Leveraging Generative AI for Sustainable Development: Opportunities, Risks and Ethical Pathways

Hamza Raza, Khan and Regalla Raghu, Raj and Aslam Raza, Khan and Nur Idayu, Badrolhisam (2025) Leveraging Generative AI for Sustainable Development: Opportunities, Risks and Ethical Pathways. Journal of Business and Social Sciences, 2025 (36). pp. 1-17. ISSN 2805-5187

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Abstract

Generative Artificial Intelligence (GenAI) is emerging as a transformative technology with great potential to advance the United Nations Sustainable Development Goals (SDGs). This paper presents a systematic review of recent research to examine how GenAI contributes to sustainable development in sectors such as education, healthcare, and governance. The study highlights the major opportunities offered by GenAI, including improved productivity, equitable access to information, and data-driven decision making that supports long-term sustainability. At the same time, it identifies critical risks such as high energy consumption, environmental impact, and ethical challenges related to fairness, transparency, and accountability. The review follows the PSALSAR framework to collect, evaluate, and synthesize existing evidence on the benefits and risks of GenAI. It also assesses emerging approaches to responsible AI governance that aim to create an inclusive and sustainable digital ecosystem. By balancing innovation with ethical responsibility, this study provides policy and research recommendations to guide the sustainable and equitable use of generative AI for global development.

Item Type:	Article
Uncontrolled Keywords:	Generative Artificial Intelligence, Sustainable Development Goals, Ethical AI, Responsible AI Governance, Energy Efficiency in AI, Sustainable Growth, Digital Inclusion, Environmental Impact, Data-Driven Decision Making, Sustainable Innovation
Subjects:	G Geography. Anthropology. Recreation > GE Environmental Sciences Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software
Depositing User:	Unnamed user with email masilah.mansor@newinti.edu.my
Date Deposited:	23 Dec 2025 07:39
Last Modified:	23 Dec 2025 07:39
URI:	http://eprints.intimal.edu.my/id/eprint/2269

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