UPSKILLING AND RESKILLING STRATEGIES FOR EMPLOYEES FACING AI-DRIVEN AUTOMATION: A CRITICAL REVIEW
Abstract
The rapid diffusion of generative artificial intelligence (GenAI) and algorithmic task automation across modern enterprises has fundamentally accelerated skill obsolescence, creating an urgent strategic imperative for continuous employee upskilling and reskilling. This critical review systematically evaluates contemporary learning and development (L&D) strategies designed to foster workforce readiness in automated work environments. Adhering to the PRISMA 2020 systematic review protocol, a corpus of 16 peer-reviewed benchmark studies published between 2021 and 2026 was synthesized. The thematic analysis categorizes reskilling interventions into personalized AI-driven micro-learning, cross-functional hybrid technical-cognitive development, and human-agent cobot collaboration training. Meta-synthesized structural equation modeling indicates that structured reskilling initiatives exert a robust positive effect on workforce agility (β = .45, p < .001) mediated through skill self-efficacy and psychological job security. Furthermore, multi-level alignment—synchronizing national policy frameworks, organizational L&D infrastructure, and individual growth mindsets—emerges as a decisive boundary condition for sustainable employability. The paper concludes with an integrative governance framework guiding strategic HR leaders in mitigating automation-induced job displacement while enhancing organizational competitiveness.