Abstract
Objective
This presentation focuses on transforming institutional data accessibility through a multi-agent ecosystem designed to overcome the limitations of legacy systems in higher education. The central goal is to reduce technical barriers, improve data accuracy, and deliver real-time insights through conversational, AI-powered agents. The approach seeks to create a more efficient, transparent, and user-friendly framework for accessing critical data related to enrollment, retention, graduation, HR, and other institutional domains.
Context
Many universities face persistent challenges due to outdated systems, fragmented data formats, and limited integration with modern analytics tools. Staff often spend significant time on repetitive data extraction and reporting tasks, leading to burnout, delayed decision-making, and reduced institutional agility. These challenges create a ripple effect, impacting compliance, competitiveness, and the institution’s ability to demonstrate value to stakeholders. Addressing these foundational data barriers is essential to building a responsive, data-driven educational environment that supports strategic planning and student success.
Key Insights
The Office of Institutional Research & Analytics at Rowan University introduces a multi-agent ecosystem anchored in four key pillars derived directly from the first phases of the project’s implementation:
- Efficiency - Reduces data retrieval time from hours to minutes by automating over 80% of common data requests.
- Accuracy - Automated validation minimizes human error by up to 95%, ensuring consistent, reliable, and standardized reporting.
- Governance - Governed datasets using a centralized semantic layer with consistent definitions. Role-based security and controlled access safeguard sensitive data, promoting trust and compliance across institutional users.
- Accessibility - A natural language interface democratizes access, allowing non-technical staff to retrieve data without SQL knowledge, cutting training time by 50%.
Together, these pillars support a shift from reactive data practices to proactive, insight-driven governance, enabling faster decisions, reduced costs, and improved transparency across campus operations.