By Hisham Jabi, CEO and Founder of Jabi Consulting
Washington, DC
Is AI Solving the Youth Labor Market Mismatch in MENA?
Artificial intelligence is rapidly reshaping labor markets across the world. In the Middle East and North Africa (MENA), however, the central issue is not simply technological disruption. It is whether AI can address—or will instead deepen—the region’s long-standing mismatch between youth entering the labor market and the opportunities available to them. The evidence suggests that without deliberate interventions supported by political leaders and led by private sector, AI is more likely to intensify this mismatch than resolve it.
MENA already faces the most constrained youth labor market globally. Youth unemployment stands at approximately 25 percent—the highest in the world—and exceeds 30 to 40 percent in several countries, including Palestine, Jordan, and Tunisia. Nearly one in three young people is not in employment, education, or training (NEET), and youth are five times more likely to be unemployed than adults. These outcomes are not temporary fluctuations; they reflect deep structural weaknesses in how labor markets function across the region.
Demographics further amplify the challenge. More than 55 percent of the population in MENA is under the age of 30, creating sustained pressure on labor markets that are already unable to absorb new entrants. Even in the absence of technological disruption, job creation has not kept pace with labor supply. AI is entering a system in MENA that is already under strain.
At the same time, the region is far from uniform. The GCC countries—such as the United Arab Emirates and Saudi Arabia—represent high-income, rapidly transforming economies that are investing heavily in artificial intelligence and digital infrastructure. These countries are generating demand in advanced sectors, including logistics, services, and AI-driven industries. Yet even here, a paradox persists: while demand for skills is rising, local youth are often not aligned with market needs, and reliance on expatriate labor remains high.
In North Africa, including Egypt, Morocco, and Tunisia, the challenge is more acute. Labor supply is large, job creation is limited, and education systems remain misaligned with market demand. Evidence from Egypt indicates that approximately 21 percent of jobs are at high risk of automation, while only about 24 percent of workers can transition easily into new roles. Nearly 75 percent require significant reskilling. This suggests that AI-driven disruption in these contexts is unlikely to be absorbed smoothly.
The Levant presents a different but equally complex picture. Countries such as Jordan, Syria, Lebanon, and Palestine exhibit relatively strong educational attainment but weak economic absorption. High levels of graduate unemployment reflect limited private sector growth and constrained economic environments. In these settings, human capital exists but is not effectively utilized.
Across all three subregions, a consistent pattern emerges: a structural mismatch between what education systems produce and what labor markets demand. Education continues to emphasize memorization and theoretical knowledge, while employers (especially in emerging AI-intensive industries) increasingly require critical thinking, digital literacy, communication skills, and adaptability. At the same time, labor market systems lack the data, coordination, and institutional capacity to align supply and demand effectively. I fully recognize that the lack of jobs in several countries remains a critical challenge. However, the rapid transformation driven by AI across multiple sectors is accelerating faster than labor systems can adapt, making the skills mismatch an even more significant and urgent issue that must be addressed with speed and focus.
It is within this context that AI must be understood. Globally, artificial intelligence is expected to reshape up to 60 percent of jobs and automate approximately 30 percent of tasks by 2030. Two-thirds of jobs in advanced economies are already considered exposed to AI. Importantly, the impact is not evenly distributed. Entry-level white color jobs with routine roles—those that typically serve as gateways for young workers—are the most vulnerable. Early evidence suggests that entry-level opportunities in AI-exposed sectors are already declining by 13 to 20 percent, while a majority of firms report reducing hiring for junior roles.
In MENA, this trend carries particular risk. The region’s primary challenge is not job destruction, but limited access to jobs. AI, by compressing entry-level roles and increasing skill thresholds, risks narrowing this access further. At the same time, demand for AI-related skills is rising rapidly—by as much as sevenfold in recent years—creating a widening gap between those equipped to participate in the new economy and those who are not.
Yet the economic potential of AI in the region is significant. Estimates suggest that AI could contribute up to $320 billion to Middle East GDP by 2030. This creates a paradox: strong growth potential alongside the risk of labor market exclusion. Growth, in this context, does not automatically translate into employment.
The implications are clear. AI is likely to increase inequality within the region, particularly between the GCC and non-GCC countries. It may accelerate brain drain, as skilled workers migrate toward more dynamic markets across the GCC. Most critically, it risks eliminating or narrowing the entry points through which young people access employment. The rapid adoption of AI in the GCC is likely to accelerate economic growth, but not in a way that is evenly distributed. It will further widen income disparities between GCC economies and the rest of the region, while also concentrating job creation in higher-skill, AI-enabled sectors. This risk leaving large segments of youth—particularly in non-GCC countries—further excluded from emerging opportunities. If not addressed, this divergence could deepen economic imbalances and become a source of increased instability in an already fragile and uncertain regional context.
However, this outcome is not inevitable. The core problem in MENA is not simply a lack of jobs or skills—particularly if the region is viewed as a single economic bloc, and given the nature of AI-enabled work that allows for remote employment. Rather, it is the absence of systems that effectively connect supply and demand. AI-powered labor market platforms, if deployed strategically, can serve as system integrators rather than disruptive forces.
Artificial intelligence can be used to map labor market demand in real time, identifying emerging skills across sectors and geographies. It can support adaptive, personalized training pathways that align with these demands, enabling large-scale reskilling with connection to real jobs. It can also improve matching between employers and job seekers, reducing friction and inefficiencies that currently characterize labor markets.
A practical application of this approach would be the development of AI-powered labor market platforms that integrate demand signals, education systems, and career pathways. Such platforms could guide youth toward relevant training, inform government policy, and support private sector hiring at scale. They could operate across key sectors, including services, supply chains, healthcare, education, tourism, and AI/technology itself, helping to create a more responsive and inclusive labor ecosystem.
For this to succeed, policy must evolve. Governments must move beyond traditional education reforms and invest in systems that enable employability. This includes prioritizing skills over credentials, building data-driven labor market infrastructure, and fostering regional coordination between labor-surplus and labor-demand economies.
AI will not, on its own, solve the youth employment challenge in MENA. Left unmanaged, it is likely to deepen existing structural constraints. But if applied with intention, it can become a powerful tool for bridging the gap between supply and demand. The future of employment in the region will depend not on how many jobs are created, but on how effectively systems enable young people to access, adapt to, and participate in a rapidly evolving labor market.
