How the UAE is building AI leaders beyond traditional education
Unlike standard AI programmes focused primarily on technical instruction, NEP-AI is structured around Emirati professionals already operating within priority sectors across the UAE economy, says Eman Al Mughairy, expert at the National Experts Program in the Culture and Identity sector
18 May, 2026
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As the UAE accelerates its push to become a global artificial intelligence hub, the focus is increasingly shifting from infrastructure and investment to talent capability. While universities and training programmes continue to expand AI education, the country is also experimenting with a different model — one built around execution, institutional impact, and sector integration.
For Eman Al Mughairy, expert at the National Experts Program in the Culture and Identity sector and head of Outreach at Mohamed bin Zayed University of Artificial Intelligence, the UAE’s National Experts Program AI track (NEP-AI) represents a deliberate departure from conventional learning pathways.
“What makes NEP-AI different is simple: it doesn’t behave like a traditional programme,” she says. “Most education pathways are designed to transfer knowledge. NEP-AI is designed to shape perspective and create impact.”
Moving beyond traditional AI education
Unlike standard AI programmes focused primarily on technical instruction, NEP-AI is structured around Emirati professionals already operating within priority sectors across the UAE economy.
“NEP-AI is designed for Emirati professionals already embedded across priority sectors,” Al Mughairy explains. “This means AI is applied within real institutional contexts, shaped by sector-specific knowledge and national priorities.”
The programme’s positioning at mid- to senior-management level is intentional. By targeting professionals already involved in decision-making environments, AI capability is integrated directly into institutions where policy, strategy, and operational execution intersect.
“It also operates at a different level of seniority,” she says. “Participants are mid- to senior-level professionals, which ensures that capability is integrated directly into the environments where policies are shaped and decisions are made.”
This approach reflects the UAE’s broader strategy of embedding AI across government, industry, and public services, rather than treating it as a standalone technology sector.
Beyond individual capability-building, Al Mughairy sees the programme as part of a larger national objective: strengthening technological sovereignty and long-term resilience.
“By distributing expertise across sectors, it strengthens a national backbone of AI capability,” she says.
The emphasis is not simply on technical literacy, but on creating leaders who can translate AI into institutional outcomes aligned with national priorities. Most significantly, programme success is measured not by academic achievement but by implementation.
“Success is not measured by what participants know, but by what they deliver,” Al Mughairy says.
This execution-focused approach is reinforced through capstone projects, where participants work on real-world sector challenges under structured mentorship. “Every stage of learning is tied to execution, addressing real challenges and translating AI from concept into institutional application.”
Selecting future AI leaders
The programme’s rigorous selection process reflects its strategic ambition.
“NEP-AI looks for Emirati professionals who are already operating within sectors where AI matters,” Al Mughairy says.
Technical skills remain important, but the programme evaluates a much broader set of capabilities — including decision-making, systems thinking, and the ability to connect AI to policy and societal outcomes.
“There is also a strong focus on responsibility,” she explains. “Candidates are expected to demonstrate how AI impacts institutions, policy, and society, not just systems.”
The process itself combines technical assessments, AI-based interviews, and in-person evaluation by a multidisciplinary panel. At each stage, the central question remains consistent.
“Can this individual translate AI into meaningful, real-world outcomes?” Al Mughairy asks.
NEP-AI’s eight-month structure is designed as a progression from technical understanding to applied delivery.
“It begins by establishing a strong technical foundation,” Al Mughairy says. “Participants develop a clear, practical understanding of how AI systems work, including infrastructure, data, and deployment realities.”
From there, the focus shifts toward value creation and implementation strategy. Participants are expected to identify sector-specific AI opportunities, assess feasibility, and understand the economics of deployment.
“As the programme advances, the emphasis moves to strategy and leadership,” she explains.
International study visits also form a core component of the experience, exposing participants to global AI ecosystems, governance frameworks, and operational models.
“These are structured engagements with leading AI ecosystems, focused on applied models, governance approaches, and implementation at scale.”
Throughout the programme, capstone projects run in parallel, ensuring that learning remains directly connected to real institutional problems.
“By the end of the programme, the expectation is that participants can apply AI in ways that are relevant, responsible, and aligned with national priorities.”
One of the programme’s defining characteristics is its sector-based structure. “Participants are selected from across 25 priority sectors,” Al Mughairy says. This creates a model where participants gain deep expertise within their own fields while simultaneously developing visibility into AI applications across multiple industries.
“Depth comes from the participant’s own sector. Breadth comes from the programme.” The result is a cohort capable not only of driving AI within their own institutions, but also understanding how AI capability connects across the broader national ecosystem. “That combination ensures participants do not operate in isolation,” she says.
Why global collaboration matters
For Al Mughairy, international exposure is not an optional enhancement — it is essential.
“AI is not a local industry. It’s a global system where convergence matters — technically, economically, and politically,” she says.
This perspective shapes NEP-AI’s approach to partnerships and study visits, which are designed to expose participants to how other nations deploy, govern, and regulate AI at scale.
“Participants are exposed to how other countries deploy AI, how institutions manage risk, and how systems are built and governed in practice.” This global benchmarking process serves two purposes: aligning participants with international standards while strengthening their ability to adapt those insights to the UAE context.
“Global collaboration… challenges assumptions and expands what they consider possible.”
The programme’s capstone projects are positioned as the clearest demonstration of its execution-led philosophy.
“Capstone Projects are where the programme makes a difference,” Al Mughairy says.
Each participant develops an AI initiative tied to a real sector challenge, with a focus on measurable outcomes and implementation viability.
“These are not academic exercises; they are designed to be practical, measurable, and aligned with institutional needs.” Participants must not only design solutions, but also present operational models and deployment strategies to senior stakeholders. “This is what shifts the programme from learning to delivery.”
For the UAE, AI capability-building is increasingly tied to economic diversification and long-term competitiveness.
“NEP-AI contributes by embedding capability across the system,” Al Mughairy says.
She points to the growing importance of technology convergence, where competitive advantage increasingly depends on the ability to combine and scale multiple technologies effectively.
“An AI-enabled economy is not built by engineers alone, but by people who can translate, align, and activate across systems.”
This is where NEP-AI positions itself differently — not only developing technical experts, but also connectors capable of bridging policy, technology, and execution.
“The programme also connects multiple layers — government, industry, academia, and international partners — through applied learning and project delivery.”
Defining success for the UAE AI model
Ultimately, Al Mughairy believes the UAE’s success in AI capability-building will not be measured by announcements or investment totals, but by practical deployment.
“Success will be reflected in how AI is used, not how it is described,” she says.
For her, the UAE’s differentiator lies in alignment — where education, leadership development, research, and implementation operate within a coordinated national framework.
“What stands out in the UAE is alignment,” she explains. “There is a clear national direction, supported by education, leadership development, research, and sector deployment — all working toward the same objective.”
Within that system, NEP-AI serves a highly specific role: translating strategy into institutional execution through people.
“It focuses on people, and on building the capability required to translate strategy into execution.”
As countries globally race to build AI ecosystems, the UAE’s model suggests that long-term competitiveness may depend less on isolated technical expertise and more on the ability to integrate AI capability directly into the structures where decisions are made.
