A Literature Survey on AI Driven Career Path Prediction

Abstract

The field of career path prediction and professional planning has seen a significant change due to the growing convergence of AI and computational intelligence. This overview of the literature delves into the latest developments in AI-powered career path prediction, combining research results from several fields. Predictive models and approaches applied to scientists, IT professionals, MBAs, students, and individuals in a variety of industries are examined in this study. The study begins with an analysis of how mixed job expectations affect IT professionals' career satisfaction, emphasizing the careful balance that must be struck between administrative and technical tasks. The gender gap in MBA career trajectories is discussed in the following sections, with a focus on wage distribution, promotions, and patterns of mobility. After that, the review turns its attention to long-term career projections and presents cutting-edge models like NAOMI, Fortune Teller, and CareerBERT