The rise of AI factories
Only eighteen months ago, ‘hyperscale’ referred to facilities supporting c.50 megawatt (MW) of data centre load. This is roughly the amount needed to power around 50,000 homes, or a small city. Fast forward to today and we are talking about 5 gigawatt (GW) data centre campuses, or ‘AI factories’ as Jensen Huang of Nvidia calls them – enough to power around 5 million homes simultaneously, or the entire state of Mississippi.
Projects announced since January 2025 are redefining the scale of data centres: Humain’s 500 MW "AI Zone" in Saudi Arabia, G42’s colossal 5 GW UAE-US AI Campus near Abu Dhabi and America's audacious “Project Stargate” collectively amass to c.10 GW of new data centre capacity, over a million Blackwell-class GPUs, and total capital investments nearing $700 billion by the end of the decade.
The UAE’s planned 5 GW AI campus illustrates this new scale, spanning roughly ten square miles – larger than Monaco. Its scale not only accommodates vast arrays of computing infrastructure but also supports substantial renewable and nuclear power generation facilities alongside water desalination plants. Meanwhile, Saudi Arabia’s 500 MW Humain AI Zone will initially house 18,000 Blackwell GB300 GPUs and benefit from a $10 billion AMD supply agreement, complemented by custom Qualcomm Arm-based CPUs designed specifically to maximise GPU performance.
Across the Atlantic, Stargate’s first campus in Abilene, Texas, aims for a substantial 1.2 GW capacity, eventually scaling up to 400,000 NVIDIA GB200 GPUs. This campus will form part of a wider network of 20 US-based locations, collectively drawing approximately 5 GW of power and generating around 100,000 direct jobs. Stargate outstrips all previous private infrastructure initiatives since World War II.
Why scale matters
These are big numbers. But the size of the prize is equally eyewatering: a 100,000-fold improvement for agentic workloads within five years, which will benefit first movers most. AI models are now scaling along three frontiers: pre-training scaling, post-training, and inference time reasoning. The rationale behind these massive data centre expansions stems from the persistent improvement in model performance with increasing compute power: each generation of large language model requires c.10x more compute, and as a result, have been getting 3-4x ‘smarter’ every year.
Meanwhile, chip architectures are also getting c.4x more performant every year (the performance-per-watt leap from Nvidia’s Hopper architecture to Blackwell is 4x). Layer on top algorithmic enhancements (such as DeepSeek’s breakthrough in January), and you get a compounding effect that is exponential. Wall Street is notoriously poor at modelling exponentials, but sovereign governments appear to have grasped what is at stake.
Strategic and geopolitical implications
The Middle East has an abundance of energy but a shortage of labour. The massive projects announced in the past week underscore a drive to translate this energy into digital labour and benefit from the exponential progress in AI system capabilities. These deals are also decisive wins for the US, benefitting not only from reciprocal investment in US data centre infrastructure and energy, but also an expanded market for US technology. In the space of just two weeks, the US has pivoted from restricting the export of its technology to acting as its distributor. The implications are significant.
The industrial, market, and geopolitical ramifications of these projects are profound. Extensive pre-orders of GPUs by Saudi Arabia, the UAE, and Project Stargate effectively lock in a significant proportion of Nvidia’s production capacity through 2027, granting unprecedented pricing and strategic leverage. Meanwhile, these massive facilities reshape power markets globally, their cumulative draw rivalling entire national grids like Sweden’s nuclear fleet, driving direct agreements between cloud providers and energy firms.
The future of AI infrastructure
We believe the scale of these "AI factories" will deliver decisive competitive advantages. States and organisations capable of hosting such facilities will realise dramatic reductions in operational costs, expedited model tuning, and unmatched training capabilities. Smaller players risk obsolescence unless they pivot strategically or federate within these mega-facilities.
The staggering scale of facilities announced in Riyadh, Abu Dhabi, and Texas represent not outliers but logical steps in a computational arms race driven by transformer architectures since 2017. Jensen Huang’s vision of data centres as AI factories is no longer speculative; it is our emerging reality, prompting the fundamental question: will today’s 5 GW campuses become tomorrow's standard or merely prototypes for something even more ambitious?
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