Pelser, Theuns2025-04-112025-04-112025-05-052024-11*A2025http://hdl.handle.net/2263/102027Mini Dissertation (MBA)--University of Pretoria, 2024.Digital technologies (DT) and AI are key drivers of Digital Transformation and have revolutionised how businesses operate, resulting in unprecedented progress in promoting sustainability. A critical gap in integrating environmental sustainability considerations within digital transformation (DTx) has been identified. A clear understanding of the relationship between these concepts, among key stakeholders is needed to make informed decisions regarding DTx investments. The manufacturing sector is at a critical juncture as concerns about environmental degradation intensify and sustainable practices become imperative. Studies in a different context found that DTx has the potential to transform traditional capital–intensive manufacturing assets to enhance environmental sustainability. Through an exploratory qualitative study, this research project aimed to identify key success drivers for DTx on environmental sustainability. In particular AI’s impact on greenhouse gas emission (GHG) reduction from the large manufacturing sector companies. This study uncovered eight key drivers for the successful integration of AI technologies for sustainability, defined along both internal and external drivers, and benefits, challenges and risks. The results indicate that while AI adoption is still in the early phase, the study found that the benefits are indirect. Findings confirmed that for a successful AI-driven DTx to advance manufacturing environmental sustainability practices, there are significant hurdles to overcome. The present study will be valuable to researchers, practitioners, and government and policymakers.en© 2024 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria.UCTDDigital transformationEnvironmental sustainabilitySustainable manufacturingIndustry 4.0Artificial intelligence (AI)Mini Dissertationu23984083