AI-Powered Institutional Intelligence Hub: From Communication to Student Success & Administrative Decision-Making”

Syndicates

Manas Ranjan Dash, Quazi Mariyam Azam, Yash Kumar, Hari Om Pandey –Galgotias University

Institutional communication & information

In universities, students often miss critical announcements due to fragmented communication across emails, WhatsApp, messaging apps, and portals. Our AI-powered Institutional Intelligence Hub analyzes, centralizes, prioritizes, and personalizes communication. It includes a 24/7 AI assistant for queries and an AI-driven academic risk detection system that analyzes engagement patterns to identify at-risk students and proactively triggers alerts and interventions involving students, faculty, and administrators within an academic setting.

Ineffective communication in higher education directly impacts student success, leading to missed deadlines, stress, and unequal access to information. Students who are less proactive or overwhelmed are disproportionately affected, raising concerns about equity and inclusion. Faculty also face increased workload due to repetitive queries, reducing the time available for meaningful engagement. This situation creates cognitive overload and weakens institutional efficiency. However, it also presents an opportunity for AI to improve clarity, reduce information overload, and enable proactive support systems. By ensuring timely access to critical information and identifying at-risk students early, AI can enhance learning outcomes, improve student well-being, and create a more inclusive and responsive environment.

Our team aims to participate in this challenge to explore how AI can be applied to solve real-world problems in education. With a multidisciplinary background, we seek to understand how intelligent systems can enhance communication, support student success, and improve institutional decision-making. Through this experience, we aim to learn about practical AI implementation, ethical considerations, and scalability. We also seek to explore how technology can reduce inefficiencies and inequalities in education. Ultimately, we aim to transform our idea into a meaningful solution while developing skills in innovation, collaboration, and problem-solving.

Our contribution is the development of an AI-Powered Institutional Intelligence Hub, a centralized platform designed to transform fragmented communication into an intelligent, proactive system that supports student success and improves institutional efficiency. The platform uses AI to automatically organize users into relevant groups while maintaining a clear hierarchy. It features a dual messaging system where critical information is identified and prioritized using Natural Language Processing (NLP), ensuring that important announcements are clearly distinguished from general discussions. Critical information such as deadlines, exam schedules, and official announcements is highlighted and personalized for each student based on their course, department, and role. A key component of our solution is the AI-driven Academic Risk Detection and Intervention system. The platform continuously monitors student engagement patterns, including missed messages, lack of interaction, and ignored deadlines. Based on this data, the system assigns a dynamic risk level to each student. When a student is identified as at risk, the AI proactively sends alerts, reminders, and recommended actions. In more critical cases, it notifies mentors or faculty members, enabling timely human intervention before academic issues escalate. Additionally, the platform includes a 24/7 AI Virtual Assistant that responds to routine student queries, reducing repetitive workload for staff and ensuring instant support for students. The system also provides an analytics and decision-support dashboard for administrators, offering insights into communication effectiveness, student engagement, and risk trends. This enables data-driven decision-making and improves institutional responsiveness. This solution can be implemented in phases, starting with communication centralization and message prioritization, followed by integration of predictive risk detection and analytics. It requires access to institutional data, secure infrastructure, and alignment with privacy and ethical AI standards. Overall, our contribution shifts institutional communication from a passive system to an active, intelligent, and intervention-driven ecosystem that enhances learning outcomes, reduces administrative burden, and supports student success at scale.