AI and Institutional Data

Before using AI with institutional data, ask yourself:

• Am I using a University-approved AI tool?
• Does my prompt contain confidential or personally identifiable information?
• Will I verify the accuracy of AI-generated content?
• Am I using AI to support—not replace—my professional judgment?

These principles can help you use AI effectively while protecting institutional data and maintaining trust in decision-making.

Accuracy
Review and verify AI-generated information before using it in reports, communications, or decisions.

Transparency
Be clear about when and how AI contributed to your work, particularly when creating summaries, communications, or analyses for others.

Privacy and Data Protection
Follow FERPA and University policies when working with institutional data. Use only University-approved AI tools for University information.

Human Judgment
AI can support your work, but it cannot replace professional expertise, institutional knowledge, or thoughtful decision-making.

Fairness
Be aware that both data and AI-generated responses may reflect bias. Consider multiple perspectives and review outputs critically.

Responsible Use
Use AI intentionally to improve efficiency, deepen understanding, and support collaboration—not simply to automate decisions.

AI can assist throughout the decision-making process.

Analyze

• Identify patterns and trends in dashboard data
• Summarize survey findings or open-ended responses (using de-identified data)
• Generate questions for deeper exploration
• Compare findings across reports or time periods

Communicate

• Draft emails, reports, and executive summaries
• Develop presentation talking points
• Create meeting agendas
• Refine written communications for different audiences

Plan

• Brainstorm strategies and possible interventions
• Develop action plans based on findings
• Organize project plans and timelines
• Create templates for planning and documentation

Reflect
Use AI as a thinking partner by asking questions such as:

• What patterns stand out?
• What assumptions might I be making?
• What additional information would strengthen this decision?
• What perspectives may be missing?
• What unintended consequences should I consider?