Refugees and Migrants Missing from the Table: Mapping AI Policy Gaps and Proposing an Inclusive Agenda in the Arab Region

August 5, 2025

Mennatullah Hendawy, Technical University of Munich, Germany; Center for Advanced Internet Studies, Germany

Introduction

As artificial intelligence (AI) becomes a central pillar of national development strategies across the globe, many Arab countries are embracing AI to advance economic growth, digital transformation, and public sector modernization. However, amid the region’s growing engagement with AI policy, refugees and migrants remain conspicuously absent from strategic planning. This omission not only reflects long-standing patterns of structural marginalization but also raises urgent questions about the inclusivity, credibility, and long-term resilience of AI governance in the region.

This article investigates the extent to which refugees and migrants are included—or excluded—in national AI strategies, with a particular focus on the Arab region. It asks: How do current AI policies account for mobile populations, especially in contexts marked by significant displacement and migration flows? And what might an inclusive AI agenda look like for countries in the Arab world?

To answer these questions, this study conducted a qualitative document analysis of 62 national and regional artificial intelligence strategies, sourced primarily through the OECD.AI Policy Observatory (Policies - OECD.AI) and supplemented by additional searches to fill coverage gaps. These strategies represent a global sample, including five from Arab countries and others from the European Union (EU) and African Union (AU). Each strategy was systematically reviewed for mentions of key migration-related terms: “refugees,” “migrants,” “migration,” “immigration,” and “immigrants.”

Occurrences of these keywords were extracted, categorized by country, and contextualized through thematic analysis. To deepen insight and enhance consistency, AI tools such as ChatGPT and Deepseek were used in conjunction with human validation to analyze the content of relevant excerpts. This process yielded six recurring themes that illustrate how national AI strategies engage—directly or indirectly—with human mobility. These themes span the policy lifecycle, from attracting AI talent to addressing ethical considerations for displaced populations.

The findings point to stark disparities. While countries like Ireland, Kenya, and Greece actively integrate migration into their AI visions, most Arab countries remain disengaged from this intersection. This silence has significant implications: by failing to account for mobile and marginalized populations, Arab AI strategies risk reinforcing exclusionary development models, undermining the very technological futures they seek to build.

In what follows, the article unpacks these six themes and concludes by proposing a regionally grounded, refugee-inclusive AI agenda that aligns innovation with equity and human rights.

Identified Themes from National AI Strategies

The analysis of 22 national and regional AI strategies reveals six recurring themes in how migration, immigration, and refugee issues intersect with artificial intelligence governance. These strategies demonstrate a range of ways in which AI is envisioned—as a tool to manage human mobility, a mechanism to attract global talent, a means for socio-economic integration, or a potential site of ethical risk. Crucially, these themes reflect both action and omission: while some countries actively address the needs and roles of mobile populations in AI policy, the vast majority remain silent.

To organize these findings, this article presents a six-phase framework that traces how refugees and migrants may be considered—implicitly or explicitly—across the policy lifecycle. Rather than treating migration as a single policy domain, the framework maps it across a continuum of relevance, from initial attraction of talent to long-term ethical governance. These six phases are:

1. Attraction and Talent Growth: Policies that seek to attract migrants and refugees as skilled contributors to AI innovation and national competitiveness.
2. Border Innovation: AI applications in border management, immigration control, and security screening.
3. Economic and Labor Market Integration: Strategies that position migrants and refugees as part of the domestic AI workforce and broader labor ecosystem.
4. Social Inclusion and Service Access: AI use in facilitating education, health, public services, and social integration for displaced or vulnerable groups.
5. Talent Retention and Brain Drain Mitigation: Efforts to retain domestic talent or engage diasporas to prevent erosion of national AI capacity.
6. Ethical and Rights-Based AI Governance: Frameworks that acknowledge potential harms of AI deployment on mobile populations and propose safeguards or inclusive design.

These six dimensions form a process-oriented view of how mobile populations might engage with—or be impacted by—national AI systems. Table 1 presents a detailed thematic breakdown of how each of these themes appears across the 22 analyzed strategies. It also distinguishes between Arab and non-Arab states, highlighting that while some countries like Ireland, Kenya, and the Netherlands are actively incorporating migration considerations, most Arab countries remain absent from the discussion.

