Following the recent African Union–Africa Water Investment Summit 2025 in Cape Town: Third International Conference on Earth and Environmental Sciences 2025 (ICEES 2025) in Durban, a strong call emerged to enhance cooperation and strengthen institutional support mechanisms to achieve the Sustainable Development Goals, particularly SDG 6.

A central theme was the necessity for united, collaborative action and deep reforms to foster a resilient and water secure future. It is encouraging to see a strong focus on strengthening data and information systems to improve decision-making and to better track sector performance in relation to SDG 6.

Data-drive approaches

Data and information linked to identified strategic water security support mechanisms (policy, technical and financial institutional interventions, as well as behavioural change programmes) still lack high-predictive accuracy. Therefore, data-driven approaches, like AI, machine learning (ML) and IoT architecture are becoming even more crucial.

Moreover, while the challenges of climate variability in water resource planning and infrastructure design are being studied, the lack of high-quality primary data in water risk assessments and management plans often leads to poorly informed decisions, particularly when scaling water security measures in resource-constrained areas. The need for real-time data-driven adaptive AI frameworks as well as the integration (and interoperability) of large and often complex IoT is thus self-explanatory.

While demands for more systems-thinking frameworks and procedures by water utilities are equally gaining importance, data-driven approaches that translate large complex (and real-time) high-quality datasets into practical information is key for improved water resilience.

Over the past few decades, advancements in data collection techniques, digital platforms, decision-support tools, including increased awareness and need towards citizen science, have enhanced our ability to consider water security interventions in considerable detail.

Nevertheless, the value of such advancements remains inadequate unless these are effectively applied in decision-making. Data-driven approaches or frameworks thus highlight the dire need for water centres of excellence focusing on water security interventions that link science, engineering and technology outputs with stakeholder needs and priorities.

Bridging this gap requires co-produced knowledge, data-driven approaches that take stakeholders into consideration directly, and iterative engagement processes that promote mutual knowledge, understanding and trust among water science-engineering-technology (SET) practitioners, policymakers, civil society groups and local communities.

While water management networks are complex and challenging in nature, the development of integrated data-driven systems would enable faster responses to complex water management and operational needs, as well as supporting policy and business operating decisions through streamlined access to relevant high-quality (and fit-for-purpose) water use data. Harnessing data-driven approaches in water management is therefore key, as it further encourages decision-makers to embrace innovative technological solutions and tools that are crucial in achieving planned aligned to SDG 6

By Dr. Harrison Pienaar, chairman, WISA