Integrating Artificial Intelligence-Driven Principles in Enhancing Water Management: Assessing the Prospects and Challenges in Achieving Water Security in South Africa

Abstract Water management in South Africa is increasingly challenged by climate variability, ageing infrastructure, institutional fragmentation, and persistent inequalities in access to water resources. These factors have exposed limitations in conventional decision-making systems, which are characterised by fragmented data, delayed reporting, and reactive management approaches. In this context, artificial intelligence (AI) offers emerging opportunities to strengthen water governance by improving data integration, predictive capacity, and evidence-based decision making. Using an empirical mixed-methods design, the study integrates quantitative survey data from 150 water-sector stakeholders with qualitative evidence from 10 purposively selected experts and secondary documentary and policy materials to examine the role of AI in strengthening water governance and decision-making in South Africa. The findings reveal that AI can significantly enhance early warning systems, optimise water allocation, detect system inefficiencies such as leakages and non-revenue water, and promote transparent, timely, and adaptive decision-making. However, the study further identifies critical barriers to effective AI adoption, including limited technical capacity, data gaps, high implementation costs, ethical and governance concerns, and uneven institutional readiness across water authorities. This study recommends This study recommends strengthening supportive policy frameworks, capacity development, data governance reforms, and inclusive implementation strategies. Furthermore, it is imperative to strengthen collaboration between government, academia, and the private sector to enable AI-driven solutions contribute to equitable, resilient, and sustainable water management outcomes.