In total, 37 non-Arab countries and 3 Arab countries made no mention of migration-related terms in their AI strategies. Notably, only one Arab country (Saudi Arabia) addressed the role of migration in AI talent attraction, while another (Egypt) briefly engaged with concerns around brain drain. The lack of attention to refugees and migrants in national AI visions across the Arab region underscores the urgency of rethinking policy frameworks to ensure that technological innovation does not entrench exclusion—but rather becomes a pathway toward inclusive governance.

Table 1. The number of countries addressing each of the six themes.

Theme 1: Refugees and Migration as Catalysts for AI Talent Growth

A key theme emerging from several national AI strategies is the strategic use of migration policy to attract and retain highly skilled professionals in AI and related technological fields. Among the 22 countries referencing migration, seven explicitly promote economic migration schemes targeting researchers, innovators, and tech experts as a means to boost national AI capacity.

Targeted visa programs are a common mechanism. Greece, for example, introduced a Tech Visa to attract qualified talent from outside the EU: “Implement a Greek Tech Visa program to facilitate migration of qualified talent from non-EU countries” (Hellenic Republic, 2024, p.39, A blueprint for Greece’s AI transformation).

Rwanda offers a specialized visa framework for exceptional talent, supported by a national skills classification system (MINICT & RURA, 2022, p. 10, The National AI Policy: To leverage AI to power economic growth, improve quality of life and position Rwanda as a global innovator for responsible and inclusive AI). The Czech Republic’s Fast Track and Welcome Package schemes provide long-term and permanent residency options for researchers and experts: “Promotion and assistance in the use of existing projects of economic migration for researchers and experts… and granting permanent residence in the interest of the Czech Republic” (MIT, 2019, p. 15, National Artificial Intelligence Strategy of the Czech Republic).

In the Arab region, Saudi Arabia is the sole country explicitly engaging with AI-relevant migration. Its Talent Incentives Program seeks to attract foreign AI professionals through favorable immigration policies: “Attract foreign talents to KSA Data & AI sector through attractive and welcoming immigration policies” (SDAIA & MCIT, 2020, p. 31, National Strategy for Data & AI).

The United States has also moved to revise its immigration frameworks, prioritizing individuals with “extraordinary ability” in AI under visa categories such as O-1A, EB-1, and EB-2. Planned updates include expanding visa renewals for J-1 scholars and F-1 STEM students, and publishing migration trend data to inform policy (The White House, 2023, pp.75205–75206, Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence).

Beyond attraction, some countries address inclusion and reintegration. South Korea extends job-seeker support to marriage migrants and North Korean defectors. Ireland’s Women ReBOOT program enables migrant women with tech experience to re-enter the workforce. Slovakia links migration policy to digital talent development through urban innovation and quality-of-life incentives (ODPMII, 2019, p. 15, 2030 Digital Transformation Strategy for Slovakia).

These cases reflect three intersecting priorities:

• Building competitive AI ecosystems through global talent acquisition.
• Addressing labor shortages by tapping into underutilized migrant skillsets.
• Fostering gender and social inclusion within tech sectors.

While a handful of countries, including Saudi Arabia, are beginning to align migration policy with AI development, most Arab states remain disengaged from this conversation. This absence signals a missed opportunity—not only to enhance innovation capacity, but also to position migration as a strategic asset rather than a challenge. An inclusive approach to AI talent development would require Arab governments to adopt more proactive, rights-based migration frameworks that recognize displaced populations not only as beneficiaries of AI, but as contributors to its future.

Theme 2: Refugees and Migration as Catalysts for AI-Driven Border Innovation

A second key theme identified in national AI strategies is the deployment of AI technologies in the service of border control, immigration enforcement, and migration management. While fewer countries address this theme compared to talent attraction, those that do highlight a growing trend: using AI to streamline, securitize, and automate border regimes.

Three countries—Greece, Singapore, and Spain—explicitly reference AI-driven innovation in the governance of borders and migration flows. These strategies often frame AI not only as a tool for enhancing efficiency, but as a solution to perceived risks associated with irregular migration, smuggling, or overstretched asylum systems.

In Greece, for instance, the national AI strategy proposes a regulatory sandbox model for piloting new technologies in high-risk sectors, including migration control: “Develop regulatory sandboxes in migration, health, and law enforcement to test emerging AI tools” (Hellenic Republic, 2024, p. 42, A blueprint for Greece’s AI transformation).

