Adaptation of Generation Z Employees to Artificial Intelligence in the Workplace Implications for HR Management - Muhammad Ramdhan (Jurnal Nasional Manajemen Pemasaran dan SDM, 2026)
This study aims to explore how Generation Z employees adapt to the implementation of Artificial Intelligence in the workplace and to examine its implications for Human Resource Management (HRM). The research was conducted in organizations located in Cianjur, Indonesia, using a qualitative approach. Data were collected through semi-structured interviews with 10–15 Generation Z employees, selected purposively. The data were analyzed using thematic analysis to identify patterns related to adaptation processes, challenges, and organizational support. The findings reveal that Generation Z employees demonstrate a high level of adaptability to AI technologies, primarily through self-directed learning, peer collaboration, and experiential learning. AI is perceived as a tool that enhances efficiency, productivity, and decision-making accuracy. However, several challenges were identified, including limited advanced digital skills, fear of job displacement, and insufficient organizational support. The study also finds that adaptation to AI is not solely a technical process but involves psychological and organizational dimensions. Furthermore, HRM plays a crucial role in facilitating successful AI adoption. HR is expected to act as a strategic partner by providing continuous training, fostering a digital organizational culture, and supporting employees’ emotional readiness. The study concludes that the success of AI implementation depends on the alignment between technology, human resources, and organizational strategies. This research contributes to the literature by providing context-specific insights from a regional setting and highlighting the importance of a human-centered approach in managing digital transformation. Future research is recommended to adopt quantitative or mixed-methods designs and to explore broader contexts to enhance generalizability