Frances Mojica 
Everyone in higher education is talking about AI. From predictive models to automated alerts and personalized learning, it sounds like the future is here. But if you’ve tried to roll out any of these tools and ended up frustrated, you’re not alone. The real issue isn’t the AI itself; it’s that most institutions still don’t have their data in order.
Why AI Sounds Great (But Still Fails)
Walk into any higher ed conference and you’ll hear the same promises: dashboards that predict which students are at risk, systems that improve course planning, and enrollment models that help with long-term forecasting. On paper, it’s exciting. In reality, a lot of these efforts stall or quietly disappear. Why?
The issue isn’t that higher ed lacks data. Most colleges and universities are sitting on years of it – application stats, course performance, attendance, financial aid, and student engagement. The problem is coordination.
Data is spread across departments, locked in spreadsheets, and manually updated across disconnected systems, making it difficult for decision-makers to view information holistically and understand how it interrelates.
Here’s what that means in practice:
- If enrollment numbers are delayed, any predictions based on them won’t be timely or reliable.
- If your IT team spends all their time cleaning up files, they don’t have the time to analyze trends.
- If leadership can’t see real-time data across departments, strategy becomes guesswork.
Getting the Basics Right Before You Layer on AI
Before investing in predictive tools, it’s worth asking:
- Do we have shared definitions across departments?
- Can decision-makers access real-time, institution-wide metrics?
- Is there a single source of truth?
If you can’t confidently say yes to those, AI won’t solve your problems. It’ll just amplify the gaps. The institutions seeing results from AI didn’t start with the latest tool – they started with clean, centralized, and well-governed data. They trained teams to understand and act on data, then they brought in AI to scale that insight further.
If It’s Not Visible, It’s Not Fixable
Higher ed doesn’t need to chase every new tech trend. It needs clarity. When systems are aligned and decision-makers have access to real-time, trusted data, that’s when the real benefits of AI (or any tool) can start to show up:
- Improved student retention and graduation rates from identifying at-risk students early and enabling timely interventions.
- Sharper enrollment management through real-time forecasting of program and geographic demand, guiding recruitment efforts.
- Optimized course planning and faculty scheduling by using data to reduce course cancellations, overstaffing, or under-enrollment.
- Stronger student services outreach by helping advisors and support teams prioritize students most in need of assistance, from academic to mental health support.
Explore how to make this a reality on your campus.
Download the full whitepaper: From Fragmented Systems to Strategic Clarity
