Exploration of AI Powered Human-Computer Interaction on Employee Career Mobility and Career Path Diversity

With the rapid development of human-machine interaction technology, people's work methods and content have undergone tremendous changes, which have had a profound impact on employee career mobility and diversity. Therefore, this project aims to explore the mechanism of how this change affects individual growth and organizational stability from two perspectives: individual development and organizational stability. Firstly, this project will systematically examine the impact of technological progress on job automation and talent demand from both theoretical and empirical perspectives, and explore its role in talent mobility and path diversification. In terms of research methods, a combination of qualitative and quantitative approaches is adopted. Quantitative analysis used big data to analyze employee mobility and combined it with technological applications to establish a quantitative evaluation model for personnel mobility. Qualitative research uses in-depth interviews to uncover the career development trajectories of managers and employees from their practical application experiences. In technology intensive, service, manufacturing, and creative fields, the application proportion of artificial intelligence technology has gradually increased from 20% to 40%, while the career diversification index has risen from 1.85 to 2.10. The research results show that human-machine interaction technology can significantly enhance the flexibility and diversity of personal career development by reshaping roles and job requirements. The research results will provide new theoretical basis for a deeper understanding of the impact of the technological revolution on talent mobility and diversity.