Singapore advances a fully automated risk assessment system at its borders, integrating AI for facial recognition, behavioral analytics, and data cross-referencing to manage traveler flows and detect threats (SNDGO, 2019, National Artificial Intelligence Strategy: Advancing Our Smart Nation Journey).

Spain, meanwhile, incorporates satellite-based surveillance systems and predictive analytics to detect and monitor irregular migration routes across the Mediterranean, with a focus on early warning and resource optimization: “Application of AI in monitoring and prediction in areas such as migration, trafficking, and humanitarian response” (MINECO, 2020, p. 61, Estrategia Nacional de Inteligencia Artificial).

These examples reflect a global shift toward what scholars have described as “digital bordering”—the outsourcing of immigration decision-making to algorithmic systems, often without sufficient transparency or accountability (Rinaldi & Teo, 2025, The Use of Artificial Intelligence Technologies in Border and Migration Control and the Subtle Erosion of Human Rights). AI-driven border tools increasingly operate at the intersection of surveillance, security, and humanitarian governance, raising critical questions about proportionality, fairness, and due process.

Despite this global trend, no Arab country explicitly addresses the use of AI in border control or immigration enforcement within their national AI strategies. This silence may stem from the securitized and opaque nature of migration governance in the region, where technologies are likely being deployed without formal policy articulation or public oversight. Alternatively, it may reflect a lack of investment in AI capacity for border innovation altogether.

The absence of strategic direction on this front is concerning. The rapid proliferation of AI in border contexts—facial recognition at checkpoints, biometric screening at entry points, algorithmic profiling for visa and asylum decisions—demands robust governance frameworks. Without them, Arab states risk replicating exclusionary and rights-eroding practices already criticized in other regions.

In sum, while countries like Greece, Singapore, and Spain are at the forefront of AI-enabled border innovation, the Arab region remains disconnected from both the promise and the perils of this development. Integrating ethical oversight, legal safeguards, and regional coordination mechanisms into any future adoption of AI in migration governance will be essential to avoid deepening marginalization and reinforcing technological opacity at the border.

Theme 3: Refugees and Migration as Economic Accelerators in AI Development

A third emerging theme in global AI strategies is the integration of migrants—not only as elite talent to attract, but as essential contributors to broader economic development and labor market resilience. Five countries—across Europe, Asia, and Africa—explicitly link migration to labor needs, retention goals, and knowledge transfer in the context of national AI advancement.

In Europe, economic migration programs are increasingly aligned with workforce development in the tech and AI sectors. The Czech Republic emphasizes continuity in its Fast Track and Welcome Package schemes, designed to attract and retain highly qualified foreign workers: “Continuously implement economic migration programmes aimed at facilitating the arrival of highly qualified employees… and adapt them to practical needs” (MIT, 2019, pp. 22–23, National Artificial Intelligence Strategy of the Czech Republic).

Ireland adds a social dimension to its strategy by liberalizing spousal work rights, aiming to support family cohesion and improve the overall appeal of the country for skilled migrant workers: “The liberalisation of restrictions around spousal working rights should help boost initial attraction and retention” (Government of Ireland, 2021, p. 58).

In Asia, strategies prioritize labor equity and support for underrepresented or vulnerable migrant populations. South Korea offers employment assistance to marriage migrants and North Korean defectors, recognizing their integration as a socioeconomic imperative (MSIT, 2019, p. 45, National Strategy for Artificial Intelligence). Meanwhile, Turkey directly states its intention to employ immigrants skilled in AI: “Foreign nationals and immigrants with the necessary qualifications… will be employed to contribute to AI sector development” (MoIT & CBDDO, 2021, p. 64, National Artificial Intelligence Strategy 2021-2025).

In Africa, national strategies emphasize long-term capacity building through mobility and skills exchange. Kenya, for example, promotes simplified migration frameworks to recruit foreign AI talent not only to address immediate gaps, but to facilitate knowledge transfer to local professionals: “Facilitating the acquisition of quality foreign AI talent… can help bridge the skills gap while fostering knowledge transfer to local professionals” (MICDE, 2025, p. 67, Kenya Artificial Intelligence Strategy 2025-2030).

