artificial intelligence, ethics, and how technology is reshaping everyday life. Read more