State-Owned Companies and Artificial Intelligence: Strategies for Addressing the Socio-Economic Challenges in South Africa

Khumalo, Thandiwe Euphronia and Lekhanya, Lawrence and Anwana, Emem (2025) State-Owned Companies and Artificial Intelligence: Strategies for Addressing the Socio-Economic Challenges in South Africa. In: Information Management and Technology: The Proceedings of the 10th International Conference on Business and Management Dynamics (ICBMD), Edition 1. 1 ed. BP International, pp. 196-221. ISBN 978-93-49238-57-2

Full text not available from this repository.

Abstract

In South Africa, leveraging artificial intelligence within state-owned companies (SOCs) presents a unique opportunity to address the various socio-economic challenges facing the country, while fostering innovation and efficiency in the public sector. This paper examines how artificial intelligence can be optimized within South African state-owned companies to address socio-economic challenges, foster innovation, and improve service delivery, resource management, and infrastructure maintenance. The study employs a doctrinal analysis methodology to assess relevant legislation, such as the Companies Act 2008 and the Public Finance Management Act 1999, as well as the King IV Report on Corporate Governance. Additionally, the paper uses a qualitative approach to gauge the perspectives of SOC managers on AI adoption by conducting interviews with relevant stakeholders. The findings suggest that a comprehensive strategy focused on capacity building, strategic prioritization, public-private collaboration, ethical considerations, data-driven decision-making, public engagement, regulatory oversight, and long-term sustainability can enable South Africa to harness the transformative potential of AI to tackle socio-economic issues and promote inclusive growth and development. The paper aims to assist decision-makers, managers, and policymakers in understanding the legal and policy frameworks necessary to leverage the potential of AI in SOCs.

Item Type: Book Section
Subjects: STM Open Press > Multidisciplinary
Depositing User: Unnamed user with email support@stmopenpress.com
Date Deposited: 26 Feb 2025 05:19
Last Modified: 26 Feb 2025 05:19
URI: http://resources.peerreviewarticle.com/id/eprint/2244

Actions (login required)

View Item
View Item