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Artificial intelligence is no longer just a technological breakthrough; it is quickly becoming a linchpin of global power. While countries once focused on military alliances, industrial capacity, or energy resources, many now see AI as a crucial part of their national security and economic strategy.

This notion of “AI sovereignty” recognizes that whoever masters key components of the AI stack — ranging from high-performance computing to regulatory policy — will profoundly influence the world stage. Far from an abstract concern, governments across the globe are already putting billions of dollars into AI labs, ordering top-tier chips, and positioning themselves to attract or develop frontier technologies.

In the next few years, national leaders face a fundamental choice about how they will obtain the compute, data, energy, and regulatory frameworks that power advanced AI models. Some may opt to “build,” pouring resources into domestic research labs, data centers, and homegrown talent. Others may decide to “buy,” forming alliances with hypercenter nations or corporations that can supply cutting-edge hardware and knowledge.

This “build vs. buy” decision is not new in the history of technology. Countries grappled with similar questions when electricity, railroads, and telecommunication networks first arose. However, AI’s speed of evolution and its capacity to encode cultural values and worldviews in digital form make today’s decisions especially urgent.

One way to evaluate a nation’s AI potential is through four interlocking pillars: compute, data, energy, and policy.

Compute refers to access to high-performance hardware capable of training and running large AI models, often requiring specialized chips like graphics processing units. Data encompasses the quantity and quality of datasets that train AI systems necessary for advanced model capabilities.

Energy is the cost and availability of electricity — an increasingly critical factor because running large-scale AI workloads consumes enormous power. Finally, policy determines how governments regulate AI development, protect intellectual property, and set ethical boundaries on model usage.

Countries that have excelled in any of these pillars have a head start. The US has long been a leader in compute, hosting major chip manufacturers and cloud infrastructure giants. China is similarly advanced, although unique legal frameworks allow it to mobilize private-sector resources at scale.

Nations in the Middle East hold a comparative advantage in energy — ample reserves and low-cost power that could transform their economies into AI super-hubs if strategically paired with strong data-center construction and top research talent.

Meanwhile, regions like Europe are pushing forward on policy, trying to articulate a coherent approach to regulating AI models while safeguarding innovation.

For most nations, it is impractical to dominate all four pillars single handedly. At least in the near term, sovereignty does not require building everything in-house. Instead, the goal is to avoid dependence on unreliable or misaligned partners for any critical element of AI infrastructure.

Where a country lacks robust data center facilities, it might ally with a corporate cloud provider or a friendly state that can host compute capacity. Where local energy costs are high, a government might incentivize green power initiatives or forge international agreements to secure long-term energy contracts, thus creating an environment to attract AI labs and startups. The critical question is whether a nation can trust these alliances to remain stable and beneficial over time, particularly if geopolitical winds shift.

AI truly is a new dimension of geopolitics; therefore, each country can align its strengths toward building a robust AI ecosystem.

Mohammed A. Al-Qarni 

Leaders making these calculations should pay attention to several key indicators. First, watch where high-end computing hardware is flowing. Early chip orders and multi-year contracts for GPUs, tensor processing units, or specialized accelerators often signal a commitment to becoming an AI “hypercenter.”

Second, look for data-center investments and energy infrastructure expansions; both strong predictors of a nation’s ambition to host large-scale AI projects. Third, monitor research ecosystems: Are universities expanding AI curricula, are local tech firms partnering with global AI players, and is there a surge in AI talent visas or exchange programs?

Finally, observe the regulatory front. A patchwork of conflicting rules deters AI innovators and pushes them elsewhere, so any coherent federal-level framework is a sign a government wants to compete effectively.

Practically, policymakers can prepare in a few ways. They can provide clarity on data usage, ensuring local researchers have access to large, high-quality datasets while respecting privacy and ethical considerations.

They can incentivize the private sector to build and operate advanced data centers domestically, particularly if cheap energy is abundant. They might form strategic alliances, bilateral or regional treaties to pool resources and share the burden of significant infrastructure costs. And crucially, they can invest heavily in AI education and training, cultivating a workforce capable of building and maintaining sophisticated systems.

These efforts foster self-sufficiency and signal to international partners that a nation is a credible, capable ally in collaborative ventures.

Those who underestimate AI’s geopolitical significance may be left scrambling for relevance as alliances solidify around the countries and corporations that control the fundamentals. For instance, missing the chance to secure a pipeline of GPUs can mean lagging years behind in frontier AI research.

Failing to craft a coherent data policy could deter innovators, while moral and cultural values are shaped elsewhere. And overlooking the crucial role of energy means watching from the sidelines as other regions with the right mix of power, computing, and policy surge ahead.

This may sound daunting, but it also represents an unprecedented opportunity. AI truly is a new dimension of geopolitics; therefore, each country can align its strengths — abundant energy, a tradition of technical expertise, or a highly skilled workforce — toward building a robust AI ecosystem.

The path need not be isolationist; international partnerships and private-sector collaboration can fill gaps in a nation’s strategy, provided mutual trust and a well-defined division of responsibilities exist.

What matters is that leaders recognize the shift now, weigh their options, and act before the global map of AI power becomes locked in place. In the near term, sovereignty is about ensuring you have choices rather than being at the mercy of those who took the AI revolution seriously first.

• Mohammed A. Al-Qarni is an academic and consultant on AI for business.