The Arab region is a reactive recipient, not an AI creator: a multi-country field study of leaders finds limited governance capacity and urges a strategic, inclusive policy roadmap across seven pillars to enable safe adoption and public-sector transformation.

Charting AI Governance Future in the Arab Region: A Policy Roadmap

Akmaral Orazaly, Fadi Salem · Fetched March 26, 2026 · Social Science Research Network

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The Arab region currently lacks sufficient AI governance capacity and needs a coordinated, multi-pillar policy roadmap — informed by stakeholder consultations across ten countries — to build strategic, responsible, and inclusive AI governance that supports public sector modernization and economic development.

The Arab region’s capacity for Artificial Intelligence (AI) governance remains limited relative to the accelerating pace of global AI developments and associated challenges. This gap hinders the ability of many governments in the region to push their countries toward joining the ranks of those benefiting from the AI revolution—both in developing the public sector and supporting economic growth and social development. Currently, the region remains reactive as a “recipient” rather than a “creator” or an effective partner. This reality calls for a series of policy interventions at both local and regional levels to empower the AI ecosystem in the Arab region. What are the policy directions that Arab governments can adopt to build an AI governance framework that is strategic, responsible, and inclusive? This executive report provides a roadmap for establishing an AI governance infrastructure through a set of strategic policy recommendations across seven key pillars. These recommendations are based on regional research that included hundreds of leaders active in the AI domains, from the public and private sectors. This report highlights the key findings of a field study covering ten Arab countries to explore the realities and challenges of AI governance. The study was conducted by the Mohammed bin Rashid School of Government’s Future of Government Center, in collaboration with global AI pioneers. The results of this regional research outline a multi-dimensional policy roadmap that dives deep into the region’s current capabilities and the hurdles it faces in catching up with the AI revolution from a governance and policy perspective, presenting them in a practical framework for public sector leaders.

Summary

Main Finding

The Arab region currently lags in AI governance capacity and is primarily a reactive “recipient” of AI developments rather than a creator or strategic partner. To capture the economic and public-sector benefits of AI—and to mitigate associated risks—governments must adopt a coordinated, multi-dimensional governance framework across seven strategic pillars that build institutional capacity, enable responsible innovation, and ensure inclusive outcomes.

Key Points

Regional diagnosis: limited institutional capacity, fragmented initiatives, skills shortages, uneven data infrastructure, and low regulatory readiness impede the region’s ability to harness AI for growth and public-service transformation.
Current stance: most countries act reactively, adopting external tools and standards rather than shaping AI development domestically or regionally.
Purpose of the report: deliver a practical, policy-oriented roadmap based on regional research involving hundreds of public- and private-sector AI leaders across ten Arab countries.
Seven policy pillars (summary): national governance structures; regulatory and legal frameworks; data governance & infrastructure; talent & education; public-sector adoption & procurement; innovation ecosystems & private-sector engagement; ethics, inclusion & regional coordination.
Cross-cutting needs: clearer mandates, funding mechanisms, coordinated regional action, public–private partnerships, and capacity-building tailored to local contexts.

Data & Methods

Coverage: field study spanning 10 Arab countries, led by the Mohammed bin Rashid School of Government’s Future of Government Center in collaboration with global AI experts.
Participants: input from “hundreds” of leaders active in AI across government, private sector, and civil society.
Methods (mixed): stakeholder interviews, expert workshops, surveys of practitioners and policymakers, policy and institutional reviews, and synthesis of regional case examples and global best practices.
Outputs: multi-dimensional policy recommendations structured into seven pillars, with practical steps for public-sector leaders.
Limitations: findings reflect the participating countries and stakeholders; qualitative elements and self-reported assessments mean some recommendations require local piloting and further quantitative validation.

Implications for AI Economics

Growth & productivity: stronger AI governance can accelerate public-sector efficiency and catalyze private-sector innovation, increasing productivity and GDP contributions from AI-enabled services and industries.
Investment climate: clear, predictable governance and data rules reduce policy risk, attracting domestic and foreign investment into AI R&D, startups, and scale-ups.
Human capital & labor markets: sustained investments in education, reskilling, and upskilling will determine whether AI augments the workforce or accelerates disruptive displacement—with major distributional consequences if not managed.
Data as economic asset: harmonized data governance and interoperable infrastructure unlock data-driven value chains (health, finance, logistics) while balancing privacy and trust—critical for monetization and public-service use.
Innovation ecosystems: targeted incentives, procurement reform, and regional collaboration can expand market size, support SMEs, and integrate Arab actors into global AI value chains.
Inclusion & distributional risks: governance that foregrounds inclusion can mitigate risks of unequal gains across countries, genders, and socio-economic groups; without it, AI could worsen existing inequalities.
Regional coordination multiplier: pooling regulatory frameworks, shared infrastructure, and joint capacity-building reduces duplication, raises bargaining power in global standards debates, and lowers costs for smaller states.

