AI and Higher Education in MENA: A Region Diverging, Not Simply Catching Up

Across the Middle East and North Africa (MENA), artificial intelligence (AI) has become a fixture of national development rhetoric, and higher education is routinely cast as the sector that must “catch up” if the region is to benefit from, rather than be displaced by, the technology. Yet this framing obscures more than it reveals. The more accurate and more consequential story is not a single regional race against a global clock, but a widening internal divergence: a small number of well-capitalised Gulf states are building dedicated AI universities and national talent pipelines at striking speed, while most public university systems across North Africa and the Levant still lack even a basic digital transformation strategy. This matters because higher education is the institutional layer through which AI-related economic gains, labour-market disruption, and governance capacity are mediated. If the gap between AI-intensive and AI-marginal university systems widens, the result will not simply be slower regional progress — it will be a more unequal MENA, in which a handful of states absorb AI’s productivity dividend while others absorb its labour-market disruption without the institutional means to respond. Whether MENA universities can “catch up” is therefore the wrong question for most of the region; the right question is whether divergence can be managed, and on what terms.

Two Decades of Uneven Digital Foundations

MENA’s encounter with AI in higher education did not begin in a vacuum. The region’s digital learning infrastructure remained underdeveloped well into the 2020s. A joint study by the UNESCO International Centre for Higher Education Innovation (UNESCO-ICHEI) and the Arab League Educational, Cultural, and Scientific Organisation (ALECSO), covering ten countries including Egypt, Jordan, Morocco, Tunisia, and the United Arab Emirates (UAE), found that as of December 2023 only four of the ten — Jordan, Morocco, Algeria, and Mauritania — had a clear national strategy for higher education digitalisation, and most lacked any dedicated regulatory framework for digital learning (UNESCO-ICHEI & ALECSO, 2024). In other words, the foundational digital governance that AI integration depends on was, until very recently, the exception rather than the norm.

Against this backdrop, a small set of Gulf states has pursued a markedly different trajectory. The UAE launched its National Strategy for Artificial Intelligence 2031 and, as part of it, founded the Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) in Abu Dhabi — the world’s first university dedicated entirely to AI, offering fully funded graduate programmes since 2021 and an undergraduate degree since 2025 (Wikipedia, 2026; MBZUAI, 2026). Saudi Arabia’s Saudi Data and Artificial Intelligence Authority (SDAIA) has pursued a parallel path through its National Strategy for Data and AI (NSDAI), launched in 2020, which explicitly identifies education as one of its priority sectors and has financed large-scale upskilling programmes, including one that had certified roughly 1.1 million Saudi citizens by the end of 2025 (Saudipedia, 2024; Riyadh Web3, 2026). Universities such as the King Abdullah University of Science and Technology (KAUST) and King Fahd University of Petroleum and Minerals have built dedicated AI faculties and bootcamp partnerships with international technology firms (Arab News, 2024).

This is not simply a story of money chasing prestige. The World Bank’s regional human development analysis finds that MENA’s exposure to AI-driven labour-market change is comparatively high — higher, on some measures, than Latin America, South Asia, and parts of Europe and Central Asia — driven by a young population, ambitious digital strategies, and substantial public investment in digital infrastructure (World Bank, 2025). The stakes of how universities respond are therefore real. But exposure to AI-driven change and capacity to respond to it are distributed very unevenly across the region.

Governance and Institutional Strategy: A Two-Tier System Taking Shape

The clearest analytical pattern to emerge is institutional bifurcation rather than uniform catch-up. A handful of flagship, state-backed AI universities — MBZUAI, KAUST, and a small number of comparable institutions — now operate at a level of resourcing and international competitiveness that did not exist in the region a decade ago. Meanwhile, the majority of public universities across Egypt, Tunisia, Jordan, Algeria, and elsewhere continue to operate without an institutional AI strategy, without a quality-assurance framework for AI-related credentials, and in many cases without reliable digital infrastructure at all (UNESCO-ICHEI & ALECSO, 2024). This is not a temporary lag that will close through diffusion; it reflects different starting points in public finance, governance capacity, and political stability.

This bifurcation has a governance dimension that extends beyond resourcing. A 2024 analysis in the journal Data & Policy found that AI governance efforts across MENA fall well short of the scale of the challenge, with national AI strategies still heavily concentrated among a minority of states, and most governments in the region investing little in the underlying data governance and human-capital infrastructure that AI policy depends on (Cambridge Data & Policy, 2024). For universities, this matters because institutional AI strategy cannot be separated from national data governance, accreditation reform, and regulatory clarity — areas where capacity is thin outside the Gulf. The interpretive question this raises is whether the flagship-institution model is a viable template for the rest of the region, or whether it is so specific to Gulf fiscal capacity and state-led development models that it offers limited transferable lessons.

Funding and Sustainability: A Capital Intensity Problem

AI education at the frontier is capital-intensive in ways that distinguish it from earlier waves of higher education reform, such as expanding access or introducing e-learning. It requires computing infrastructure, competitive faculty salaries in a globally scarce labour market, and sustained R&D funding. Saudi Arabia’s NSDAI carries an estimated allocation in the tens of billions of dollars, and the broader Saudi AI ecosystem — including the Public Investment Fund’s AI venture HUMAIN — involves commitments reported in the order of $100 billion (Riyadh Web3, 2026). The UAE, similarly, is host to large-scale infrastructure projects involving international partners such as OpenAI, Oracle, and Nvidia (Forbes, 2025).

