Abstract
Abstract : In an era of rapid digitization and data overload, students, educators, and institutions face significant challenges in accessing accurate, timely, and relevant examination-related information. This research proposes the development of a Centralized Examination Information System (CEIS) powered by Artificial Intelligence (AI), designed to unify fragmented exam data across various platforms into a single, intelligent portal. The system leverages machine learning algorithms and natural language processing to aggregate, categorize, and personalize examination content, schedules, syllabi, eligibility criteria, and preparation resources from diverse educational bodies. Key features include dynamic content updates, AI-driven recommendation engines, and a user-centric interface that adapts to user profiles, preferences, and academic goals. The proposed system not only simplifies access to crucial examination information but also delivers smart insights such as deadline alerts, trend analysis, and personalized preparation paths based on user behavior and historical data. This paper outlines the system’s architecture, AI components, data integration methods, and user interface design. It also evaluates potential impacts on student preparedness, administrative efficiency, and digital inclusion. By centralizing and intelligently managing examination data, CEIS aims to reduce information asymmetry, enhance decision-making, and democratize access to academic opportunities. The findings demonstrate the system’s potential to transform the examination landscape through automation, accuracy, and adaptive learning.