Integrating AI for environmental sustainability in medium to large corporations: a case study of South Africa

Faith Tinonetsana; Priscilla Musariwa; Elvis Madondo

doi:10.36096/ijbes.v6i6.643

Authors

Faith Tinonetsana Doctor, Durban University of Technology, Durban, South Africa https://orcid.org/0000-0002-3401-8247
Priscilla Musariwa Doctor, Durban University of Technology, Durban, South Africa https://orcid.org/0000-0002-8396-2592
Elvis Madondo Doctor, Public Relations Management, Durban University of Technology, Durban, South Africa

DOI:

https://doi.org/10.36096/ijbes.v6i6.643

Keywords:

Artificial Intelligence (AI), Environmental Sustainability, Climate Change, Sustainable Development Goals (SDGs), Corporate Ethos, Ecological Conservation

Abstract

In response to escalating global environmental challenges, mainly the urgent issue of climate change delineated by the United Nations Sustainable Development Goals (UN SDGs), large corporations are increasingly pressured to mitigate their carbon emissions and ecological footprint. The integration of artificial intelligence (AI) technologies has emerged as a pivotal strategy in this endeavour, promising to revolutionise how businesses approach sustainability while maintaining economic competitiveness. AI offers capabilities such as optimising operational efficiencies, enhancing energy management systems, and facilitating data-driven decision-making processes—all of which are instrumental in achieving sustainability objectives. However, the effective application of AI in environmental sustainability initiatives faces several challenges. These include addressing data scarcity, ensuring ethical deployment of AI technologies, and complying with evolving regulatory frameworks. This study investigates how large corporations are leveraging AI to reduce their environmental impact through AI-driven strategies for carbon footprint reduction. The study follows a qualitative approach, six medium-large corporates in Gauteng were interviewed to gain insights on the subject matter. The findings highlight that AI adoption enhances operational efficiency and environmental stewardship while highlighting ongoing challenges and the need for robust ethical and regulatory frameworks. Moreover, emerging trends such as AI-driven autonomous vehicles for logistics and advanced climate modelling illustrate AI's transformative potential in reshaping corporate ethos and addressing environmental concerns. The study contributes insights grounded in the Resource-Based View (RBV) theory, offering practical recommendations for corporations to harness AI effectively for sustainable growth within the framework of the UN SDGs and global environmental norms.

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