Trends in Employee Competency Development in the Era of Industry 5.0: A Literature Review - Milasari, Neneng; Supriandi, Supriandi (RIGGS: Journal of Artificial Intelligence and Digital Business, 2026)
Industry 5.0 introduces a human-centric paradigm that integrates advanced technologies with human creativity, emotional intelligence, and sustainability values. This study conducts a qualitative literature review of fifteen academic sources identified through Google Scholar to examine emerging trends in employee competency development in the Industry 5.0 era. The findings reveal a fundamental reorientation of workforce requirements, shifting from predominantly technical abilities to hybrid competencies that blend digital literacy, analytical reasoning, socio-emotional intelligence, sustainability awareness, and adaptive learning capacity. Employees are expected not only to master AI-assisted tools, automation systems, and data-driven platforms but also to collaborate effectively with intelligent machines and engage in complex decision-making processes shaped by real-time analytics. At the organizational level, the review highlights the growing importance of human-centered talent development strategies, including reskilling and upskilling initiatives, technology-enhanced learning ecosystems, and AI-supported personalized training pathways. These strategies aim to foster continuous learning and ensure that employee capabilities evolve alongside technological progress. The incorporation of ethical technology use, sustainability-oriented competencies, and psychological well-being further reinforces the principle that innovation in Industry 5.0 must remain inclusive and socially responsible. Overall, the study deepens the understanding of how Industry 5.0 reshapes competency frameworks across sectors and underscores the need for organizations, educators, and policymakers to proactively design learning environments that support future-ready human capital. The findings provide a foundation for developing integrated approaches to workforce transformation and identify gaps for future empirical research.