The Arm Global AI Readiness Report highlights AI’s paradox: while it poses environmental risks, it also offers powerful tools to advance sustainability.
At the heart of AI's environmental impact is its immense energy consumption. Data centers worldwide now consume approximately 460 terawatt-hours (TWh) annually—equivalent to the entire electricity use of Germany. In the U.S., data centers accounted for 2.5% of electricity use in 2022, with projections suggesting a rise to 7.5% (390 TWh) by 2030, roughly the consumption of 40 million households.
This rapid rise presents a challenge for already strained electrical grids, particularly as nations transition toward intermittent renewable energy. Some regions have enacted moratoriums on new data center projects due to transmission congestion. Without coordinated investment in grid infrastructure and energy efficiency, AI’s unchecked growth could undercut global emissions targets.
AI’s energy footprint is not confined to massive data centers. The proliferation of edge computing and IoT devices is spreading energy demands to homes, vehicles, and factories. As more devices process AI locally—reducing reliance on cloud infrastructure—the cumulative energy use grows. However, targeted solutions can mitigate this impact.
Strategies include:
Despite its energy demands, AI can be a formidable force in advancing climate resilience. Machine learning algorithms enhance wind and solar forecasting, optimize grid operations, and improve energy storage management—directly supporting the clean energy transition. In climate modeling, AI enables more accurate simulations of extreme weather, aiding disaster preparedness and mitigation.
AI is also transforming supply chains, transportation systems, and environmental monitoring. From satellite-based detection of illegal deforestation to predictive models in urban transit, AI applications are helping reduce emissions and improve efficiency across sectors.
Achieving sustainable AI requires global, cross-sector collaboration. Initiatives like the Coalition for Sustainable AI—launched in partnership with France, UNEP, and the ITU—aim to align technological advancement with climate goals. Regulatory frameworks, such as the EU AI Act, are already setting standards for transparency, ethics, and environmental responsibility.
Additionally, industry players are advocating for Environmental Product Declarations to measure and reduce the embodied emissions of datacenter infrastructure. With investments like the $100 million U.S. NIST initiative to develop sustainable semiconductor materials using AI, the momentum is shifting toward climate-aligned innovation.
AI’s environmental trajectory is not yet set. The industry stands at a crossroads: it can either accelerate climate challenges or emerge as a cornerstone of the solution. By embedding sustainability into AI design—from chip architecture to software code—and fostering international cooperation, AI can live up to its potential as a transformative tool for climate action.
As contributing authors Dr. Just and Dr. Höher assert,
“It is no longer a question of whether AI can be sustainable, but whether we will take the necessary steps to make it so.”
