(untitled) (International Journal of Functional Research in Arts and Humanities (IJFRAH), 2026)
As the quality of education is compromised with high rates of turnover and a lack of professional development possibilities, teacher retention in education colleges and professional growth remain the major issues. This article considers the potential to revolutionize the approach to these issues with by contribution of AI-driven predictive models to enhance retention strategies and personalised professional development strategies. The research paper explores the role of predictive analytics, predicting professional needs and in-service environments through an extensive synthesis of secondary sources, such as academic and institutional reports and case studies. The examination demonstrates inadequacies in professional development and retention frameworks already present and in particular lack of proactive strategies and customized interventions. This piece of work seeks to guide policymakers, administrators, and educators to tap AI to produce strong, skilled, and committed teaching personnel in the colleges of learning by establishing a set of recommendations that are practical.