Reskilling and Upskilling in the AI Era

In an era of AI-driven disruption, reskilling and upskilling have become key levers for maintaining workforce relevance. Recent bibliometric data show an annual growth rate of 23% in related research since 2022, a trend that is in sync with the rise of generative AI technologies. This study uses bibliometric analysis based on VOSviewer to map the evolution of relevant research topics in this field from 2015 to 2025. Through the literature indexed by Scopus, this paper finds that there is a ”core-periphery” structure of knowledge production in this field, with many high-impact studies coming from developed countries, obscuring the contextual approaches of developing economies. Current research focuses on key clusters including corporate digital training, policy-led initiatives and ethical frameworks, and personalized learning with artificial intelligence. The analysis highlights systemic gaps, such as the underrepresentation of gender-inclusive strategies and the lack of longitudinal studies tracking policy effectiveness beyond short-term interventions. We propose three future directions: (a) integrating global South perspectives through databases such as MyCite and the ASEAN Citation Index; (b) adopting mixed methods that combine quantitative bibliometrics with qualitative case studies; and (c) developing standardized metrics to assess the equity impact of reskilling programs. This study not only maps the knowledge structure of the field, but also critiques its geographical and methodological biases, calling for a more inclusive research agenda to address the growing skills gap in the AI economy.