For some time now, the Middle East’s AI story has leaned heavily on spectacle. Saudi Arabia has announced eye-catching projects, from its $10 billion AI hub with Google Cloud to The Line, the futuristic smart city designed to showcase next-generation technology at a massive scale. Meanwhile, the UAE is unveiling the 5‑gigawatt Stargate AI campus in Abu Dhabi, backed by OpenAI, Nvidia, Oracle, and SoftBank.
However, while those are the sort of loud, visual, and easy-to-sell narratives that the front pages love, they can also be misleading. The real contest for AI power will not be decided by press conferences or model launches, but rather by who controls the infrastructure that serious AI systems cannot function without. And on that front, Qatar is not chasing headlines. Instead, it is focusing on quieter, less visible moves that matter over the long term.
Laying the foundations that matter
Right now, banks, hospitals, energy companies, government departments, and every other institution sitting on terabytes of invaluable data are facing the same dilemma: to gain insights from AI, they must expose their most proprietary or regulated information. The trust gap has quietly blocked AI’s move from pilot projects to daily use in mission-critical systems.
Qatar’s recent moves show it understands both sides of this problem. First, the $20 billion partnership between the Qatar Investment Authority and Brookfield targets the physical foundations of AI — compute capacity, data centers, and power — that are essential for running enterprise AI.
Brookfield has publicly estimated that global AI infrastructure spending could reach $7 trillion in the next decade, a figure that should move the conversation from software bravado to industrial reality.
However, infrastructure alone does not solve the trust problem.
Second, Qatar is hosting the Gulf’s first confidential AI computing facility, funded by MBK Holding, built by AILO, and anchored by OLLM as its primary user. That matters more than it sounds.
Confidential AI allows data to remain encrypted while being processed, not just while stored or transmitted. That distinction is everything, for without it, AI will stay trapped in labs and pilot programs, while with it, the technology should enter production, as it allows for the conditions that make enterprise AI legally viable. Jurisdictions that ignore this constraint are building systems that businesses dealing with sensitive data simply cannot touch.
Keeping data encrypted end-to-end changes who can deploy advanced models and where. It removes the tradeoff between capability and compliance. That is why confidential computing has become a prerequisite for enterprise AI in regulated sectors, and Qatar is not waiting for this shift to arrive; it is building for it now.
Substance over scale
Some may argue that Qatar’s approach lacks scale compared with the Saudi megaprojects or the Emirati chip clusters. However, that critique misses the point, which is that AI power does not accumulate linearly, but rather compounds where trust, regulation, and infrastructure meet.
There is little value in building dozens of massive AI data centers if businesses, governments, and the public do not trust the systems running inside them.
At this point, the focus is moving away from raw AI capability and toward questions of privacy, data protection, and accountability. High-profile controversies around data use, law-enforcement access, and the treatment of sensitive information have made many institutions more cautious. As a result, the limiting factor for AI adoption is no longer computing power alone, but whether people are willing — and legally able — to use it.
It means that the next phase of AI adoption will not reward whoever trains the biggest model; instead, it will reward whoever can deploy the tech safely inside systems that already carry legal and ethical risk. And that is where confidential AI will shift the balance.
Once regulators start demanding guarantees that data accessed by AI will not appear in plaintext, even during computation, then expect entire classes of AI deployment to move to environments that can provide such guarantees.
The $20 billion partnership between the Qatar Investment Authority and Brookfield lays the groundwork for power, data centers, and compute. The push into confidential AI tackles the next problem — trust — making it possible for banks, governments, and other regulated institutions to use AI without exposing sensitive data.
This approach treats AI as something that compounds over time. It favors patient capital, secure infrastructure, and regulatory fit over speed or hype.
It isn’t advisable for countries to skip any of these steps, since, instead of accelerating dominance, they’ll only be creating fragility, especially considering a geopolitical dimension that some prefer to ignore.
As I see it, AI is set to become one of the most consequential technologies ever, and in that scenario, sovereignty will no longer be defined by borders alone. It will be determined by where the data is processed and who controls the machines processing it. Because of that, any country relying on foreign cloud infrastructure for key services will be surrendering strategic autonomy. Essentially, AI leadership without infrastructure control is an illusion, and Qatar recognizes this, hence the investment in local, integrated compute.
Now, if people were to compare its approach with that of its regional peers, they would notice the stark contrast. On one hand, Saudi Arabia’s spending blitz risks creating impressive capacity that could end up being underused by risk-averse enterprises.
That would be a serious risk for economies that are investing heavily in AI as a way to reduce long-term dependence on oil revenues. If large amounts of compute sit idle, the economic return on those investments weakens.
There is also a deeper irony at play. Large-scale AI infrastructure depends heavily on energy, much of it still tied to fossil fuels. In that sense, the push away from oil and the reliance on energy-hungry compute are two sides of the same coin.
On the other hand, the UAE’s alliances guarantee access to chips, but they also deepen the country’s reliance on external actors for governance and deployment. Turning chips into trusted, widely adopted systems also requires deep, sustained technical talent and governance frameworks that global users are comfortable relying on.
At present, much of the region’s AI execution still depends on international partnerships, expatriate expertise, and outsourced teams. That model can accelerate early progress, but it also raises questions about long-term capability and trust. For many Western governments and enterprises, who controls an AI system — and under which legal and political framework it operates — matters as much as the technology itself.
When export controls tighten, and access to advanced hardware becomes politicized — as seen in the ongoing chip wars between the U.S. and China — countries that rely on goodwill alone could find themselves quite exposed.
However, Qatar’s alignment with the U.S. and European regulatory standards, combined with its investment-led partnerships, should help reduce that exposure drastically. The country is not trying to outspend its neighbors; instead, it is making itself indispensable to serious AI operators who will need stability, compliance, and long-term certainty.
Quiet accumulation of real power
To sum it up, Qatar’s focus on hard, practical infrastructure, while not as glamorous as the big model launches or flashy megaprojects of its neighbors, is what will pay off in the long run.
According to estimates, the nation’s AI sector could be worth more than $567 million by the end of 2025, boosting its economic growth by 2.3% and generating up to $5 billion in revenue by 2030.
Dominating the Middle East’s AI space will require more than just the biggest language model or the most popular startup funds. It’ll require owning the most secure, most scalable, and most independent infrastructure that all future apps will need. And Doha is building leverage by focusing on compute power, data integrity, and energy advantage — a patient strategy whose effects on the market will matter.
Benzinga Disclaimer: This article is from an unpaid external contributor. It does not represent Benzinga’s reporting and has not been edited for content or accuracy.
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