WEF urges MENA nations to treat AI data centres as critical loads and boost power capacity

The World Economic Forum has urged Middle East and North Africa (MENA) nations to label artificial intelligence (AI) data centres as “critical dynamic loads” and to overhaul energy planning. The forum’s report says the region must raise electricity capacity by 40 % by 2030, yet current forecasts show only a 15 % rise. It warns that the shortfall could cripple MENA’s goal of becoming a global AI‑infrastructure hub. The report recommends governments separate AI data centres from ordinary industrial users, mandate energy‑demand forecasts and set up coordination among developers, utilities, grid operators and regulators. Projects with more than 10 megawatts of IT load must file detailed electricity‑demand forecasts when applying for grid connection. AI server racks draw 30‑100 kilowatts each, far above the 3‑10 kilowatts typical of traditional web workloads. Sudden spikes or drops in demand could destabilise grids, especially if several facilities switch on or off together. Cooling consumes over 40 % of data‑centre power in the region, and extreme heat combined with limited water supplies raises operating costs. To mitigate risks, the forum outlines four action areas: smarter infrastructure design, integrated energy systems, advanced cooling and water management, and forward‑looking regulation. It pushes for more solar power with battery storage, on‑site generation, AI‑based energy management, closed‑loop cooling, and treated wastewater reuse. Small modular nuclear reactors and enhanced geothermal systems are mentioned as longer‑term options, though their commercial viability remains uncertain. Behind‑the‑meter generation could cut data‑centre rollout time by 12‑36 months by reducing reliance on the utility grid. The report also calls for harmonised regulatory standards and cross‑border cooperation to boost investment confidence.

Context

Classifying AI data centres as critical loads signals that their power needs are essential for national infrastructure, similar to hospitals or airports. This approach helps planners allocate sufficient capacity and design safeguards against grid failures.