These figures are simply unreplicable for most MENA economies. Tunisia, Jordan, and Egypt operate under far tighter fiscal constraints, and their higher education systems compete for resources against more immediate social priorities. The practical implication is that for most of the region, “catching up” through direct emulation of the Gulf model is not a realistic policy option. Instead, the more relevant trade-off is between two more modest paths: integrating AI literacy into existing curricula at relatively low cost, or pursuing regional cooperation mechanisms — such as the joint UNESCO-ICHEI/ALECSO research initiative or the newly launched UN Development Programme (UNDP) digital transformation hub for Arab and African states — that pool scarce expertise rather than duplicating it nationally (UNDP, 2026). Whether such cooperative mechanisms can substitute for national capital investment remains, at this stage, an open and largely untested question.

Talent, Brain Drain, and the Limits of Capital

A further complication is that money, while necessary, has not been sufficient to resolve the region’s AI talent constraints — even in the best-resourced states. Despite extensive investment, the UAE is estimated to hold roughly 0.7% of global AI talent (ranked 16th worldwide) and Saudi Arabia approximately 0.4% (ranked 19th), with both countries reporting persistent difficulty recruiting senior AI researchers despite compensation packages that can exceed $1 million (TechRound, 2026). SDAIA’s own assessment reportedly identifies a gap of 10,000 to 15,000 qualified AI practitioners between current supply and projected 2030 demand (Riyadh Web3, 2026). MBZUAI’s response has been to recruit more than 100 faculty members from China, the United States, Germany, and elsewhere (Rest of World, 2025) — an approach that builds research capacity quickly but also means the flagship model currently depends heavily on imported expertise rather than organically grown academic talent.

For the rest of the region, the talent picture is more precarious still. The World Bank’s 2021 World Development Report estimated that MENA loses approximately 10,000 skilled information and communication technology (ICT) professionals annually to emigration (World Bank, 2021), a pattern widely attributed to governance instability, limited research funding, and constrained career prospects in countries such as Lebanon, Egypt, and Tunisia. This is a genuine structural tension: the very conditions that make domestic AI capacity-building urgent in non-Gulf states — weak institutions, fiscal constraint, political instability — are the same conditions driving the emigration of the people such states would need to retain in order to build that capacity. It is worth noting explicitly that some of the talent-ranking and gap figures cited above derive from industry analyses and journalistic reporting rather than peer-reviewed sources, and should be read as indicative rather than precise.

Equity, Labour Markets, and the Risk of a Two-Speed Region

The labour-market case for AI-literate graduates is reasonably well evidenced, even if its scale is difficult to quantify precisely. Surveys cited by the World Bank suggest that close to 70% of regional chief executives view shortages of digital skills as a major business risk, even as the delivery of education and training across the region has changed little to meet that demand (World Bank, 2025). UNESCO’s 2024 AI competency frameworks for students and teachers were designed precisely to help national systems align curricula with this demand (UNESCO, 2024), but adoption depends on the same institutional capacity that is unevenly distributed across MENA.

The equity implications are significant. Where flagship AI universities exist, they tend to serve a small, highly selected cohort — MBZUAI, for instance, enrols several hundred students from dozens of countries (Forbes, 2025) — while AI literacy for the broader student population, including in mainstream public universities, lags considerably. This raises a legitimate distributional question that is sometimes underexamined in enthusiastic accounts of Gulf AI investment: even within wealthy states, is AI higher education capacity being built in a way that broadens opportunity, or does it risk concentrating advantage among a narrow elite while the majority of graduates remain unprepared for an AI-altered labour market? The evidence here is genuinely mixed and contested; Saudi Arabia’s large-scale upskilling programmes, with reported female participation above 50%, suggest a deliberate effort toward broader access (Riyadh Web3, 2026), but comparable mass upskilling infrastructure is largely absent outside the wealthiest states.

Divergence, Not a Single Race

The question of whether MENA universities can catch up on AI education before “it’s too late” presumes a single regional trajectory and a fixed finish line. Neither assumption holds. What is emerging instead is a bifurcated higher education landscape: a small number of state-backed institutions in the Gulf operating at, or near, global research frontiers, built substantially on imported faculty and capital-intensive infrastructure; and a much larger set of university systems across North Africa and the Levant still establishing the basic digital governance frameworks that AI integration presupposes. For the latter group, the realistic policy question is not how to replicate the Gulf model, but how to use limited resources to build AI literacy at scale, strengthen regional cooperation mechanisms, and mitigate the labour-market disruption that AI may bring even in the absence of frontier research capacity.

Several developments will be worth monitoring closely. First, whether Gulf-funded scholarship and training pipelines — many of which recruit internationally — begin to generate meaningful capacity spillovers into non-Gulf MENA systems, or whether they instead intensify intra-regional brain drain. Second, whether regional and multilateral initiatives, such as the UNDP’s newly announced digital transformation hub, can function as genuine capacity-pooling mechanisms rather than symbolic gestures. Third, whether quality-assurance and accreditation bodies across the region develop shared standards for AI-related credentials, which would help prevent a proliferation of low-quality AI programmes responding to market hype rather than labour-market need. The evidence base for several of these questions remains thin, and claims about specific talent gaps or programme outcomes should be treated with appropriate caution pending more rigorous, independently verified data. What can be said with more confidence is that the region’s AI higher education story will be defined less by whether it “catches up” globally than by whether it manages to narrow, rather than entrench, the gap between its own most and least AI-ready university systems.

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• UNESCO International Centre for Higher Education Innovation (UNESCO-ICHEI) & Arab League Educational, Cultural, and Scientific Organisation (ALECSO). (2024). Regional Insights into Higher Education Digitalisation: Collaborative Exploration in the Arab Region.
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• Wikipedia. (2026). Mohamed bin Zayed University of Artificial Intelligence. [Used for institutional/biographical detail only; verify against primary MBZUAI sources for any formal citation.]