An  increasingly  popular  subcategory  of  Artificial  Intelligence  (AI)  is  Generative  AI (GAI),  which  encompasses  technologies capable of creating new content, such as images, text, and music, often resembling outputs made by humans. The  potential  impact  by  GAI  on  sustainability  is  multifaceted.  On  the  positive  side,  generative  AI  can  aid  in  optimizing  processes, developing innovative solutions, and identifying patterns in large datasets related to sustainability. This can lead to  more  efficient  resource  management,  reduced  energy  consumption,  and  the  creation  of  more  sustainable  products.  However,  there  are  also  potential  negative  impacts,  such  as  increased  energy  consumption  associated  with  training  and  running  generative  AI  models,  as  well  as  the  potential  for  unintended  consequences  or  biases  in  the  generated  content.  Additionally,  overreliance  on  generative  AI  may  lead  to  reduced  human  oversight,  which  could  undermine  holistic,  interdisciplinary, and collaborative approaches to sustainability. The aim of this paper is to explore the potential impacts on sustainability by generative artificial intelligence through a review of prior research on the topic. The study was conducted with a scoping literature review approach to identify potential impacts by generative AI on sustainability. Data were collected through  a  search  in  the  database  Scopus  during  the  spring  semester  of  2024.  Keywords,  relevant  for  the  study,  were  combined  with  Boolean  operators.  Papers  identified  through  the  search  underwent  a  manual  screening  process  by  the  authors, in which papers were selected for inclusion or exclusion in the study based on a set of criteria. Included paper were then analyzed with thematic analysis, according to the guidelines by Braun and Clarke. A categorization matrix, based in prior research  on  sustainability,  supported  the  analysis  and  deductive  coding  of  collected  data. Results  of  the  study  highlight  generative AI’s potential impact on sustainability that relate to both environmental aspects, economic aspects, and social aspects of sustainability. These different aspects of sustainability impact make this research an important contribution for deepening  the  understanding  of  generative  AI  and  its  potential  consequences  for  society.  Findings  of  the  study  provide  theoretical  contribution,  implications  for  practice,  and  recommendations  for  future  research  on  generative  AI  and  sustainability.