Powering AI at Scale: Optimizing Hyperscale Data Centre Infrastructure in MENA

The report highlights the critical need for the MENA region to transition from 'legacy infrastructure' to a 'sustainable nexus' to support the energy-intensive demands of AI. It identifies significant risks, including grid instability due to volatile AI workloads and extreme water stress from cooling needs. The document proposes a four-part strategy involving modular design, behind-the-meter (BTM) energy generation, hybrid cooling solutions, and the reclassification of data centres as 'critical dynamic loads' to ensure long-term infrastructure viability.

• MENA's electricity capacity is projected to need a 40% increase by 2030 compared to 2020 levels, but it is currently on track to grow by only 15%.
• AI workloads create extreme energy volatility, with racks consuming 30–100 kW compared to 3–10 kW for traditional web workloads, which can destabilize conventional grids.
• Extreme heat in MENA significantly increases energy demand for cooling, which can account for more than 40% of total electricity consumption in regional data centres.
• The report introduces a 'resource–intelligence matrix' to move facilities from 'legacy infrastructure' (fossil fuel-heavy and inefficient) to a 'sustainable nexus' characterized by clean energy, AI-optimized operations, and PUE ratios below 1.3.
• Behind-the-meter (BTM) generation, including solar-plus-storage and gas turbines, is recommended to accelerate deployment by 12–36 months by bypassing utility interconnection queues.
• Small modular reactors (SMRs) and enhanced geothermal systems (EGSs) are identified as promising medium-to-long-term baseload solutions, with SMRs expected to reach commercial viability within five to seven years.
• To mitigate water scarcity, the report advocates for hybrid cooling (liquid, immersion, and free cooling), closed-loop systems, and the use of treated wastewater.
• The report argues that data centres should be reclassified as 'critical dynamic loads' rather than static industrial loads to improve grid forecasting and emergency response.
• MENA's current grid connection timelines of two to five years provide a comparative advantage over the US and Europe, but this may erode if infrastructure cannot absorb demand sustainably.

APA

World Economic Forum (2026). Powering AI at Scale: Optimizing Hyperscale Data Centre Infrastructure in MENA. https://reports.weforum.org/docs/WEF_Powering_AI_at_Scale_Optimizing_Hyperscale_Data_Centre_Infrastructure_in_MENA_2026.pdf

Chicago

World Economic Forum. Powering AI at Scale: Optimizing Hyperscale Data Centre Infrastructure in MENA. 2026. https://reports.weforum.org/docs/WEF_Powering_AI_at_Scale_Optimizing_Hyperscale_Data_Centre_Infrastructure_in_MENA_2026.pdf.

Wikipedia

{{cite report |author=World Economic Forum |title=Powering AI at Scale: Optimizing Hyperscale Data Centre Infrastructure in MENA |date=October 2026 |url=https://reports.weforum.org/docs/WEF_Powering_AI_at_Scale_Optimizing_Hyperscale_Data_Centre_Infrastructure_in_MENA_2026.pdf |access-date=23 October 2026 |via=Climate Insights Directory}}

BibTeX

@techreport{worldeconomicforum2026powering, author = {{World Economic Forum}}, title = {{Powering AI at Scale: Optimizing Hyperscale Data Centre Infrastructure in MENA}}, institution = {World Economic Forum}, year = {2026}, month = oct, url = {https://reports.weforum.org/docs/WEF_Powering_AI_at_Scale_Optimizing_Hyperscale_Data_Centre_Infrastructure_in_MENA_2026.pdf}, urldate = {2026-10-23}, note = {Indexed by Climate Insights Directory} }