A literature review on the relationship between energy poverty and artificial intelligence

Alina Georgeta Ailincă ()
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Alina Georgeta Ailincă: "Victor Slavescu" Financial and Monetary Research Center, INCE, Romanian Academy, Bucharest, Romania

International Conference on Machine Intelligence & Security for Smart Cities (TRUST) Proceedings, 2025, vol. 2, 97-107

Abstract: Within the sustainable development goals, an important element is section seven, which talks about affordable, reliable and sustainable energy. At the European Union level, SDGs7 the subject is of increased importance, with extremely high environmental objectives being imposed, including achieving climate neutrality within the next 20 years. In this framework, energy poverty, which describes the inability of households to meet their basic energy needs (for heating, cooking, cooling, lighting), simultaneously touches on issues of social equity, energy infrastructure, climate change and broad socio-economic impact. In this context, although artificial intelligence (AI) raises issues related to a high technological level and huge energy consumption, therefore a possible negative impact on energy poverty, it nevertheless has a great potential to combat it by identifying, forecasting patterns, preventing, mitigating and correcting energy poverty. Prior work, both our own and from the literature, was analyzed to enhance understanding of energy efficiency and artificial intelligence. In this context, the objective of the paper is to to investigate the literature on the capacity of artificial intelligence in alleviating energy poverty by providing solutions on almost all the aforementioned levels (socio-cultural, economic, climate and policy). The results can help us understand what needs to be done further to improve the fight against energy poverty, including from the perspective of population energy security.The implications lie in the factthat it can be of assistance to the state, national and international organizations, local administrations, citizens and non-governmental organizations. The value of the study is given by the precariousness of studies on energy poverty (especially at the national level), often being the elephant in the room. In addition, from the perspective of AI possibilities, the approaches in the literature are even more restricted, being able, by their quality, to contribute to the rise from this status.

Keywords: AI; energy; social inequality; energy structure; climate change. (search for similar items in EconPapers)
JEL-codes: O35 (search for similar items in EconPapers)
Date: 2025
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