These cases reflect distinct regional logics:

• Europe emphasizes labor retention and family-based integration.
• Asia focuses on equity through the inclusion of historically marginalized migrant groups.
• Africa prioritizes talent mobility as a pathway to knowledge generation and local ecosystem strengthening.

Yet across all of these approaches, a critical absence remains: refugees are consistently excluded from AI labor strategies. While economic migrants are increasingly framed as drivers of innovation and growth, displaced populations are rendered invisible—treated neither as skilled contributors nor as subjects of upskilling and workforce inclusion efforts.

This gap is particularly stark in the Arab region, where no national AI strategy acknowledges the economic or labor potential of refugees or migrants. Given the region’s prominent role as a host of large refugee populations, this silence not only reflects structural exclusion but also represents a missed opportunity to align AI development with inclusive labor practices.

Recognizing the potential of refugees and migrants to contribute to national AI sectors requires a fundamental shift—from viewing them as burdens to viewing them as assets. This would entail:

• Creating pathways for refugee upskilling and credential recognition.
• Designing labor policies that include forcibly displaced populations.
• Fostering cross-sector partnerships that bridge humanitarian assistance with economic development.

Without such inclusion, national AI strategies risk reinforcing dual-track economies—where innovation proceeds on one tier, and exclusion deepens on another.

Theme 4: Refugees and Migration as Imperatives for Inclusive AI Development

A fourth theme emerging from national AI strategies is the use of artificial intelligence to enhance social inclusion and improve public services for vulnerable and mobile populations. Five countries—Ireland, Argentina, India, Spain, and the African Union—explicitly highlight how AI can support refugees and migrants, particularly through language accessibility, education, and digital service delivery. Yet once again, no Arab country addresses this domain, reflecting a troubling policy blind spot.

In Ireland, AI is being used to dismantle linguistic and accessibility barriers for refugee youth. A collaborative initiative with Microsoft is developing AI-powered chatbots that provide educational resources to young refugees in their native languages, ensuring that displaced learners can access high-quality materials without relying on translation or intermediaries (Government of Ireland, 2021, p. 18). This vision of inclusion is extended in Spain, where the national strategy identifies migration as a priority area for AI applications in the public sector, on par with employment, healthcare, and justice (MINECO, 2020, p. 61, Estrategia Nacional de Inteligencia Artificial).

In the Americas, automation and service efficiency are emphasized. The U.S. Department of Immigration has implemented a chatbot to assist users in navigating administrative procedures, while the city of Buenos Aires launched Boti, a virtual assistant available 24/7 to answer resident queries, including those related to migration and public services (MINCYT, 2019, p. 134, Plan Nacional de Inteligencia Artificial).

India presents a different model, leveraging AI for predictive governance. Its national strategy incorporates migration trend analysis into chatbot-based grievance redressal and public service delivery, aiming to optimize administrative responsiveness in contexts of population mobility (NITI Aayog, 2018, p. 40, National Strategy for Artificial Intelligence #AIforAll).

On the African continent, the African Union’s continental AI strategy takes an explicitly equity-oriented stance. It calls for AI solutions that serve marginalized communities—including migrants, persons with disabilities, and those lacking access to dominant languages—by investing in natural language processing for local and indigenous languages (AU Commission, 2024, p. 52). It also stresses the importance of including vulnerable groups in AI training and capacity-building efforts to prevent their exclusion from emerging digital economies, arguing that AI training must “include vulnerable groups… to ensure they are not left out of the digital environment powered by AI” (AU Commission, 2024, p. 48).

These regional approaches illustrate how AI can be used not just to manage migration, but to support migrant well-being and inclusion. European strategies tend to focus on access to education and inclusive public services. The Americas prioritize administrative efficiency and 24/7 service access. African strategies foreground anti-discrimination, linguistic equity, and participation, while India centers predictive analytics and resource planning.

However, across all these efforts, Arab national AI strategies remain entirely silent on the use of AI for migrant inclusion. This absence is particularly concerning given the region’s centrality to global displacement flows and its growing investments in smart governance. The failure to articulate how AI might support refugees and migrants—whether through service delivery, education, language access, or inclusion in digital infrastructure—signals not only a policy oversight, but a missed ethical and developmental opportunity. As AI systems continue to reshape public services, ensuring that they are designed to include, rather than exclude, displaced populations must become a strategic priority.

