AI-Driven EdTech Innovations for Workforce Reskilling: Bridging Education and Business Needs

This study explores how artificial intelligence (AI)-driven educational technologies enhance workforce reskilling effectiveness and bridge the gap between education and industry needs. Focusing on AI-driven content personalization and adaptive learning with engagement tools, the research examines their combined influence on professional skill development and the mediating role of industry–academia collaboration. Using a quantitative descriptive correlational design, data were collected from 230 professionals, trainers, and employees across various sectors engaged in AI-supported training programs. Statistical analyses including correlation, regression, and mediation confirmed that both AI-driven personalization and adaptive learning have a significant positive impact on reskilling outcomes, with adaptive learning showing the strongest influence. The study also found that industry–academia collaboration serves as a vital bridge, strengthening the relationship between AI innovations and workforce reskilling by aligning educational content with real-world job demands. The findings indicate that AI technologies not only enhance learning efficiency but also promote engagement, confidence, and sustained motivation among learners. Furthermore, strong collaboration between academic institutions and industries ensures that AI-integrated training remains relevant and future-focused. The research concludes that combining AI-based adaptive systems with institutional partnerships can create a more inclusive, efficient, and sustainable model for workforce reskilling in the era of digital transformation.