Resumen

BALOYI, Wiston Mbhazima; MEYER, Natanya  y  ROSSOUW, Dirk. A critical review of the enablers and constraints of artificial intelligence in the South African public sector. JCMAN [online]. 2025, vol.22, n.1, pp.1-24. ISSN 1815-7440.  https://doi.org/10.35683/jcman1185.302.

PURPOSE OF THE STUDY: Artificial intelligence (AI) is increasingly reforming the value chain activities of the public sector to meet the citizens' demands, thus triggering the need to comprehend the enablers and constraints in the industry. This study provides a critical review of the enablers and constraints to the adoption of artificial intelligence (AI) in enhancing public sector management practices in South Africa. DESIGN/METHODOLOGY/APPROACH: The study employs a qualitative approach, utilising a critical document review (an unobtrusive form of research) and the extensively applied Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) to analytically investigate the enablers and constraints of AI adoption in enhancing management practices in the South African public sector. The literature was sourced from the Web of Science search engine from 2022 to 2025. FINDINGS: The study aimed to critically review the enablers and constraints of AI adoption to enhance South African public sector management practices. The results of the study reveal that even though AI releases a plethora of opportunities for public sector organisations, such as intensified operational efficiency, cost-effectiveness, increased productivity, and effective disbursement of resources, it has also been linked to the possibility of job displacement, ethical issues (such as data privacy and security, transparency and accountability) and AI legal and regulatory frameworks (governance) issues. RECOMMENDATIONS/VALUE: This study contributes to management research by identifying and critically evaluating the prevalent enablers and constraints in AI adoption and implementation in emerging economies, such as South Africa. It recommends the enforcement of ethical and regulatory frameworks for navigating the adoption of AI technologies in enhancing management practices in the South African public sector. Furthermore, the study adopts Tornatzky and Fleischer's (1990) technology-organisation-environment framework to appraise the public sector organisations in terms of the three contextual factors. MANAGERIAL IMPLICATIONS: The study sheds light on the current state of policies and strategies that are significant for governing and enhancing AI adoption in advancing management processes within the South African public sector. Considering that South Africa is not exempt from achieving the United Nations' Sustainable Development Goals (SDGs) Vision and Trajectory 2030, the study provides crucial insights and guidelines to policymakers, practitioners, and decision-makers as a basis for managing AI adoption and improving general management processes in the South African public sector. JEL CLASSIFICATION: O32, O55

Palabras clave : Artificial intelligence; public services; PRISMA; public sector; South Africa.

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