The IR Challenge

Institutional research serves many needs:

• Compliance reporting to federal, state, and accreditation bodies
• Enrollment projections and financial modeling
• Program review and assessment support
• Strategic planning data
• Ad hoc requests from leadership

IR offices are often small relative to their workload. Standard reports consume time that could go to strategic analysis.

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What an IR Agent Does

A vertical AI agent for institutional research accelerates standard work while making data more accessible.

Report Automation

For compliance:

Standard Report Generation: Produce IPEDS, state, and accreditation reports efficiently.

Consistency Checking: Verify data consistency across reports.

Trend Comparison: Highlight significant changes from prior periods.

Documentation: Maintain methodologies and definitions.

Analysis Support

For strategic work:

Data Preparation: Assemble datasets for analysis.

Pattern Identification: Surface significant trends and anomalies.

Scenario Modeling: Project outcomes under different assumptions.

Visualization: Create clear presentations of complex data.

Self-Service Analytics

For the institution:

Question Answering: "How many students from X state enrolled last fall?"

Dashboard Maintenance: Keep institutional metrics current and accessible.

Definition Guidance: Ensure users understand what metrics mean.

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Building on the Right Foundation

IR data is sensitive and consequential. Accuracy and appropriate access control are essential.

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The Opportunity

Institutions with accessible, timely data make better decisions. AI agents can make IR insights more available while maintaining rigor—when built with understanding of IR requirements.

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Universities exploring IR AI should prioritize platforms that integrate across institutional systems, maintain data accuracy, and provide implementation partnerships that understand institutional research. The goal is better decisions—not automation that sacrifices rigor.