The Digital Native Advantage: Generation Z, Artificial Intelligence, and the Transformation of Organizational Management
DOI:
https://doi.org/10.5281/zenodo.22706875Abstract
Abstract
Managing artificial intelligence (AI) in the workplace requires a workforce that can adapt to rapid technological shifts while maintaining ethical and collaborative practices. This paper examines how Generation Z, the first generation of true digital natives influences contemporary organizational management. Rather than relying on a casual or arbitrary selection of literature, this study follows a structured PRISMA 2020 protocol to identify, screen, and select relevant research. By querying major academic databases including Google Scholar, ScienceDirect, Wiley Online Library, and JSTOR, we analyzed a final corpus of 48 peer reviewed articles published between 2014 and 2024.
The findings reveal a dual layered dynamic in the workplace. On one hand, Generation Z’s natural technological comfort allows them to act as early adopters and informal tech guides, driving "reverse mentorship" programs that help older colleagues adjust to AI tools. On the other hand, their integration creates specific organizational vulnerabilities. Our model highlights severe intergenerational friction with traditional supervisors, a notable risk of "cognitive offloading" causing skill atrophy for roughly 19% of young workers and increased psychological isolation within AI driven workflows.
Ultimately, this study shows that leveraging the digital native advantage requires managers to move away from simply providing tools and instead focus on holistic, people centered governance. These insights offer a practical framework for business leaders and HR professionals looking to maintain competitive, collaborative, and human focused teams in an AI driven era.
Keywords
Artificial Intelligence, Generation Z, workplace integration, management, AI ethics, organizational behavior, generational dynamics
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 African Scientific Journal

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
















