Original Research

Municipal employee perceptions on the use of artificial intelligence to perform their work

Libokazi Bunyula, Sithenkosi Lungisa, Qaqambile Mathentamo
South African Journal of Economic and Management Sciences | Vol 28, No 1 | a6203 | DOI: https://doi.org/10.4102/sajems.v28i1.6203 | © 2025 Libokazi Bunyula, Sithenkosi Lungisa, Qaqambile Mathentamo | This work is licensed under CC Attribution 4.0
Submitted: 28 March 2025 | Published: 12 December 2025

About the author(s)

Libokazi Bunyula, Department of Applied Management, Administration and Ethical Leadership, Faculty of Management and Commerce, University of Fort Hare, Alice, South Africa
Sithenkosi Lungisa, Department of Applied Management, Administration and Ethical Leadership, Faculty of Management and Commerce, University of Fort Hare, Bhisho, South Africa
Qaqambile Mathentamo, Department of Accounting, Economics and Innovations, Faculty of Management and Commerce, University of Fort Hare, East London, South Africa

Abstract

Background: Over the past 30 years of democracy, South Africa has undergone a significant technological transformation, with an increasing integration of artificial intelligence (AI) in government operations. Local governments remain reliant on manual systems, resulting in inadequate service delivery, community protests, and corruption.
Aim: This study assessed municipal employees’ perceptions of using AI in their work, highlighting a research gap in reliance on manual systems that contribute to poor service delivery, community unrest, and corruption. The findings underscore the need for electronic management systems and a deeper understanding of employee perceptions of AI.
Setting: The study was conducted in the Buffalo City Metropolitan Municipality (BCMM) in the Eastern Cape Province of South Africa.
Method: A quantitative, hypothetical-deductive study employed structured questionnaires to assess the perceptions of 255 employees in BCMM’s corporate services and finance divisions, utilising a cross-sectional, purposive sampling design.
Results: Employees generally view AI positively, recognising its advantages. Structural Equation Modelling results indicate that a low perceived ease of use hinders performance, while positive attitudes and perceived usefulness enhance it, highlighting the challenges in experience and capacity-building for effective AI use.
Conclusion: Municipalities can enhance employee performance and service delivery by implementing user-friendly systems and cultivating a positive attitude towards AI. Furthermore, strategic investment in employee retention and institutional capacity building is crucial for the effective and efficient adoption of AI.
Contribution: This study contributes to the limited literature on electronic management systems and provides insights to improve employee perceptions and adoption of AI within municipal contexts.


Keywords

perceived usefulness; ease of use; attitudes; financial management; artificial intelligence; Buffalo City Metropolitan Municipality

JEL Codes

D24: Production • Cost • Capital • Capital, Total Factor, and Multifactor Productivity • Capacity; J24: Human Capital • Skills • Occupational Choice • Labor Productivity; M53: Training

Sustainable Development Goal

Goal 9: Industry, innovation and infrastructure

Metrics

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