{"id":75910,"date":"2026-06-05T18:24:26","date_gmt":"2026-06-05T12:54:26","guid":{"rendered":"https:\/\/www.nextias.com\/ca\/?p=75910"},"modified":"2026-06-05T18:28:37","modified_gmt":"2026-06-05T12:58:37","slug":"ai-power-consumption","status":"publish","type":"post","link":"https:\/\/www.nextias.com\/ca\/current-affairs\/05-06-2026\/ai-power-consumption","title":{"rendered":"AI Could use 3% of World&#8217;s Power by 2030: UN Report"},"content":{"rendered":"\n<p><strong>Syllabus: GS3\/Environment<\/strong><\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Context<\/strong><\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>United Nations report Environmental Cost of Artificial Intelligence highlights that by 2030,<strong> AI could consume 3% of world\u2019s electricity.<\/strong><\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Major Findings<\/strong><\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Water and Power Consumption: <\/strong>AI-related water consumption could equal the basic annual domestic needs of 1.3 billion people by the end of the decade.\n<ul class=\"wp-block-list\">\n<li>Data centres could consume 945 terawatt-hours of electricity annually by 2030 \u2013 nearly triple the combined annual electricity use of Pakistan, Bangladesh, and Nigeria.\u00a0<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li><strong>Water and Land Footprint:<\/strong> Every unit of electricity used by data centres also carries a \u201cwater footprint\u201d for cooling and energy production, and a \u201cland footprint\u201d associated with power generation and supply chains.<\/li>\n\n\n\n<li><strong>Electronic Waste: <\/strong>The report warns of a growing electronic waste challenge, with AI infrastructure projected to generate up to 2.5 million tonnes of e-waste annually by 2030.\n<ul class=\"wp-block-list\">\n<li>Much of this burden is likely to fall on lower-income countries with limited capacity for safe disposal.\u00a0<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li><strong>The production of critical minerals needed for AI hardware <\/strong>also raises concerns about environmental degradation and social inequities in extraction regions.<\/li>\n\n\n\n<li><strong>Disparities: <\/strong>More than 90% of AI-specialised computing capacity is concentrated in just two countries \u2013 the United States and China. At the same time, over 150 nations lack significant domestic AI infrastructure.\n<ul class=\"wp-block-list\">\n<li>This imbalance not only limits economic opportunities but also raises questions of<strong> environmental justice,<\/strong> as some countries bear the environmental costs without sharing in the benefits of AI-driven growth.\u00a0<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Way Ahead<\/strong><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>The report calls for<strong> urgent action <\/strong>to ensure that the <strong>technology develops within planetary limits.\u00a0<\/strong><\/li>\n\n\n\n<li>The study outlines a framework for a<strong> \u201cresponsible AI ecosystem\u201d<\/strong>, built on principles including <strong>transparency, efficiency by design, equity, lifecycle responsibility, global cooperation and sustainable use.<\/strong>\u00a0<\/li>\n\n\n\n<li>Governments are urged to integrate AI infrastructure into energy, water and land-use planning, while companies are encouraged to design systems that minimise resource consumption.\n<ul class=\"wp-block-list\">\n<li>Users, too, have a role to play by choosing lower-impact applications where possible.\u00a0<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li>Ultimately, the report argues that the future of AI will depend not only on technological innovation but also on governance choices made today.<\/li>\n<\/ul>\n\n\n\n<p><strong>Source: UN<\/strong><\/p>\n","protected":false},"excerpt":{"rendered":"<p><strong> Context <\/strong><\/p>\n<li class=\"ms-5\"> United Nations report Environmental Cost of Artificial Intelligence highlights that by 2030, AI could consume 3% of world\u2019s electricity. <\/li>\n<p><\/p>\n<p><strong> Major Findings <\/strong><\/p>\n<li class=\"ms-5\"> Water and Power Consumption: AI-related water consumption could equal the basic annual domestic needs of 1.3 billion people by the end of the decade. <\/li>\n<li class=\"ms-5\"> Data centres could consume 945 terawatt-hours of electricity annually by 2030 \u2013 nearly triple the combined annual electricity use of Pakistan, Bangladesh, and Nigeria.\u00a0 <\/li>\n<li class=\"ms-5\"> Water and Land Footprint: Every unit of electricity used by data centres also carries a \u201cwater footprint\u201d for cooling and energy production, and a \u201cland footprint\u201d associated with power generation and supply chains. <\/li>\n<p><a href=\" https:\/\/www.nextias.com\/ca\/current-affairs\/05-06-2026\/ai-power-consumption \" class=\"btn btn-primary btn-sm float-end\">Read More<\/a><\/p>\n","protected":false},"author":15,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[21],"tags":[],"class_list":["post-75910","post","type-post","status-publish","format-standard","hentry","category-current-affairs"],"acf":[],"jetpack_featured_media_url":"","_links":{"self":[{"href":"https:\/\/www.nextias.com\/ca\/wp-json\/wp\/v2\/posts\/75910","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.nextias.com\/ca\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.nextias.com\/ca\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.nextias.com\/ca\/wp-json\/wp\/v2\/users\/15"}],"replies":[{"embeddable":true,"href":"https:\/\/www.nextias.com\/ca\/wp-json\/wp\/v2\/comments?post=75910"}],"version-history":[{"count":4,"href":"https:\/\/www.nextias.com\/ca\/wp-json\/wp\/v2\/posts\/75910\/revisions"}],"predecessor-version":[{"id":75914,"href":"https:\/\/www.nextias.com\/ca\/wp-json\/wp\/v2\/posts\/75910\/revisions\/75914"}],"wp:attachment":[{"href":"https:\/\/www.nextias.com\/ca\/wp-json\/wp\/v2\/media?parent=75910"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.nextias.com\/ca\/wp-json\/wp\/v2\/categories?post=75910"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.nextias.com\/ca\/wp-json\/wp\/v2\/tags?post=75910"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}