Theme 5: Refugees and Migration as Dual Challenges in AI Talent Retention

A fifth theme identified in national AI strategies relates not to the attraction of new talent, but to the retention of existing talent and the mitigation of brain drain—issues that are especially critical in developing contexts where skilled professionals often migrate to more advanced economies. Among the 22 countries referencing migration, only three—Nigeria, Egypt, and Ireland—explicitly engage with this challenge in the context of AI development. The theme remains largely absent across the Arab region, despite widespread concern about talent loss and its impact on innovation ecosystems.

In Nigeria, the national AI strategy offers one of the clearest acknowledgments of this issue. It warns that the emigration of skilled professionals is severely undermining the country’s ability to develop a robust AI sector, noting that “Nigeria is experiencing a considerable brain drain… this outflow of talent deprives the country of valuable, talented people and exacerbates the talent shortage” (NCAIR & NITDA, 2024, p. 32, National Artificial Intelligence Strategy). The strategy further links brain drain to macroeconomic instability, highlighting its ripple effects on investment in health, education, and digital infrastructure (NCAIR & NITDA, 2024, p. 63, National Artificial Intelligence Strategy).

Egypt, in its 2021 national AI strategy, similarly raised concern over the emigration of scientists and engineers, describing it as a “major problem” and emphasizing that “the immigration of Egyptian scientists and engineers to more advanced economies can have the most detrimental impact on the AI sector” (MCIT & NCAI, 2021, p. 52, Egypt National Artificial Intelligence Strategy). Yet tellingly, this concern is no longer referenced in the updated 2025–2030 strategy, suggesting a possible shift in policy priorities or a de-prioritization of the issue altogether.

By contrast, Ireland and the European Union approach brain drain more proactively. Rather than viewing it solely as a threat, they emphasize coordinated legal mechanisms to retain talent. The EU’s strategy encourages member states to reinforce excellence through improved implementation of the Blue Card scheme, stating that they will “reinforce excellence and retain talented workers… including the Blue Card to attract talent” (European Commission, 2018, p. 5, Coordinated Plan on Artificial Intelligence). Ireland’s approach aligns with this vision, framing talent retention as part of a broader ecosystem that supports both domestic professionals and migrant workers through rights-based integration policies.

These strategies reflect two broad paradigms. On one hand, Nigeria and Egypt highlight the risks and consequences of brain drain, but offer few sustained or forward-looking solutions. On the other, Ireland and the EU focus on legal and institutional tools—like residency pathways and talent mobility frameworks—that aim to retain skilled workers and address the structural causes of talent flight.

Crucially, no Arab national AI strategy beyond Egypt even mentions talent retention or diaspora engagement. This silence is especially significant given the widespread emigration of highly educated Arab youth, the existence of vibrant tech-savvy diaspora communities, and the well-documented barriers to reintegration for returning professionals. Without formal mechanisms to track, engage, or incentivize return, these populations remain disconnected from national AI agendas.

Addressing this gap will require Arab countries to reframe skilled migration not only as a loss but as a transnational opportunity. This could include:

• Developing incentive-based return programs for AI professionals in the diaspora.
• Creating virtual collaboration platforms that allow knowledge exchange without requiring physical return.
• Establishing regional talent-sharing frameworks that facilitate mobility while strengthening local ecosystems.

The challenge of talent retention cannot be separated from the broader politics of migration and inequality in the global AI economy. For Arab countries seeking to position themselves as AI innovators, investing in inclusive, rights-based strategies to retain and engage local and expatriate talent is not optional—it is foundational.

Theme 6: Refugees and Migration as Catalysts for Ethical AI Governance

A sixth and final theme identified in global AI strategies relates to the ethical dimensions of AI governance, particularly as they concern vulnerable and mobile populations. While most national strategies frame AI ethics around abstract values such as fairness, transparency, and human rights, only three actors—the Netherlands, the African Union, and Japan—explicitly acknowledge the risks AI poses for refugees, migrants, or displaced groups. These risks include surveillance, bias, exclusion, and the erosion of rights at the intersection of security, mobility, and technology.

