Sustainable Development and Artificial Intelligence: The Case for AI in Water Infrastructure

Author: Makhosazane Luthuli

I was invited by AUDA-NEPAD to participate as a panellist at the Third Infrastructure Financing Summit (LFS) held in Luanda, Republic of Angola, from 28-31 October 2025, under the general theme: “Infratech & Innovation Forum: Accelerating African Infrastructure through Home-grown Digital Solutions.” On this platform, I facilitated a focused group discussion on AI in water infrastructure development across Africa. With this hot topic and expert participants from across the continent, there was no shortage of engaging conversations and robust debate! This blog aims to share the knowledge and experience I gained from the session. I wish to extend my sincere thanks to AUDA-NEPAD for their kind invitation.

Climate change is rapidly intensifying the water crisis across Africa, manifesting as extreme weather events, erratic rainfall, and higher temperatures that threaten both human livelihoods and vital ecosystems. While this challenge is immense, Artificial Intelligence (AI) is emerging as an important component of Africa’s water infrastructure development plans. AI can provide crucial support for climate change adaptation, particularly in water infrastructure and resource management, promising to improve efficiency and resilience. However, realising AI’s full potential requires us to first navigate and address several significant constraints.

When we consider the state of water infrastructure development across Africa, and the vast needs that remain unmet across regions, it can be difficult to conceptualise, let alone integrate, the topic of artificial intelligence in water infrastructure. This was the sentiment shared by participants in the AI labs discussion group that I facilitated during the Luanda Financing Summit 2025. There was a sense that in some countries such as Chad, where basic water infrastructure is lacking, any discussion about AI is premature. Conversely, participants from countries with more developed water infrastructure such as Egypt felt that AI cannot be ignored and that it is important to leverage this technology for effective climate adaptation. Participants form South Africa and Kenya cited numerous problems they experience at a municipal level from ageing pipes and non-revenue water to the escalating impact of climate change emphasising that these issues require a decisive, modern approach which may include AI.

In this context, and with these mixed sentiments, the discussion group explored the notion that the integration of Artificial Intelligence into water infrastructure is a fundamental pillar of Africa’s sustainable development and climate adaptation. Whatever the state of Africa’s infrastructure today, merging technology with basic infrastructure is a practical way forward towards the achievement of the AU Agenda 2063 goals for The Africa We Want.

At Allegro, we have previously shared insights on how earth observation data can used to achieve sustainable development objectives, including sustainable water management. The integration of AI in sustainable water management is a growing field of study for us as consultants, but it is already moving beyond proof-of-concept and demonstrating tangible results in key African nations:

South Africa: Tackling Non-Revenue Water and Transboundary Management

In South Africa, where municipalities lose a staggering amount of treated water to leaks and poor management, integrating AI into water management is an imperative. A relatable example is that of leak detection and predictive maintenance. Companies are developing AI-powered platforms that analyse real-time pressure and flow data from existing systems. This allows for predictive maintenance, pinpointing hidden leaks and forecasting pipe failures beforethey occur. For municipalities with drastically reducing the country's non-revenue water losses. This saves both water and significant financial resources.

The Limpopo Water Copilot project, spanning South Africa, Botswana, Mozambique, and Zimbabwe, is a landmark example of transboundary water governance in Southern Africa. It uses a Digital Twin of the river basin, integrating real-time data and historical satellite imagery with generative AI. This provides water managers with reliable, scientific insights to effectively coordinate management strategies, which is paramount for climate adaptation in a shared, drought-prone basin.

Egypt: Precision for Water-Intensive Agriculture

The Egyptian landscape is known to be mostly desert, but for the Nile river. Facing acute water scarcity, Egypt is deploying AI to secure its vital agricultural sector, which consumes the majority of the nation's water.

• Smart Irrigation: Projects like Ai4Water utilise AI alongside satellite imaging and moisture sensors. Farmers receive timely, customised guidance on water usage based on soil chemistry, weather, and crop type. This move away from traditional flood irrigation allows for precision watering, leading to significant water conservation and more resilient food security in the face of climatic variability.

• Optimising Desalination: Researchers are employing AI to optimise the development and performance of novel, nano-enhanced membranes used in desalination plants. By using Artificial Neural Networks to predict how membranes will perform under various conditions, the technology can lower the energy consumption and cost of increasing the fresh water supply—a vital climate adaptation strategy for coastal regions.

Why The Merger of AI and Water Infrastructure is so compelling

The challenge of sustainable development is inseparable from climate adaptation. Climate change is introducing greater uncertainty—extreme droughts, unpredictable rainfall, and catastrophic flooding—which our existing, analogue infrastructure is simply not equipped to handle.

1. Resilience through Prediction: AI allows us to shift from a reactive to a predictive model of water management. It forecasts demand, predicts flood and drought events with greater accuracy, and identifies pollution risks, enabling authorities to act decisively before a crisis hits.

2. Efficiency is the New Source: For water-stressed regions, the most immediate source of 'new' water is eliminating wastage. AI-driven systems can cut water losses by a substantial margin, ensuring that every drop of treated water reaches its intended community, thereby improving service delivery and social equity.

3. Future-Proofing Investment: As African nations seek large-scale investment for infrastructure, integrating AI makes projects more attractive, robust, and future-proof. It ensures that the continent is building smart, responsive, and durable systems that can withstand the mounting pressures of urbanisation and a rapidly changing climate.

The marriage of technology and water infrastructure demands a serious paradigm shift. It is not enough for us to say that Africa needs to focus on building basic infrastructure before considering AI. The very present challenges posed by climate change require us to take a holistic and future-fit view of sustainable development where technology is an enabler and enhancer of infrastructure development, that supports a sustainable and resilient future for all Africans.