This project used an AI-guided forecasting process to help an organizationanticipate enrollment shifts and plan ahead. I combined ten years of departmental enrollment history with contextual factors (institutional policy, economic conditions, program initiatives, etc.), then iteratively prompted ChatGPT to analyze patterns, test assumptions, and generate forward projections. I reviewed and refined the model logic through multiple rounds of questioning to strengthen credibility and practical relevance, and translated the final results into decision-ready visuals and written findings for internal stakeholders.