In Europe, the Netherlands situates its ethical AI strategy within the broader regulatory framework of the European Union. It highlights the European Commission’s intent to develop a dedicated strategy for AI in security and migration domains, noting that this will be coordinated through the Directorate-General for Migration and Home Affairs. This approach is embedded within a multi-stakeholder governance model that includes INTERPOL, the UN Crime and Justice Research Institute, and the Council of Europe’s Ethical Charter on AI in judicial systems (EZK, 2019, p. 16, Strategic Action Plan for Artificial Intelligence: The Netherlands). Here, migration is framed as both a security concern and a domain requiring legal oversight and ethical constraint.

The African Union, by contrast, offers a more human-centered framing. It warns that while AI holds transformative potential, it is also accompanied by significant risks—including algorithmic bias, disinformation, surveillance, and discrimination—especially for vulnerable groups such as migrants, women, and persons with disabilities. The AU strategy calls for inclusive safeguards, affirming that “these benefits are accompanied by AI risks… including bias, discrimination of vulnerable persons (migrants…), surveillance, and copyright violations” (AU Commission, 2024, p. 3). It further advocates for AI systems that reflect socio-economic justice and incorporate indigenous knowledge, highlighting the importance of protecting those on the peripheries of data-driven governance.

In Japan, ethical AI development is linked to broader goals of environmental sustainability and demographic resilience. The strategy envisions digital innovation—such as Digital Twins and flexible work environments—as enabling more decentralized lifestyles and supporting climate-resilient forms of migration. Rather than treating migrants as security subjects or passive aid recipients, Japan’s approach imagines them as active participants in digitally inclusive futures, noting that digitization “will enable flexible work and lifestyles… opening the way to migration… and realizing inclusion of diversity and sustainability” (CAO, 2022, p. 13, AI Strategy 2022).

These three approaches reflect distinct regional values. The EU model emphasizes legal regulation and rights-based oversight in security contexts. The AU framework centers harm prevention and equity for marginalized populations. And the Japanese strategy aligns AI ethics with sustainability, decentralization, and social innovation.

Despite these promising directions, a significant limitation remains: none of these strategies offer a comprehensive framework for cross-border accountability or refugee-specific protections in AI systems. Mobile populations continue to fall through the cracks of national ethics regimes, which tend to be either securitized, generalized, or heavily abstracted.

Most notably, Arab national AI strategies are entirely silent on the ethical implications of AI for displaced populations. Given the region’s long-standing entanglement with displacement, conflict, and securitized migration governance, this omission raises serious concerns. It reflects not only a lack of inclusive foresight, but a broader failure to engage with AI’s potential to either entrench or disrupt existing systems of exclusion.

Moving forward, ethical AI governance in the Arab region must prioritize:

• Algorithmic impact assessments that explicitly account for refugee and migrant populations.
• Participatory design processes that include displaced communities as stakeholders in AI system development.
• Regional oversight mechanisms to ensure that AI used in migration, border management, and public service delivery is rights-respecting and transparent.

Ultimately, the question is not only what AI can do, but whom it serves—and whom it excludes. An ethics framework that fails to address the lived experiences of displaced populations risks reproducing the very inequalities AI promises to solve.

Incorporating Refugees and Migrants into National AI Strategies

While several global AI strategies meaningfully engage with migration-related themes, Arab countries remain largely silent. Egypt briefly raises concerns about brain drain, and Saudi Arabia outlines policies to attract foreign AI talent, but broader considerations of migration governance, refugee inclusion, and ethical implications remain absent. This silence reinforces the need for a regionally grounded and inclusive AI agenda—one that does not treat migration as an externality but sees it as central to technological and social transformation. Drawing on the six themes identified in global strategies, Arab states can begin to develop AI approaches that engage with refugees and migrants not as peripheral actors, but as co-constituents in the future of digital governance.

To begin with, Arab national strategies could integrate migration policies into AI development agendas by learning from models such as Greece’s Tech Visa, Rwanda’s specialized frameworks for AI talent, and the United States’ prioritization of individuals with extraordinary ability. These examples demonstrate how visa pathways, skills recognition, and legal reform can build domestic AI ecosystems by incorporating international expertise. However, efforts to attract talent must be balanced with ethical commitments: mitigating the brain drain from developing economies, fostering upskilling initiatives for underrepresented migrant groups, and supporting gender-inclusive programs like Ireland’s Women ReBOOT. Regional cooperation could also play a role—through harmonized standards for skills assessments, mutual recognition of qualifications, and AI-focused migration partnerships.

