Toward Sustainable Workforce Futures: Designing a Career Readiness Model with Generative AI

This study presents the development and evaluation of a predictive model designed to assess career readiness skills from written artifacts, like resumes. As AI-powered tools become increasingly integrated into career readiness programs, there is a growing need to understand how these technologies can support the measurement and growth of career readiness skills. Career readiness is deeply linked to sustainable economic development, and this current study contributes to this goal by exploring how AI can expand and promote access to economically empowering careers through personalized career support. This study examines how a generative AI-powered career coach could use a model to support undergraduate students participating in a summer internship program. Drawing from five established career readiness frameworks, the predictive model was trained to evaluate 14 core skills. Its performance was assessed according to accuracy and alignment with trained human coders as well as participants’ perceptions of the model's recommendations. Planned analysis includes precision, recall, and F1 scores, regression models to establish convergent validity, and thematic analysis of participant feedback. We hope to use our findings from this study to inform future directions for the model, including personalized interventions, occupational identity support, and integration with existing programs. This work contributes to the growing body of literature on the responsible and effective integration of AI in career readiness programming.