AI in Action: Practical Strategies to Optimize Financial Aid

Financial aid has always been one of higher education’s most powerful—and complex—levers. Institutions are expected to balance access, equity, enrollment goals, and net tuition revenue, all while navigating shifting demographics, FAFSA disruptions, and constrained budgets. In recent years, analytics in higher ed has emerged as a critical capability for meeting these demands with greater precision and confidence. 

Today’s most successful campuses are moving beyond hindsight and instinct. They are using predictive and prescriptive analytics to understand student behavior, model financial aid scenarios, and take action where it matters most. This whitepaper explores how AI-driven analytics are being applied in practice—and how institutions can begin using these tools to optimize financial aid strategy. 

Key Takeaways You'll Gather From This Whitepaper Include: 

• How analytics in higher ed enables institutions to move from broad financial aid strategies to precise, student-level decision making. 
• How predictive and prescriptive analytics work together to reveal not only enrollment likelihood, but the actions most likely to influence it. 
• Why financial aid optimization involves allocating dollars with intention to supporting access, equity, and net tuition revenue simultaneously. 
• Why institutions don’t need perfect data to start, just need clear goals, cross-functional alignment, and a plan to act on insights. 
  

Together, predictive and prescriptive analytics move financial aid teams from insight to impact. When institutions treat analytics as a shared strategy—not a standalone tool—adoption accelerates and impact grows.