The Use of Artificial Intelligence in Enhancing Accountability and Transparency in South African Municipalities: Prospects, Barriers and Strategic Pathways for Local Government
TL;DR
The study concludes that AI should be treated as a governance support tool rather than a complete solution to municipal failure, because its value depends on phased implementation, data modernisation, capacity building, legal safeguards, human oversight and inclusive citizen engagement.
Abstract
This study examined how artificial intelligence (AI) can enhance accountability and transparency in South African municipalities. The study responded to persistent municipal governance challenges, including weak financial oversight, fragmented data systems, service delivery inefficiencies and declining public trust. A systematic review design was adopted to synthesise global, African and South African evidence on AI adoption in public administration and municipal governance. The review was guided by PRISMA principles and included 43 eligible studies selected from academic, policy and institutional sources. The Technology Acceptance Model and Institutional Theory were used to interpret both user-level and institutional factors influencing AI adoption, including perceived usefulness, perceived ease of use, staff readiness, organisational resistance, regulatory pressure and governance norms. The findings show that AI can support municipal accountability through fraud detection, procurement monitoring, audit support and anomaly identification. AI can also improve transparency through citizen-service chatbots, complaint-routing systems, open data tools and integrated information platforms. However, the review found that AI adoption in South African municipalities is constrained by poor digital infrastructure, weak data interoperability, limited technical skills, financial pressure, organisational resistance and unclear ethical governance arrangements. The study concludes that AI should be treated as a governance support tool rather than a complete solution to municipal failure. Its value depends on phased implementation, data modernisation, capacity building, legal safeguards, human oversight and inclusive citizen engagement. Future research should examine municipal-level AI implementation, public trust, algorithmic accountability and the effects of AI on equitable service delivery.