SPSS Assessment of Artificial Intelligence for Effective Decision Making in Water Management in South Africa

The study investigated the transformative potential of artificial intelligence (AI) in South Africa's water management, addressing challenges posed by population growth, climate change, and water scarcity. Employing a mixed-method research design, both qualitative and quantitative methodologies were integrated, aligning with a pragmatic research philosophy. Thematic analysis interpreted qualitative data, while statistical methods, including SPSS, analyzed quantitative data. Challenges in water management were unveiled, emphasizing water scarcity's significance. Population growth, climate change, and water scarcity impacts on decision-making were explored, revealing concerns such as unplanned settlements and increased demand. AI's benefits in improving decision-making, conserving water, and enhancing food security were underscored. Recommendations for AI tools enhancement included open data initiatives and stakeholder cooperation. The study's outcomes contribute valuable insights for policymakers, water managers, and researchers in navigating South Africa's water management complexities. Despite the comprehensive approach, acknowledgment of limitations and ethical considerations, including participant confidentiality, were prioritized. The study highlights AI's potential to revolutionize water management practices, laying the groundwork for future advancements in the field.