Background: Artificial intelligence (AI) is fundamentally transforming labor markets worldwide, creating unprecedented challenges for workforce development and national competitiveness. The United Arab Emirates (UAE), with its ambitious Vision 2031 and National AI Strategy 2031, represents a critical case study of how resource-rich economies navigate the transition from oil-dependent models to knowledge-driven, AI-enabled futures. Understanding effective reskilling strategies in this context is essential for policymakers, employers, and educational institutions across the Gulf Cooperation Council (GCC) region and beyond. 

Objective: This article examines reskilling strategies for AI-driven workforce transformation within the UAE context, analyzing how national policies, employer-led initiatives, and educational reforms intersect to prepare workers for an AI-augmented economy. The study synthesizes global best practices with UAE-specific challenges to identify actionable pathways for equitable and sustainable workforce development.

Methods: This study employs a comprehensive literature review and policy analysis approach, synthesizing evidence from 60 peer-reviewed publications, national strategy documents, and institutional reports published between 2019 and 2026. The analysis
integrates theoretical frameworks including socio-technical systems theory, human capital theory, and role redesign frameworks to understand the multidimensional nature of workforce transformation. Evidence is drawn from empirical studies, case analyses, and
policy evaluations across multiple sectors and geographic contexts, with particular attention to GCC-specific initiatives.

Results: The analysis reveals that successful reskilling strategies combine three core elements: skills-first hiring and AI-augmented apprenticeships that rebuild entry pathways; modular lifelong learning systems emphasizing both technical AI literacy and durable
human skills; and policy mechanisms incentivizing credential portability and employer co- investment. In the UAE context, initiatives such as the National AI Strategy 2031, high-tech Emiratisation programs, and pilot credential frameworks like SkillChain DX demonstrate alignment with global best practices. However, significant challenges persist, including a 34% workforce skill gap, emerging two-track talent systems risking labor market bifurcation, organizational resistance to sustained training investment, and regulatory gaps in AI governance. The UAE’s unique labor market composition—characterized by high expatriate participation and traditional public sector preference among nationals—adds complexity to reskilling implementation.

Conclusion: Effective reskilling for AI-driven economies requires coordinated action across multiple stakeholders and policy domains. For the UAE, this means integrating Emiratisation goals with technology-focused workforce development, establishing national skills frameworks with portable microcredentials, funding employer-led apprenticeships through co-investment models, bridging the emerging two-track talent system through mid-career conversion programs, and aligning regulatory frameworks with workforce development objectives. The UAE’s substantial financial resources and proactive digitalization provide advantages, but success depends on addressing structural barriers, ensuring inclusive access to reskilling opportunities, and maintaining alignment between education, labor, and industrial policies. These findings offer actionable insights for policymakers and practitioners navigating similar transitions in resource-rich, rapidly developing economies.