UN Study Highlights AI’s Escalating Environmental Footprint by 2030
Ingrid Solberg | AA
A new UN study warns artificial intelligence could consume resources on a scale rivaling major nations, with energy, water, and land impacts hitting developing regions hardest by 2030.
A new study released by the United Nations University (UNU) has issued serious warnings about artificial intelligence’s intensifying environmental footprint. Titled The Environmental Cost of Artificial Intelligence: Carbon, Water and Land Footprints, the report underscores the rapid and potentially unsustainable growth of AI-related resource consumption globally. Its findings reveal that the developing regions of Asia may face the most significant impacts, complicating already precarious situations of water scarcity and rising energy demand.
By 2030, AI-related electricity consumption is projected to reach levels requiring nearly three times the annual power used by Pakistan, Bangladesh, and Nigeria combined. These nations, collectively home to approximately 650 million people, risk seeing disproportionate burdens from AI’s expansion, UNU researchers warned. The study estimates that carbon dioxide emissions generated by AI systems alone could reach up to 400 million tons annually by the end of the decade,a figure comparable to the United Kingdom’s current emissions levels.
How much water will AI need annually by 2030?
AI infrastructure could require 9.3 trillion liters of water annually by 2030, equivalent to the domestic water needs of approximately 1.3 billion people in sub-Saharan Africa, according to a UN study.
AI-Driven Strains on Water and Land Infrastructure
The report did not stop at energy or carbon emissions; it also shed light on significant water and land resource consumption. UNU researchers estimate that AI infrastructure could require approximately 9.3 trillion liters of water annually by 2030,an amount equivalent to the domestic needs of 1.3 billion individuals across sub-Saharan Africa. This sharp increase in water usage will likely exacerbate existing challenges in water-stressed regions, particularly in parts of Asia, where scarcity already hampers socioeconomic development.
Land associated with AI-related infrastructure, such as data centers and energy installations, is expected to surpass 14,500 square kilometers by the end of this decade. Considering such developments, UNU researchers cautioned technology companies against overlooking local environmental impacts, emphasizing that the benefits of AI are concentrated among a few nations while indirect costs reverberate across vulnerable populations. They stressed the need for balanced governance to address the inequalities in how these environmental burdens are distributed.
Calls for Governance, Transparency, and Cooperation
In response to these findings, the UN study calls for immediate action to curb AI’s environmental impact while ensuring sustainable development. It advocates for heightened transparency from technology firms, improved standards in environmental governance, and stronger international collaboration. Without these measures, the unchecked growth of artificial intelligence risks challenging global sustainability goals.
Why Cities Must Lead AI Sustainability Efforts
Mayors and city governments are uniquely positioned to address the environmental challenges linked to AI. Urban centers are hubs for innovation and deployment, often hosting the data centers and energy infrastructure that power artificial intelligence systems. By adopting stringent resource-preservation policies locally, cities can play a significant role in reversing global trends of unsustainable AI-related consumption. For example, implementing ordinances regulating the environmental standards of data facilities could set benchmarks for national policies while mitigating localized impacts.
Additionally, urban planning must account for the ripple effects of AI on underserved communities, particularly in regions facing acute challenges such as water scarcity. Municipal leaders can spearhead international partnerships centered on sustainable AI development, positioning their cities as models for balancing innovation with environmental stewardship. By integrating AI into climate-action frameworks, cities can ensure the sector progresses responsibly, avoiding the pitfalls highlighted in the UN study while maximizing its transformative potential.
Questions That Matter
How much carbon will AI emit by 2030?
By 2030, AI systems could emit up to 400 million tons of carbon dioxide annually, a figure comparable to the current emissions levels of the United Kingdom.
What area will AI infrastructure cover by 2030?
AI-related infrastructure, including data centers and energy installations, is expected to cover over 14,500 square kilometers by the end of the decade.