Recommended short policy agenda (mapped to the seven pillars) 1. Governance & strategy: establish national AI bodies with clear mandates, cross-ministerial coordination, national AI strategies aligned to economic and social priorities. 2. Regulation & law: adopt risk-based, technology-neutral regulation for safety, accountability, and liability; enable regulatory sandboxes for experimentation. 3. Data governance & infrastructure: create interoperable data platforms, common standards, and lawful data-sharing mechanisms with privacy safeguards. 4. Talent & education: scale STEM and AI curricula, vocational reskilling programs, and incentives to retain skilled talent regionally. 5. Public-sector adoption & procurement: reform procurement to favor responsible AI suppliers, pilot high-impact use cases, and build internal civil-service capacity. 6. Innovation & private sector support: use grants, tax incentives, incubators, and public–private partnerships to grow startups and R&D. 7. Ethics, inclusion & regional cooperation: adopt ethical AI guidelines, inclusivity metrics, and regional coordination mechanisms for standards, talent mobility, and cross-border projects.

Overall recommendation: move from ad hoc responses to a strategic, phased program that combines capacity-building, regulatory clarity, and regional collaboration to transform the Arab region from a passive recipient into an active participant and creator in the AI-driven economy.

Assessment

Paper Typedescriptive Evidence Strengthmedium — The report is based on a multi-country field study and consultations with hundreds of AI leaders and stakeholders, providing rich qualitative evidence about governance capacity and needs; however, it lacks systematic quantitative measurement, causal identification, and representative sampling, limiting its ability to support strong empirical claims about economic effects. Methods Rigormedium — Methods appear to rely on expert interviews, workshops, and qualitative field work across ten countries which supports depth and contextual insight, but the report does not document a transparent sampling frame, standardized instruments, or rigorous comparative empirical tests, leaving room for selection bias and inconsistent coverage across countries. SampleA regional field study conducted by the Mohammed bin Rashid School of Government’s Future of Government Center in collaboration with global AI organizations, covering ten Arab countries and involving 'hundreds' of leaders and practitioners from public and private sectors (policy makers, government officials, industry leaders, and AI experts); primarily qualitative data from interviews, workshops, and stakeholder consultations rather than population-representative surveys or administrative/transactional datasets. Themesgovernance adoption skills_training org_design GeneralizabilityFindings are specific to the Arab region and may not generalize to non-Arab countries with different institutional, economic, or legal contexts., Sample is composed mainly of leaders and experts (public/private sector), so perspectives of frontline workers, SMEs, or marginalized groups may be underrepresented., Report covers ten countries but likely masks substantial intra-regional heterogeneity in capacity and governance arrangements., Qualitative, time-bound assessment may become outdated quickly given rapid AI developments., Absence of representative quantitative data limits generalization to national-level prevalence or causal claims about economic outcomes.

Claims (9)

Claim	Direction	Confidence	Outcome	Details
The Arab region’s capacity for Artificial Intelligence (AI) governance remains limited relative to the accelerating pace of global AI developments and associated challenges. Governance And Regulation	negative	high	AI governance capacity	0.18
This gap hinders the ability of many governments in the region to push their countries toward joining the ranks of those benefiting from the AI revolution—both in developing the public sector and supporting economic growth and social development. Governance And Regulation	negative	high	governments' ability to benefit from AI (public sector development; economic and social development)	0.18
Currently, the region remains reactive as a 'recipient' rather than a 'creator' or an effective partner in the AI ecosystem. Innovation Output	negative	high	degree of domestic AI creation/innovation versus reception/adoption	0.18
The reality of limited AI governance capacity calls for a series of policy interventions at both local and regional levels to empower the AI ecosystem in the Arab region. Governance And Regulation	positive	high	adoption of policy interventions to strengthen AI governance and ecosystem	0.03
This executive report provides a roadmap for establishing an AI governance infrastructure through a set of strategic policy recommendations across seven key pillars. Governance And Regulation	positive	high	existence of a multi-pillar policy roadmap in the report	0.3
The recommendations are based on regional research that included hundreds of leaders active in the AI domains, from the public and private sectors. Governance And Regulation	null_result	high	scope and participant coverage of the underlying research	0.18
The report highlights the key findings of a field study covering ten Arab countries to explore the realities and challenges of AI governance. Governance And Regulation	null_result	high	geographic coverage of the field study (number of countries)	n=10 0.3
The study was conducted by the Mohammed bin Rashid School of Government’s Future of Government Center, in collaboration with global AI pioneers. Governance And Regulation	null_result	high	institutional authorship and collaboration on the study	0.3
The results of this regional research outline a multi-dimensional policy roadmap that dives deep into the region’s current capabilities and the hurdles it faces in catching up with the AI revolution from a governance and policy perspective, presenting them in a practical framework for public sector leaders. Governance And Regulation	positive	high	comprehensiveness and practicality of the policy roadmap produced by the study	0.18