How the UAE Is Building a Different Model of AI Power

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It may seem that the competition in AI is primarily between the US and China. But while companies in those two countries are leading the way in cutting-edge research and products, the UAE has taken a different approach. The country views AI as more than just a commercial technology; it is positioning the tech as a vital component of national infrastructure. 

The country’s rapid emergence as a serious contributor to global AI development is not accidental, says Dr. Hakim Hacid, Chief Researcher of the Artificial Intelligence and Digital Science Research Center at Technology Innovation Institute (TII). It is the result of “deliberate long-term planning,” anchored in early investments in research capacity, talent attraction, and governance frameworks designed to move in parallel rather than in silos.

He says, “The UAE’s approach stands out along three axes: license design, sovereign agenda, and partnerships.”

The UAE was among the first nations to elevate AI to a ministerial priority, launching its National Strategy for Artificial Intelligence in 2017 and appointing a dedicated Minister of AI. Since then, the policy architecture has steadily expanded: the UAE Council for Artificial Intelligence coordinates federal and emirate-level efforts; the AI Strategy 2031 sets clear objectives in leadership, infrastructure, and regulation; and Abu Dhabi’s AI and Advanced Technology Council (AIATC) aligns research, deployment, and compute investments. Most recently, the National AI Charter has added a layer of governance focused on transparency, safety, and accountability.

Together, these institutions form what Hacid describes as a “whole-of-government approach” to AI—one that treats research, regulation, and deployment as mutually reinforcing rather than sequential.

Open Source as Sovereign Strategy

The point at which the UAE differs from other AI leaders is in its approach to openness. While many governments rely on proprietary systems built elsewhere, the UAE has placed open-source development at the center of its sovereign AI agenda.

TII’s Falcon family of large language models exemplifies this strategy. Released under permissive, royalty-free licenses, Falcon models were designed to remove barriers to adoption across borders and sectors. Since 2023, Falcon has stood out not only as the Middle East’s first home-grown large language model with openly available weights, but also as a competitive global benchmark performer.

For Hacid, openness is defined strategically. “Openness is tied to a sovereign capability strategy,” he explains, ensuring that governments, institutions, and companies can deploy AI securely and independently, without surrendering control over data or infrastructure. Crucially, the UAE pairs this openness with global partnerships across compute, research, and industry, creating what Hacid calls “a distinct and scalable model for open AI ecosystems.”

The sequencing of open access, sovereign control, and international collaboration positions the UAE as neither fully aligned with Silicon Valley’s platform dominance nor with more closed, state-centric models.

Redefining Open Science

TII’s research agenda extends beyond national ambition. By releasing powerful open-source tools while maintaining governance safeguards, the institute is shaping global conversations about how open science and responsible AI can coexist.

“Open science can reinforce, not dilute, responsible innovation,” Hacid says. In an era where AI governance debates often frame transparency as a liability, TII’s work suggests the opposite: that accessible models enable broader scrutiny, facilitate faster risk identification, and promote technical improvement.

This approach is becoming increasingly relevant as international frameworks for AI governance emerge. Rather than treating safety as a function of secrecy, the UAE’s model emphasizes standards, monitoring, and shared responsibility—principles embedded in both the National AI Charter and the institutional design supporting AI research.

Governing Across Sectors

One of the UAE’s advantages lies in its governance structures for cross-sector collaboration. AI adoption does not occur in isolation, particularly in domains such as healthcare, energy, security, or public services. According to Hacid, effective governance must go beyond regulation to enable trust, data interoperability, and institutional alignment.

Bodies such as the AI Council and AIATC function not merely as oversight mechanisms, but as connective tissue between research institutes, government agencies, and private-sector deployment. This coordination is reinforced by sovereign infrastructure that allows sensitive sectors to innovate within trusted environments, rather than outsourcing critical capabilities.

“The UAE’s approach demonstrates that AI governance is not just about oversight,” Hacid argues, “but about building the institutional bridges that make ambitious, multi-sector innovation possible.”

Sovereignty Without Isolation

As AI capabilities continue to scale, nations worldwide are grappling with how to strike a balance between sovereignty and collaboration. The UAE’s answer rejects the idea that the two are mutually exclusive.

“Sovereign AI and federated collaboration are not opposing paths; they are converging imperatives,” Hacid says. While national control over data, infrastructure, and models is increasingly seen as essential, cross-border cooperation remains critical for shared safety standards, research progress, and compute scalability.

The UAE’s strategy reflects this hybrid reality: investing heavily in sovereign research institutions and foundational models like Falcon, while maintaining trusted international partnerships. This model, Hacid suggests, is likely to define the next phase of responsible innovation, one where national stewardship coexists with global alignment.

Rethinking Safety

Perhaps the most persistent assumption Hacid challenges is the belief that openness and safety are fundamentally at odds. “In practice, transparency often strengthens safety,” he says, by enabling global participation in testing, critique, and improvement.

As AI systems grow more powerful, the debate is likely to shift beyond whether models should be open or closed, and toward how openness itself is governed.

Responsible release practices, clear accountability, and investment in shared infrastructure, Hacid argues, will matter more than secrecy in determining whether AI advances serve the public good or private concentration.

By positioning itself as a builder of institutions rather than just technologies, the UAE is asserting that the future of AI leadership will belong not only to those who innovate rapidly but also to those who govern most effectively.