{"id":560,"date":"2026-10-07T09:54:27","date_gmt":"2026-10-07T09:54:27","guid":{"rendered":"https:\/\/www.journals.utgjiu.ro\/JES\/?post_type=articol&#038;p=560"},"modified":"2026-10-07T09:54:27","modified_gmt":"2026-10-07T09:54:27","slug":"the-net-impact-of-artificial-intelligence-on-the-energy-transition","status":"publish","type":"articol","link":"https:\/\/www.journals.utgjiu.ro\/JES\/articol\/the-net-impact-of-artificial-intelligence-on-the-energy-transition\/","title":{"rendered":"The Net Impact of Artificial Intelligence on the Energy Transition"},"content":{"rendered":"<p>This article examines the net climate impact of artificial intelligence in the energy transition. The study is conceptual and is based on a structured narrative review of scientific literature and institutional documents published between 2020 and 2026. Drawing on the contributions reviewed, it proposes a counterfactual accounting framework that compares total emissions associated with the use of artificial intelligence with the emissions estimated for a situation in which the technology is not used. The change in emissions is decomposed into four components: emissions from digital infrastructure, changes arising from the scale and structure of production, demand rebound effects, and emissions avoided through efficiency gains. The framework is applied to Romania\u2019s industrial sector through three sensitivity scenarios, using official data for 2024. Depending on the share of industrial electricity consumption affected by AI applications and the assumed reduction in energy use, the results indicate annual electricity savings ranging from 5.121 to 136.562 GWh and avoided operational emissions ranging from approximately 963 to 25,674 t CO\u2082e. These values are conditional on the scenario assumptions and do not represent savings already achieved. The results show that reducing energy use per unit of output does not guarantee a reduction in total emissions, because the net climate benefit also depends on the footprint of computing infrastructure, changes in output, and rebound effects.<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}}},"class_list":["post-560","articol","type-articol","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/www.journals.utgjiu.ro\/JES\/wp-json\/wp\/v2\/articol\/560","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.journals.utgjiu.ro\/JES\/wp-json\/wp\/v2\/articol"}],"about":[{"href":"https:\/\/www.journals.utgjiu.ro\/JES\/wp-json\/wp\/v2\/types\/articol"}],"wp:attachment":[{"href":"https:\/\/www.journals.utgjiu.ro\/JES\/wp-json\/wp\/v2\/media?parent=560"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}