At the same time, Arab countries must confront the dual challenge of ensuring security and upholding rights in AI-powered migration governance. Lessons from global case studies—such as Greece’s regulatory sandbox for border AI, Singapore’s automated risk assessments, and Spain’s use of satellite data to detect trafficking—highlight both the capabilities and dangers of AI in securitized contexts. Algorithmic bias, opaque decision-making, and unchecked surveillance disproportionately harm mobile populations, particularly when safeguards are absent. Responsible governance frameworks are urgently needed—ones that establish standards for fairness and transparency, require meaningful human oversight in automated systems, and invite multi-sectoral participation from governments, civil society, and migrant communities themselves.

Beyond borders, refugees and migrants must also be recognized as part of the economic and labor infrastructure of AI development. Countries like the Czech Republic, South Korea, and Kenya show how migrants can be woven into workforce development strategies—not simply as external talent, but as contributors to knowledge transfer, capacity building, and local innovation. In the Arab region, where large refugee populations already reside, strategies could support AI-skilled refugees through targeted visa programs, public-private partnerships, and regionally coordinated integration schemes. Recognizing and validating prior qualifications, developing ethical recruitment guidelines, and investing in inclusive talent pipelines would not only serve displaced populations but enhance national competitiveness.

Equally important is the potential for AI to improve access to public services, especially for refugees and migrants. Global cases—from Ireland’s chatbots for young refugees to Argentina’s Boti virtual assistant, India’s predictive public service models, and the African Union’s commitment to local language processing—illustrate how AI can enhance service delivery, language accessibility, and social integration. In contrast, most Arab AI initiatives remain focused on infrastructure, often disconnected from governance or equity concerns. As seen in the region’s smart city development (Hendawy & Al Mansour, 2025, How Arab smart cities are performing over the years: Cities’ infrastructure in relation to their technological progress), technology investment without inclusive design tends to replicate existing hierarchies. Integrating AI into education, healthcare, and administrative systems in a rights-based and participatory manner could help bridge this gap.

Moreover, Arab strategies must address the persistent challenge of brain drain. Countries like Nigeria and Egypt have raised the alarm on skilled emigration, while the EU and Ireland have developed tools to mitigate it—such as the Blue Card scheme and coordinated retention policies. The Arab region could adopt similar approaches by establishing incentive-based return programs, engaging diaspora networks through virtual platforms, and building regional talent-sharing mechanisms. Strategies should be multi-layered: short-term policies to stem immediate losses, medium-term tools to connect with expatriates, and long-term reforms to build resilient domestic ecosystems.

Finally, any inclusive AI strategy must grapple with the ethical and rights-based governance of AI systems in migration contexts. As highlighted in the approaches of the Netherlands, Japan, and the African Union, this requires balancing technological innovation with social justice. Yet Arab countries remain absent from global ethical conversations on AI and migration—despite being central to both domains. Moving forward, regional strategies could adopt tools like algorithmic impact assessments tailored to displaced populations, design frameworks that include migrants in participatory policymaking, and contribute to transnational AI ethics discussions. Such engagement is not only urgent—it is foundational to ensuring that technological progress in the region does not deepen existing exclusions.

Conclusion

Arab national AI strategies remain largely silent on the inclusion of refugees and migrants, despite the growing role of AI in shaping governance, public services, and labor markets. This absence reflects broader patterns of exclusion and risks deepening inequality in a region already marked by displacement. In contrast, global strategies increasingly recognize the value of integrating migration into AI agendas—whether through ethical safeguards, inclusive labor policies, or digital service access for displaced populations. These examples show that AI can support not only innovation, but also justice and equity. For the Arab region, developing a refugee- and migrant-inclusive AI agenda is both a strategic opportunity and an ethical obligation. Such an approach must center on participatory design, rights-based governance, and structural inclusion. Refugees and migrants must not remain on the margins of technological progress—they must help shape it.

This article is part of a series of articles commissioned under the ‘Resilience and Inclusive Politics in the Arab Region’, generously funded by the Carnegie Corporation.