<![CDATA[Rapid technological advancements in generative artificial intelligence, cognitive robotics, and industrial automation are fundamentally reshaping occupational structures and accelerating skill obsolescence across global labor markets. This critical review systematically evaluates upskilling and reskilling strategies designed to foster workforce readiness in automated environments. Synthesizing 16 benchmark empirical and conceptual studies published between 2021 and 2026, this study examines the structural, psychological, and organizational mechanisms through which targeted learning and development (L&D) interventions mitigate skill displacement and enhance adaptive employability. The literature reveals that while technical upskilling enhances domain-specific proficiency, cross-functional reskilling yields broader career mobility and organizational resilience. Furthermore, the efficacy of workforce transformation depends heavily on a supportive learning climate, psychological safety, and AI-driven personalized learning architectures. A structural path meta-analysis demonstrates that strategic upskilling directly influences workforce readiness (β = .48, p < .001), fully mediated by skill transferability and self-efficacy. However, persistent implementation barriers—such as digital divide disparities, micro-credentialing accreditation gaps, and managerial resistance—continue to impede scalable transformation. This review provides an integrative framework and offers practical recommendations for HR leaders and policymakers to align workforce reskilling initiatives with technological adoption.]]>
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