Over the past few years, countries across the Middle East and North Africa have moved rapidly to position themselves within the global artificial intelligence landscape. National AI strategies were drafted, visions were articulated, and ambitions were set. Yet in 2026, a more significant transition is taking place, one that signals a shift from aspiration to action. The region is entering a new phase where the focus is no longer on defining AI ambitions, but on governing, implementing, and operationalizing them.
This transition is evident in countries like Egypt, which recently published a comprehensive National AI Governance Framework in 2026 alongside its updated AI Strategy for 2025–2030. These efforts go beyond vision-setting to address ethical oversight, data governance, and institutional responsibility, even exploring the development of a national AI foundation model. Similarly, the United Arab Emirates has long positioned itself as a regional leader through its AI Strategy 2031, embedding AI across government services while investing heavily in talent development. Saudi Arabia has followed a comparable path through its National Strategy for Data and AI, supported by dedicated institutions such as the Saudi Data and AI Authority, aiming to transform public services and strengthen national data infrastructure.
Across the region, other countries are advancing at varying speeds. Oman has introduced a public policy framework for the safe and ethical use of AI, complemented by updated data protection regulations. Countries such as Qatar, Jordan, and Kuwait have embedded AI within broader national visions, while others, including Morocco, still lack a dedicated AI strategy, reflecting an uneven regional landscape. In many cases, governance remains anchored in existing legal frameworks such as data protection laws and sector-specific regulations rather than AI-specific legislation.
This regional evolution mirrors a broader global shift. Internationally, AI governance has been shaped by foundational principles such as fairness, accountability, transparency, and human oversight. Frameworks developed by organizations like the OECD and UNESCO have established widely accepted ethical baselines, while more operational models, such as the AI Risk Management Framework by the National Institute of Standards and Technology, have translated these principles into actionable processes. Increasingly, countries are moving beyond principles toward implementation, introducing regulatory sandboxes, national AI systems, and mechanisms for auditing and accountability.
Within this context, MENA’s progress is notable, but it also reveals a critical gap. Governance frameworks are being established, yet their translation into real-world impact remains uneven. The challenge is no longer the absence of strategy or policy, but the capacity to implement them effectively.
This gap becomes particularly visible when examining AI adoption across industries. While approximately 60% of firms in the Middle East are experimenting with AI, only between 14 and 28 percent have successfully scaled these technologies across their operations. The financial sector leads adoption, with nearly 90% of Gulf CEOs reporting the use of generative AI in 2024, and projections suggesting that AI could contribute up to 13.6% of GDP in banking alone by 2030. Energy, construction, and manufacturing sectors also show strong investment, collectively accounting for a significant share of AI deployment in the region.
However, this momentum is not evenly distributed. Sectors such as agriculture, small and medium-sized enterprises, and traditional retail remain significantly behind. This imbalance raises an important structural question: are current governance efforts enabling broad-based adoption, or are they primarily reinforcing AI use in already advanced sectors? The economic implications are substantial, particularly given projections that AI could add approximately $320 billion to the MENA economy by 2030. Without inclusive adoption, these gains risk being unevenly distributed.
Underlying this disparity is a deeper issue of capacity. AI governance does not operate in isolation; it requires an ecosystem of actors who are equipped to understand, implement, and regulate these technologies. Governments across the region have begun addressing this through a range of capacity-building initiatives. Programs targeting policymakers and regulators have expanded, including regional trainings organized by international organizations and industry actors. For example, initiatives led by UNDP and GSMA have trained policymakers on AI governance and ethics, while programs such as Google’s MENA Regulator Academy have brought together regulators from across the region to address issues of cloud security, AI ethics, and policy innovation.
At the same time, broader workforce development efforts are underway. Initiatives like Google’s AI Opportunity Initiative aim to train hundreds of thousands of individuals across MENA by 2027, with a particular focus on underserved communities. Programs led by organizations such as Village Capital are targeting women, youth, and rural populations, while educational initiatives are introducing AI concepts at earlier stages through localized curricula and teacher training. Universities and think tanks are also contributing by facilitating discussions on workforce transformation and reskilling.
Despite these efforts, significant gaps remain. Capacity-building initiatives tend to concentrate on senior policymakers and early-career learners, often overlooking mid-career professionals, SME leaders, and vocational sectors. At the same time, disparities in digital infrastructure and skills persist across countries. For instance, while digital proficiency rates are relatively high in some Gulf countries, they remain significantly lower in parts of North Africa, limiting the ability of certain economies to fully participate in the AI transition.
These differences are reflected in emerging rankings of AI governance maturity across the region. Recent comparative analyses categorize MENA countries into distinct tiers based on governance frameworks, institutional capacity, and implementation progress. Leading countries such as the UAE and Saudi Arabia rank at the top, supported by strong institutional structures, advanced infrastructure, and clear national projects. Countries like Qatar, Oman, and Egypt follow closely, demonstrating significant progress but still facing challenges in scaling implementation. Others, including Jordan and Kuwait, are considered emerging, while several countries remain at early stages of development due to limited institutional capacity or ongoing structural challenges.
Globally, similar patterns are observed, but leading countries are increasingly distinguished by their ability to operationalize governance. The emphasis is shifting toward risk management, auditing mechanisms, and enforceable standards. In this regard, MENA stands at a critical juncture. The region has made substantial progress in defining AI strategies and establishing governance frameworks, but the next phase will depend on its ability to translate these into practice.
Ultimately, the future of AI in the region will not be determined by the ambition of its strategies, but by the strength of its implementation. This requires not only regulatory frameworks, but also sustained investment in human capital, institutional capacity, and cross-sector adoption. The transition from strategy to execution is already underway. The question that remains is whether the region can build the capabilities needed to make AI governance truly effective.