Factors Driving Artificial Intelligence Adoption in South Africa's Financial Services Sector

Authors

  • Adewale Samuel Hassan College of Business and Economics, University of Johannesburg, Auckland Park Kingsway Campus, PO Box 524 Auckland Park, Johannesburg, South Africa

DOI:

https://doi.org/10.36941/ajis-2024-0173

Keywords:

artificial intelligence, financial services, South Africa, logit regression, TOE framework

Abstract

Incorporating digital technologies, particularly artificial intelligence, into financial services operations is imperative for achieving critical sustainable development goals (SDGs) through digital financial inclusion. This paper examines the drivers behind AI adoption in South Africa's financial services landscape, given its highly advanced financial sector and rapidly evolving digitisation trends. Drawing on the Technological-Organizational-Environmental (TOE) framework, the study investigates the factors influencing AI adoption through a comprehensive analysis of existing literature, a survey of financial services professionals and binary logistic regression. The results of binary logistic regression indicated that technological, organisational and environmental improvements significantly enhance the likelihood of AI adoption in South Africa's financial services sector. Specifically, access to technological infrastructure, organisational leadership support, and regulatory clarity emerge as key determinants of AI adoption. Overall, this study underscores the need for companies in the financial sector to encourage a culture that welcomes innovation and the integration of AI technology, as well as the need for policymakers to develop comprehensive and unambiguous legislative frameworks that control AI use in financial services.

 

Received: 13 March 2024 / Accepted: 31 August 2024 / Published: 05 September 2024

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Published

05-09-2024

Issue

Section

Research Articles

How to Cite

Factors Driving Artificial Intelligence Adoption in South Africa’s Financial Services Sector. (2024). Academic Journal of Interdisciplinary Studies, 13(5), 394. https://doi.org/10.36941/ajis-2024-0173