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AI workloads force a fundamental redesign of Middle East datacentres | Computer Weekly

By Computer Weekly by By Computer Weekly
March 5, 2026
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As artificial intelligence (AI) workloads reshape global IT infrastructure, datacentres are undergoing their most profound transformation in decades. According to Faisal Ameer Malik, CTO for Enterprise Business in the Middle East & Central Asia at Huawei, the shift from the digital era to the AI era demands a complete architectural rethink, from power and cooling systems to networking, storage and management layers.

Following the launch of Huawei’s AI-centric SuperPoD architecture at Mobile World Congress 2026 in Barcelona, Malik described AI as a structural, not incremental, change. “Huawei anticipated the transition years ago,” he said. “AI doesn’t simply sit on top of digital infrastructure, it requires a redesign of the entire datacentre stack.”

Unlike traditional enterprise workloads, AI training and inference demand ultra-high compute density, lossless networking and data systems capable of feeding GPUs at enormous scale. Malik argued that only a full-stack, end-to-end approach can deliver the performance, elasticity and reliability AI datacentres require. “This holistic integration ensures high performance, energy efficiency and always-on reliability at large scale,” he added.

As GPU density rises, so too do power and thermal demands. Energy consumption has become one of the defining constraints of AI infrastructure, particularly in regions such as the Middle East, where climate conditions intensify cooling challenges. The company is addressing this through high-efficiency UPS systems capable of reaching 96.6% efficiency, as well as compact power designs that reduce footprint by around 25% for AI datacentres.

Aligning with sovereign AI ambitions

The Middle East has emerged as one of the world’s fastest-growing AI infrastructure markets, driven by national transformation programmes such as Saudi Vision 2030, UAE Vision 2023 and Qatar National Vision 2030. Governments across the region are investing heavily in sovereign AI capabilities, hyperscale GPU facilities and national cloud platforms.

Malik said these priorities directly influence Huawei’s regional strategy. Beyond supplying technology, the company positions itself as a consulting and ecosystem partner, supporting governments and enterprises in building AI use cases across finance, healthcare, education, energy and public services.

“AI infrastructure alone is not enough,” he said. “We work closely with industry partners to build real use cases that deliver measurable value and ensure that investments translate into intelligent transformation.”

Data sovereignty is another key driver. Regional governments increasingly require local data residency, privacy compliance and national resilience amid shifting geopolitical dynamics. Malik expects sovereign AI model training, including Arabic-language large language models (LLMs), to become a defining feature of the next wave of AI datacentre deployments.

While capital investment is strong, specialist skills remain a bottleneck for many organisations seeking to deploy AI at scale. The company is investing in talent development through more than 330 ICT Academy partnerships across the region. Huawei said it has supported around half a million students, alongside local training centres and initiatives such as its 1,000,000 Digital Talents programme. The goal is to close the gap between experimentation and production-scale AI.

The road ahead: hyperscale, sustainability and localisation

Looking ahead, Malik expects explosive growth in regional AI capacity over the next few years, with GPU-dense facilities reaching gigawatt-scale as sovereign investments and mega-projects come online.

He predicts that datacentre capacity could triple or more, supported by rapid hyperscale expansion, the adoption of advanced liquid cooling, and deeper integration of renewable energy sources to address power and water constraints. At the same time, stronger localisation – from sovereign cloud frameworks to Arabic-language AI models – will define the region’s AI identity.

“The Middle East has the ambition, capital and strategic vision to become a global AI hub,” Malik said. “The next phase is about scaling sustainably, building talent and ensuring that AI delivers tangible value to society and the economy.”



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