Blockchain technology has increasingly drawn the attention of governments seeking to modernize public services through transparent, secure, and efficient digital infrastructures. Drawing on case studies from diverse regions, including the UAE, Estonia, Georgia, Colombia, and multiple Gulf Cooperation Council (GCC) nations, this systematic review synthesizes implementation patterns across domains such as land administration, digital identity, procurement, and intergovernmental payments. The critical analysis highlights blockchain’s capacity to establish tamper-evident records, automate verification, and reduce administrative overhead while also addressing technical and institutional factors that shape its impact. Outcomes across successful deployments suggest that benefits are most pronounced when blockchain aligns with real governance needs and is supported by robust legal and digital infrastructure. This review also identifies key barriers to adoption, including interoperability challenges, regulatory uncertainty, limited technical capacity, and resistance to organizational change. Notably, this review highlights a critical but underexplored dimension involving the need for public accountability not only in service delivery but also in the governance of blockchain systems themselves. By examining real-world use cases alongside technical and policy frameworks, this review advances a deeper understanding of blockchain’s role in reshaping public administration and sets a research agenda for building more trusted, auditable, and inclusive digital government systems.

The Dubai Government has made significant investments in digital learning through platforms such as Al Mawrid and Bayanati, enabling widespread access to employee training and upskilling. However, there remains a major gap in translating accumulated learning into intelligent workforce restructuring. This paper proposes “SkillChain DX,” a policy-driven framework that applies artificial intelligence (AI) to dynamically map employee-acquired skills to evolving job roles across departments, developed using a conceptual design science and policy analysis approach. The framework integrates blockchain to ensure secure, tamper-proof verification of skill credentials across diverse training platforms. To validate feasibility, a pilot prototype was implemented using sentence-transformer models for semantic skill inference and cryptographic hashing mechanisms for decentralized credential verification. Experimental evaluation across six controlled scenarios demonstrated an average role-matching accuracy of approximately 82%, blockchain transaction throughput exceeding 1000 operations per second, and near-instant credential verification with over 99% performance improvement compared to manual processes. The findings demonstrate that integrating AI-driven skill inference with decentralized credential verification can significantly enhance internal mobility, role alignment, and workforce planning at a policy level. The study benchmarks international practices and outlines a practical implementation path for the Dubai Government using only publicly available technologies and case studies, positioning SkillChain DX as one of the first integrated AI–blockchain policy frameworks tailored to public sector human resources (HR) transformation in Dubai. The proposed system framework bridges the current disconnect between training access and organizational transformation, supporting a proactive, transparent, and skills-first public sector, while offering actionable policy insights for future government HR modernization.