<![CDATA[This study employs a bibliometric approach to analyze the evolution of literature on artificial intelligence (AI) and work transformation, aiming to map the knowledge structure and research trends in this field. While existing studies have predominantly focused on the technical dimensions of AI, significant gaps remain regarding social perspectives, particularly in developing country contexts. Our analysis addresses this limitation by systematically examining 718 Scopus-indexed documents (2014-2024) using VOSviewer for network visualization through bibliographic coupling and co-citation analysis. The results reveal a marked increase in publications post-2018, driven by technological advancements and sociological debates on automation. Co-citation analysis identifies six thematic clusters, including AI's labor impact, ethical considerations, and human-AI collaboration, while bibliographic coupling highlights sector-specific applications in healthcare and manufacturing, alongside persistent challenges such as skill gaps. Notably, the findings underscore the Western-centric nature of current discourse, calling for more inclusive research in Global South contexts. The study contributes to policy discussions by emphasizing the need for adaptive regulatory frameworks, reskilling initiatives, and micro-credential-based education systems. Although limited to Scopus-indexed literature, this research provides valuable insights for shaping future academic inquiry and evidence-based policymaking in the era of digital transformation.]]>
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